Posts tagged ‘cybersecurity’

Feb 26

Roundup of agentic AI forecasts and market estimates, 2026

Agentic AI spending is projected to reach $201.9 billion in 2026 (Gartner), overtaking chatbot spending by 2027. Four independent firms size the standalone market at $7–8 billion with 40%+ CAGRs. But adoption lags the money: only 23% of organizations have scaled agent deployments (McKinsey), and 40% of projects face cancellation by 2027 (Gartner).

Fortune Business Insights projects $7.29 billion in 2025, reaching $139.19 billion by 2034 at 40.5% CAGR. Precedence Research sizes it at $7.55 billion in 2025, growing to $199.05 billion by 2034 at 43.84% CAGR. MarketsandMarkets puts the figure at $7.06 billion in 2025, reaching $93.20 billion by 2032 at 44.6% CAGR. Deloitte’s TMT Predictions 2025 estimates $8.5 billion in 2026, growing to $35 to $45 billion by 2030.

Every major forecast agrees on direction. None agrees on scale. The standalone agentic AI market lands between $7 billion and $8.5 billion. Gartner’s broader view, counting agentic capabilities embedded across enterprise software, reaches $201.9 billion in 2026. That 25x gap is not a contradiction. It is a measurement problem, and the takeaways below reflect both realities. The following are the key takeaways from agentic AI forecasts published in 2026 so far:

Key takeaways

Worldwide AI spending will reach $2.52 trillion in 2026, growing 44% year-over-year. That number jumped roughly $500 billion from the September forecast, which had pegged the market just above $2 trillion. Infrastructure takes $1.37 trillion, 54% of total spend. AI software follows at $452.5 billion, up 60%. AI services add $588.6 billion. AI-optimized servers alone account for $421.6 billion, growing to 49%. Gartner expects spending to grow by another 30% in 2027 and surpass $3 trillion. I have tracked these forecasts through multiple iterations. The revisions keep going in one direction. Source: Gartner press release, January 15, 2026

Gartner projects $4.71 trillion in global AI spending by 2029. The fastest growth isn’t in infrastructure. Synthetic data generation leads all categories at 178% CAGR, followed by the broader AI Data market at 155%. Agentic AI compounds at 119%, expanding from $15 billion to $753 billion by 2029. AI Infrastructure, the largest category by dollars, grows at just 29%. The money is following the bottlenecks. Source: Gartner 4Q25: $4.71T AI Market Proves Agentic AI and Data Readiness Are the Only Race That Matters, Software Strategies Blog, January 22, 2026 Link: https://softwarestrategiesblog.com/2026/01/22/gartner-4q25-agentic-ai-data-readiness-4-71t-market/

The AI cybersecurity market is predicted to hit $51.3 billion in 2026, nearly doubling from $25.9 billion in 2025. But the category masks a structural imbalance. AI-amplified security, where AI defends the enterprise, captures 94.5% of spending at $48.5 billion. Securing AI, where the enterprise defends its own AI systems, gets $2.8 billion. Enterprises are investing 17x more in using AI as a security tool than in protecting the AI itself. Both sub-segments grow at similar CAGRs (74% vs. 72%), which means the dollar gap widens every year. By 2029, AI-amplified security reaches $160.4 billion, while securing AI hits just $11.6 billion. One is a tool. The other is the thing that needs protecting. Source: Gartner Forecasts Agentic AI Will Overtake Chatbot Spending by 2027, Software Strategies Blog, February 16, 2026 Link: https://softwarestrategiesblog.com/2026/02/16/gartner-forecasts-agentic-ai-overtakes-chatbot-spending-2027/

AI Data sits alone in the upper-right quadrant of Gartner’s spending map, compounding at 155% CAGR with 277% growth in 2026. AI Cybersecurity and AI Models cluster above 67% CAGR. AI Infrastructure anchors the chart as the largest bubble, but grows at just 29%. Global AI spending reaches $1.8 trillion in 2025 and $4.7 trillion by 2029. The acceleration is not in compute. It is in data readiness, security architecture, and agentic capabilities. By 2028, software with agentic capabilities crosses 50% of total application software spend, up from 2% in 2024. Non-agentic software spending starts declining in 2027. Source:Data Readiness and Security Are Driving AI’s $4.7 Trillion Run, Software Strategies Blog, December 22, 2025 Link: https://softwarestrategiesblog.com/2025/12/22/data-readiness-security-driving-ai-4-7-trillion/

Gartner’s AI spending forecast reaches $2.53 trillion in 2026 and $4.71 trillion by 2029. Eight markets. One pattern. AI Infrastructure dominates absolute dollars at $1.37 trillion in 2026 but grows at just 29% CAGR. AI Data, the smallest segment at $3.1 billion, compounds at 155%. AI Cybersecurity nearly doubles to $51.3 billion. AI Software hits $452.5 billion, growing 60% year-over-year as agentic capabilities reshape the category. The growth rates tell you where the bottlenecks are breaking. Source: Data Readiness and Security Are Driving AI’s $4.7 Trillion Run, Software Strategies Blog, December 22, 2025 Link: https://softwarestrategiesblog.com/2025/12/22/data-readiness-security-driving-ai-4-7-trillion/

Nearly nine in ten organizations now use AI in at least one business function, up from 78% a year ago, but nearly two-thirds have not begun scaling it across the enterprise. Only 6% qualify as high performers where AI contributes more than 5% to EBIT. Sixty-two percent of organizations are at least experimenting with AI agents, yet in no individual business function are more than 10% scaling them. High performers are three times more likely than peers to fundamentally redesign workflows and three times more likely to have senior leaders demonstrating ownership of AI initiatives. More than one-third of high performers commit over 20% of their digital budgets to AI, and about three-quarters have reached the scaling phase, versus one-third of other organizations. Source: McKinsey / QuantumBlack, The state of AI in 2025: Agents, innovation, and transformation, November 2025

Valued at $638.23 billion in 2024, the global AI market is projected to reach $3,680.47 billion by 2034, expanding to a CAGR of 19.20%. North America holds 31.80% market share. The software segment dominates at 51.40%, while machine learning leads by technology at 36.70%. Healthcare is expected to record the highest CAGR of 36.50% across end-use segments. Among regions, Asia-Pacific is expected to grow at 19.8% CAGR from 2025 to 2034, with AI projected to add up to $3 trillion to the region’s GDP by 2030, driven by national AI strategies in China, India, and Japan. Source: Precedence Research, AI Market Size, Growth & Trends, September 2025

Nearly $7 trillion. That’s the capital outlay data centers will require by 2030 to keep pace with demand for compute power. Of that, $5.2 trillion goes toward AI-ready facilities and $1.5 trillion toward traditional IT workloads. Global demand for data center capacity could almost triple by 2030, with about 70% of new demand coming from AI workloads. Three investment scenarios range from $3.7 trillion (constrained demand) to $7.9 trillion (accelerated demand, adding 205 incremental GW). The 60% majority of investment—$3.1 trillion—flows to technology developers and designers producing chips and computing hardware. Source: McKinsey, The cost of compute: A $7 trillion race to scale data centers, April 2025

Inference already consumed half of all AI compute in 2025. That number will grow to two-thirds in 2026 and reach 75% of all AI compute needs by 2030. Global data center capacity is projected to nearly double from 103 gigawatts to 200 GW by 2030, yet U.S. data centers already face a capacity shortfall exceeding 11 GW, with the cumulative gap expected to exceed 40 GW by 2028. North American data center capacity alone will increase eightfold, from 5.6 GW in 2024 to 44 GW by 2030. Operators are increasingly deploying edge facilities closer to end users to reduce latency as inference-dominated workloads drive a fundamental redesign of data center architectures. Source: Avid Solutions, 13 Data Center Growth Projections, January 2026

Generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually to the global economy, increasing the projected impact of all AI by 15 to 40%. About 75% of the value falls across four areas: customer operations, marketing and sales, software engineering, and R&D. Half of today’s work activities could be automated between 2030 and 2060, with a midpoint in 2045—roughly a decade earlier than previously estimated. When embedding effects in existing software are included, the total economic benefit rises to $6.1 trillion to $7.9 trillion annually. Source: McKinsey, The economic potential of generative AI, June 2023

The global AI market hit $294.16 billion in 2025 and is projected to grow to $2,480.05 billion by 2034, at a CAGR of 26.60%. The Banking, financial services and insurance (BFSI) segment holds 18.90% market share, while healthcare is expected to record the highest CAGR of 36.50%. In the U.S. alone, the AI market was estimated at $146.09 billion in 2024 and is predicted to reach $851.46 billion by 2034. The number of AI companies funded globally in 2024 totaled 2,049, with U.S.-funded companies accounting for 1,143, signaling strong investor confidence in the sector’s expansion potential. Source: Fortune Business Insights, AI Market Size, Growth & Trends by 2034

Big Tech’s AI capex hit $405 billion in 2025, up from a $250 billion estimate at the start of the year. Sell-side analysts have underestimated AI spending every quarter for two years running. A decade ago, Big Tech’s trailing-twelve-month capex was $24 billion—15x less than today. AI data center costs are projected at $3 trillion to $8 trillion, with gigawatt capacity expected to grow 3.5x by 2030. Source: IO Fund, Big Tech’s $405B Bet, November 2025

The global AI market was valued at $371.71 billion in 2025 and is projected to reach $2,407.02 billion by 2032, growing at a CAGR of 30.6%. Hyperscalers accounted for 53% of chip purchases in 2023, spurring 156% market growth from 2023 to 2024. While demand from hyperscalers is expected to moderate, growth of 41% is still forecast from 2025 to 2026. Enterprises are moving from cloud reliance to in-house AI infrastructure investments, particularly for cost-effective inference solutions, as edge AI gains traction through AI-enabled PCs and mobile devices. Source: Markets and Markets, AI Market Report 2025-2032

At $602 billion projected for 2026, hyperscaler capex has entered uncharted territory. Amazon, Microsoft, Google, and Meta will each exceed $100 billion individually, pushing capital intensity to 45-57% of revenue. Total hyperscaler capex from 2025-2027 is projected at $1.15 trillion, more than double the $477 billion spent from 2022-2024. Morgan Stanley and JP Morgan suggest the technology sector may need to issue $1.5 trillion in new debt over the next few years to finance AI infrastructure construction. The sheer scale of debt issuance mirrors patterns seen during the fiber-optic buildout of the late 1990s. Source: Multiple sources compiled by Introl, January 2026

The number of software companies using consumption-based pricing more than doubled between 2015 and 2024, as AI introduces new variable costs that make traditional perpetual licenses obsolete. SaaS remains dominant, but the next wave is outcome-aligned pricing that scales with actual AI usage. Software businesses that successfully adopt consumption-based pricing aligned with usage and outcomes may be better positioned to capture AI-driven value and differentiate themselves in a rapidly evolving market where the cost of each AI inference adds a new variable to the P&L. Source: McKinsey, AI adjusts the software bill, January 27, 2026

Data center capacity needs for AI and non-AI workloads could almost triple by 2030, with AI capacity increasing 3.5 times and making up roughly 70% of the total. Under a continued-momentum scenario, total capacity demand rises from 82 GW in 2025 to 219 GW by 2030, with incremental AI capacity ranging from 13 GW in 2025 to 31 GW in 2030, totaling 124 GW of new AI capacity. Non-AI workloads grow from 38 GW to 64 GW over the same period. Average power densities in AI-ready data centers have more than doubled in just two years and are expected to rise nearly four times by 2027. Source: McKinsey, Data center demands (Week in Charts), May 2025

U.S. data-center spending exceeded half a trillion dollars in 2025. The U.S. and China drove a massive expansion in AI-related computing capacity through 2024, with the U.S. pulling further ahead in the first half of 2025. AI-related trade accounted for nearly half of all merchandise trade growth in that period, despite representing only 15% of total trade volume. The infrastructure boom is reshaping international commerce, with surging demand for servers, graphics cards, and related components essential to AI training and inference now a dominant force in global supply chains. Source: Federal Reserve Board, FEDS Notes: The Global Trade Effects of the AI Infrastructure Boom, February 2026

The generative AI market is expanding from $71.36 billion in 2025 to $890.59 billion by 2032, at a CAGR of 43.4%. North America accounted for 43.05% of global revenue in 2025. Text remains the dominant data modality due to its foundational role in enterprise workflows, while the services segment is gaining traction for scalability and cost-effectiveness. Foundation model delivery platforms verticalized adoption across industries, and the rapid scaling of AI-native infrastructure are the three key forces driving the market as of 2025. The 43.4% CAGR makes this one of the fastest-expanding technology subsegments in history. Source: MarketsandMarkets, Generative AI Market Report, Global Forecast to 2032

The generative AI market reached $37.89 billion in 2025 and is projected to hit $1.2 trillion by 2035, a 37% compound annual growth rate. Transformer architectures account for more than 42% of technology revenue, driven by text-to-image and text-to-video applications. Software captures over 65% of total revenue. North America holds 41% of the market. Asia-Pacific is the fastest-growing region at a 27.6% CAGR through 2035. Financial services is expected to lead sector growth at 36.4%, fueled by fraud detection, risk management, and regulatory compliance demands. Source: Precedence Research, Generative AI Market Size, January 2026

GPUs captured 89% of AI processor revenue in 2025, but FPGA and ASIC alternatives are growing at a 17% CAGR through 2031. Hardware accounted for 68% of all AI infrastructure spending last year. North America held 40% of the market, backed by $52.7 billion in CHIPS Act grants and hyperscalers operating roughly 60% of global AI compute capacity. Liquid cooling reached 18% of AI server racks as power densities crossed 100 kilowatts per rack, the threshold where air cooling fails. Asia-Pacific is projected to grow fastest at 16.4% CAGR through 2031, driven by China’s $50 billion semiconductor fund and $15 billion in hyperscaler commitments across India. Source: Mordor Intelligence, AI Infrastructure Market Size, Trends & Growth Drivers 2031

Nearly one in four Americans has already made a purchase through AI. Morgan Stanley Research estimates agentic shoppers will drive $190 billion to $385 billion in U.S. e-commerce spending by 2030, capturing 10% to 20% of market share. Grocery and consumer packaged goods lead adoption, with 49% of AI-assisted buyers transacting in those categories. AI shopping agent users are projected to reach 126 million by 2030, up from near zero today, while traditional e-commerce users decline from 264 million to 149 million over the same period. Source: Morgan Stanley Research, Agentic Commerce Market Impact Outlook, December 2025 Link: https://www.morganstanley.com/insights/articles/agentic-commerce-market-impact-outlook

Feb 16

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Gartner forecasts agentic AI will overtake chatbot spending by 2027

Agentic AI spending grows 141% in 2026 to $201.9 billion. By 2027, it will overtake chatbot and assistant spending for the first time. Then chatbot spending starts declining. I’ve tracked Gartner’s AI forecasts through multiple iterations. This crossover changes where security risk concentrates for every security professional reading this.

The crossover is in the segment-level data tables of Gartner’s Forecast: AI Spending, Worldwide, 2024–2029, 4Q25. The headline number is well known: $2.53 trillion in 2026, $4.7 trillion by 2029 at 33% CAGR. The segment breakdowns are not. Eight markets. Nineteen sub-segments. The sub-segment data tells a different story than the top line.

This is Gartner’s first dedicated AI spending forecast, and I’ve been waiting for it. Gartner states that comparisons to previous AI estimates are not meaningful because the scope widened, adding AI cybersecurity, agentic AI as a separate segment from chatbots, AI data technology, and expanded infrastructure coverage. Gartner writes, “This is the first iteration of the forecast on AI spending that Gartner has published. Gartner has significantly expanded and modified its AI forecast coverage. Spending comparisons to previous iterations are therefore not meaningful as the scope has widened. This includes both coverage of new markets and broadened definitions of the types of AI spending that are reflected in some market segments.”

Forrester’s Predictions 2026: Cybersecurity and Risk arrives at the same warning from a different angle: an agentic AI deployment will cause a publicly disclosed breach in 2026, leading to employee dismissals. Two firms. Same conclusion. The spending data explains why.

CAPTION: Total worldwide AI spending, 2024–2029. $1.14T to $4.71T. 33% CAGR. Growth decelerates from 54% (2025) to 16% (2029) as the base expands. Source: Gartner Forecast: AI Spending, 4Q25 (December 2025).

The full market breakdown

AI infrastructure dominates at $1.37 trillion, 54% of the total. AI software follows at $452.5 billion, growing 60% year-over-year. AI services add $588.6 billion. AI cybersecurity and AI data are the outliers: growing at 74% and 155% CAGR, respectively, rates that dwarf everything else in the forecast.

Source: Gartner Forecast: AI Spending, Worldwide, 2024–2029, 4Q25 (December 19, 2025). All figures in U.S. dollars. CAGR = 2024–2029. Gartner press release: https://www.gartner.com/en/newsroom/press-releases/2026-1-15-gartner-says-worldwide-ai-spending-will-total-2-point-5-trillion-dollars-in-2026

Infrastructure takes 54% of every AI dollar

AI-optimized servers alone account for $421.6 billion in 2026, growing to $699.7 billion by 2029. AI processing semiconductors add $289.4 billion. AI-optimized IaaS hits $38.3 billion at 71% CAGR, the fastest-growing infrastructure sub-segment. AI network fabric, a new category in this forecast, reaches $28.7 billion.

Infrastructure’s share drops from 54% to 48% by 2029 as software and services scale faster. The capital-intensive build-out phase is not over.

The agentic crossover nobody is planning for

Gartner now splits AI software into chatbots/assistants and agentic AI. The spending lines cross in 2027.

CAPTION: Agentic AI spending overtakes chatbot/assistant spending by 2027. Chatbots peak at $264.7B then decline. Agentic AI grows at 119% CAGR to $752.7B by 2029. Source: Gartner Forecast: AI Spending, 4Q25 (December 2025). AI Software segment, Table 1-2.

Source: Gartner Forecast: AI Spending, 4Q25 (December 2025). CAGR = 2024–2029.

Chatbots talk to people. Agents act on behalf of people. They access databases, execute transactions, chain multi-step workflows without human approval at each step. The attack surface has moved well beyond conversation windows. Agents are autonomous decision engines with production access.

Gartner’s Top Trends in Cybersecurity for 2026 lists agentic AI oversight as the number-one trend. Forrester’s Predictions 2026: Cybersecurity and Risk goes further: an agentic AI deployment will cause a public breach this year, and employees will lose their jobs for it. Forrester senior analyst Paddy Harrington calls it a “cascade of failures,” not a single point of error. Two analyst firms. Different methodologies. Same conclusion. Security strategies built for chatbot-era risk have a shelf life measured in quarters, not years.

AI cybersecurity is two markets, not one

Gartner created a dedicated AI cybersecurity market for the first time in this forecast. It nearly doubles in 2026. But the category name hides a structural split that matters more than the growth rate.

Source: Gartner Forecast: AI Spending, 4Q25 (December 2025). CAGR = 2024–2029.

Two sub-segments. Two very different problems.

AI-amplified security ($48.5 billion, 94.5% of the market) is what most enterprises mean when they say “AI cybersecurity.” This is AI working for your security team. Machine learning models that analyze network traffic patterns and flag anomalies faster than a human analyst can. Natural language processing that reads threat intelligence feeds and correlates indicators of compromise across millions of data points in seconds. Automated triage systems that prioritize which of the 11,000 daily alerts actually need a human response. AI-powered endpoint detection that identifies malware variants that signature-based tools miss. Behavioral analytics that learn what normal looks like for each user and flag deviations. Security orchestration platforms that automate incident response playbooks, reducing mean time to containment from hours to minutes.

This is the category where enterprises are spending aggressively. And for good reason. The math on analyst workloads demands it. Security operations centers are drowning in alerts, facing a persistent talent shortage, and defending attack surfaces that expand every quarter. AI-amplified tools address all three.

Securing AI ($2.8 billion, 5.5% of the market) is the other problem. AI-amplified security puts AI to work defending the enterprise. Securing AI reverses the relationship entirely — defending the AI itself. Protecting the models, the training data, the inference pipelines, the agent workflows, and the decision outputs that enterprises are deploying at $2.53 trillion in 2026. Prompt injection defenses. Model access controls. Training data poisoning detection. Output validation. Agent permission boundaries. Audit trails for autonomous decisions.

The distinction matters because they protect different things. AI-amplified security protects your enterprise using AI. Securing AI protects the AI itself. One is a tool. The other is the thing that needs protecting. Enterprises are investing 17 times more in the tool than in protecting the thing the tool runs on.

Shadow AI is not just employees using ChatGPT

Gartner names the mechanism driving AI software growth: vendor push. Software providers are integrating GenAI and agentic AI into existing product lines. AI software grows from $143 billion in 2024 to $981 billion by 2029 at 47% CAGR.

For CISOs, vendor push changes the equation. AI capabilities are being added to tools already in production. Often without explicit procurement decisions. The AI features embedded in your existing ERP, CRM, and developer platforms may already exceed what your security team has inventoried. Shadow AI is vendors activating AI inside products you already own.

The smallest market with the biggest growth rate

AI data technology: $134 million in 2024. $3.1 billion in 2026. $14.6 billion by 2029. The 155% CAGR is the highest in the forecast. The 277% year-over-year growth in 2026 is the steepest single-year jump of any segment.

Synthetic data generation is the standout sub-segment, going from $41 million to $6.8 billion by 2029. Gartner is direct: enterprises need AI-ready data with proper labeling, quality checks, and compliance. For organizations running AI projects on ungoverned data, the readiness gap compounds every quarter.

CAPTION: AI spending markets ranked by five-year CAGR. AI Data (155%) and AI Cybersecurity (74%) lead. AI Infrastructure is the largest by absolute dollars. Source: Gartner Forecast: AI Spending, 4Q25 (December 2025).

Indirect services are the governance blind spot

Indirect AI services, where AI is a supporting component in a larger project, grow from $78.4 billion in 2024 to $255.9 billion in 2026 at 50% CAGR. Direct AI services hit $332.8 billion. By 2028, indirect overtakes direct.

Indirect AI means capabilities embedded in consulting and implementation projects that procurement does not classify as AI. If you cannot see it in your AI inventory, you cannot govern it.

Servers are a bigger market than AI software

AI-optimized servers alone hit $421.6 billion in 2026, just below the entire AI software market at $452.5 billion. By 2029, servers reach $699.7 billion. Cloud providers are building capacity for AI workloads that have not materialized at scale. The infrastructure is ahead of the applications.

The enterprise agentic stack is showing up in spending data

Gartner’s DSML segment includes a dedicated agent builder platforms sub-segment at $5.0 billion in 2026, reaching $13.7 billion by 2029. AI observability and governance adds $1.3 billion, growing to $4.0 billion. The xOps sub-segment (MLOps, DataOps, ModelOps) is the largest at $15.0 billion.

Together, these form the tooling layer for building, monitoring, and governing agents in production. The enterprise agentic stack is materializing in the spending data. Most organizations have not formalized it in their architecture.

The numbers that belong in your next board deck

If you take one thing from this forecast into a budget meeting, take this table. I built it from the raw spreadsheet data. Six years of AI deployment spending next to AI security spending. The bottom row is the one that gets the questions.

Source: Gartner Forecast: AI Spending, 4Q25 (December 2025). All percentages derived from Gartner’s published data tables (Tables 1-1 and 1-2).

The ratio improves over time. Securing AI goes from 0.07% in 2024 to 0.25% by 2029. But watch the absolute numbers. In 2029, enterprises will spend $4.71 trillion deploying AI and $11.6 billion securing it. The percentage gets better. The dollar gap gets wider. Every year, the market grows its way into a larger exposure.

Where I think this lands

Three things worth tracking from the segment data:

The agentic crossover. Agentic AI overtakes chatbot spending in 2027. The enterprise risk profile shifts from conversational data leakage to autonomous decision-making at scale. CISOs who build agentic governance frameworks in 2026 position themselves before the inflection. The spending curve says the window is narrowing.

The securing-AI gap. $2.8 billion to protect AI systems in a year when $2.53 trillion deploys them. Enterprises are enthusiastic about using AI for defense. The investment in defending AI itself has not caught up.

Data readiness is the bottleneck. The 277% growth in AI data spending confirms that AI without governed data delivers diminished returns. Data classification investments directly enable or constrain AI ROI.

If your security budget is growing at 12% and AI deployment inside your enterprise is growing at 44%, the gap compounds every quarter. You cannot close it by holding steady. The organizations getting this right treat AI security as a proportion of AI deployment, not a fixed line item.

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Sources

Gartner, Forecast: AI Spending, Worldwide, 2024–2029, 4Q25, December 19, 2025, ID G00843179.

Gartner press release (January 15, 2026): https://www.gartner.com/en/newsroom/press-releases/2026-1-15-gartner-says-worldwide-ai-spending-will-total-2-point-5-trillion-dollars-in-2026

Gartner, Top Trends in Cybersecurity for 2026 (February 5, 2026): https://www.gartner.com/en/newsroom/press-releases/2026-02-05-gartner-identifies-the-top-cybersecurity-trends-for-2026

Gartner, IT Spending Forecast 1Q26 (February 3, 2026): https://www.gartner.com/en/newsroom/press-releases/2026-02-03-gartner-forecasts-worldwide-it-spending-to-grow-10-point-8-percent-in-2026-totaling-6-point-15-trillion-dollars

Forrester, Predictions 2026: Cybersecurity and Risk (October 2025): https://www.forrester.com/blogs/predictions-2026-cybersecurity-and-risk/

All dollar figures in U.S. dollars. Growth rates and CAGR derived from Gartner’s published data tables (Tables 1-1 and 1-2).

Feb 10

Top 6 cybersecurity trends from Gartner’s 2026 Security Forecast

Over 57% of employees are using personal GenAI accounts for work. A third of them admit to uploading sensitive data into tools their security teams haven’t approved. Meanwhile, agentic AI is proliferating through no-code platforms and vibe coding, creating attack surfaces most CISOs can’t see, let alone govern. And quantum computing? No longer a 10-year planning horizon. It’s a 2030 action deadline.

Gartner’s Top Trends in Cybersecurity for 2026 report, released February 5, 2026, identifies six forces reshaping how CISOs must operate. These cut across governance, AI adoption, identity, workforce, and cryptographic strategy simultaneously. None of them is incremental.

The trends report lands alongside Gartner’s updated Forecast: Information Security, Worldwide, 2023–2029, 4Q25 (G00843183, December 18, 2025) and the Forecast Analysis: Information Security, Worldwide, 2026 (G00838442, February 5, 2026), which together project global information security spending reaching $244.2 billion in 2026, up 13.3% in current U.S. dollars. I’ve tracked this forecast through multiple quarterly updates. The trajectory keeps steepening. The six trends below explain where that money is going and why.

“Cybersecurity leaders are navigating uncharted territory this year as these forces converge, testing the limits of their teams in an environment defined by constant change,” said Alex Michaels, Director Analyst at Gartner. “This demands new approaches to cyber risk management, resilience, and resource allocation.”

The spending backdrop: $244 billion and accelerating

Before getting into the six trends, context matters. Gartner’s 4Q25 forecast shows the three major security segments all growing at double-digit constant currency rates in 2026:

Source: Gartner Forecast: Information Security, Worldwide, 2023–2029, 4Q25 Update (G00843183). Constant currency rates.

Cloud security remains the fastest-growing subsegment at 28.8% growth in 2026. Nothing else comes close. The combined cloud security market (cloud security posture management, cloud access security brokers, and cloud workload protection platforms) is projected to reach $32.4 billion by 2029, with a 25% CAGR in constant currency. I’ve been watching this subsegment accelerate for three quarters straight. CSPM alone is growing at a 31.30% CAGR.

Cloud security spending reaches $32.4 billion by 2029. CSPM leads at 31.30% CAGR. Source: Gartner 4Q25 Forecast. (Please click on the image to expand for easier reading)

Trend 1: Agentic AI demands cybersecurity oversight

This is the trend that touches everything else on this list. Employees and developers are deploying AI agents through no-code/low-code platforms and “vibe coding” at a pace that outstrips security governance. Unmanaged AI agent proliferation. Unsecured code. Compliance violations that most security teams don’t even have visibility into yet. That’s the picture Gartner is painting.

Gartner’s recommendation is blunt: cybersecurity leaders must identify both sanctioned and unsanctioned AI agents operating within their environments, enforce access controls and data guardrails, and develop incident response playbooks specific to agent-driven threats.

“While AI agents and automation tools are becoming increasingly accessible and practical for organizations to adopt, strategic cybersecurity planning for these technologies is essential,” said Michaels. “Cybersecurity leaders must work cross-functionally to manage agentic AI adoption, identifying sanctioned and unsanctioned AI agents, enforcing data access controls, and developing incident response playbooks.”

The spending data backs this up. Gartner’s 4Q25 forecast projects the AI-amplified security market reaching $160 billion by 2029, up from $49 billion in 2025. Gartner is clear that this isn’t additive spending. It represents the portion of existing security products that now embed AI capabilities. But the expectation tells the story: over 75% of enterprises will use AI-amplified cybersecurity products by 2028, up from less than 25% in 2025. Vendors that don’t embed AI will lose shelf space. (For more on AI security platforms, see Gartner’s Top Strategic Technology Trends for 2026, which predicts that over 50% of enterprises will use AI security platforms to protect their AI investments by 2028.)

Trend 2: Global regulatory volatility drives cyber resilience efforts

Regulators are getting personal. Boards and executives now face direct liability for compliance failures. Not just organizational fines, but individual accountability. The penalties for inaction have moved from theoretical to career-ending. Across multiple jurisdictions simultaneously.

Gartner advises cybersecurity leaders to formalize collaboration across legal, business, and procurement teams to establish clear accountability for cyber risk. Align control frameworks to recognized standards. Address data sovereignty concerns before they become enforcement actions. The organizations doing this well are treating regulatory preparedness as a core security function, not an annual compliance checkbox.

This is where the spending data gets interesting. Gartner’s forecast shows security consulting services growing from $24.2 billion (2024) to $36.6 billion (2029), adding $12.4 billion in five years. Security professional services follow a similar trajectory: $27.3 billion to $40.8 billion, adding $13.5 billion. Organizations are buying outside expertise because they can’t build regulatory competence fast enough in-house. I’ve been covering these numbers for three quarters, and the services growth is the part of the forecast that keeps surprising me.

Infrastructure protection adds $26.4 billion between 2024 and 2029, the largest absolute growth of any subsegment. Source: Gartner 4Q25 Forecast. (Please click on the image to expand for easier reading)

Trend 3: Post-quantum computing moves into action plans

Gartner predicts advances in quantum computing will render the asymmetric cryptography that organizations rely on unsafe by 2030. Four years. That’s the window to adopt post-quantum cryptography alternatives before “harvest now, decrypt later” attacks start cashing in on data that adversaries are collecting today.

Organizations need to identify their cryptographic deployments, assess data sensitivity and lifespan, and prioritize cryptographic agility. That last phrase keeps coming up in my conversations with CISOs. The ability to swap encryption methods without re-architecting entire systems. Swapping an algorithm is one thing. Doing it across a production environment without downtime is an entirely different problem.

“Post-quantum cryptography is reshaping cybersecurity strategies by prompting organizations to identify, manage, and replace traditional encryption methods, while prioritizing cryptographic agility,” said Michaels. “By investing in these capabilities and prioritizing migration now, assets will be secured when quantum threats become a reality.“

The encryption market in Gartner’s 4Q25 forecast grows from $1.04 billion in 2023 to $2.04 billion by 2029 at an 11.95% CAGR. A 2.0x increase. For what has historically been one of the slower-growing security subsegments, that’s a significant acceleration. Quantum urgency is changing the math.

Trend 4: Identity and access management adapts to AI agents

AI agents are breaking traditional IAM models. Plain and simple. Identity registration and governance, credential automation, and policy-driven authorization weren’t designed for autonomous machine actors that can initiate actions, access data, and interact with systems without human intervention. The scale problem compounds fast: when every employee can deploy dozens of AI agents, the identity surface area explodes.

Gartner recommends a targeted, risk-based approach. Invest where gaps and risks are greatest. Leverage automation where possible. The practical starting point is understanding which AI agents carry the most privilege and the least oversight. Those are your highest-risk identities right now, and most organizations haven’t inventoried them.

The identity market is already significant. Gartner’s 4Q25 forecast shows identity access management growing from $18.7 billion (2024) to $29.0 billion (2029), adding $10.3 billion in five years. That’s before the full scale of agentic AI identity requirements hits the market. IAM vendors that solve machine-actor identity at scale will capture a disproportionate share of that $10.3 billion growth.

Trend 5: AI-driven SOC solutions destabilize operational norms

AI-enabled security operations centers are enhancing alert triage and investigation workflows. The technology works. But deploying AI into a SOC doesn’t automatically reduce headcount needs. It changes the skill mix. Analysts who excelled at manual triage need different capabilities to oversee AI-driven workflows. Organizations are discovering this the hard way. That’s an organizational transformation challenge, and throwing more technology at it doesn’t help.

“To realize the full potential of AI in security operations, cybersecurity leaders must prioritize people as much as technology,” said Michaels. “Strengthening workforce capabilities, implementing human-in-the-loop frameworks into AI-supported processes and aligning adoption with clear strategic objectives will be critical to maintaining resilience as SOCs evolve.”

The talent dimension makes this harder than it already sounds. ISC2’s 2024 Cybersecurity Workforce Study, published in October 2024, documented a global workforce gap of 4.8 million professionals, a 19% year-over-year increase. The active workforce flatlined at 5.5 million (up just 0.1%). The numbers are brutal: 25% of organizations reported cybersecurity layoffs in 2024. 37% faced budget cuts. 90% report skills shortages. 58% believe the shortage puts their organization at significant risk. On the spending side, managed security services are growing at 11.1% in 2026, the fastest rate in the services segment. Organizations can’t hire fast enough, so they’re buying managed SOC capacity instead.

Trend 6: GenAI breaks traditional cybersecurity awareness tactics

Existing security awareness programs are failing. Full stop. A Gartner survey of 175 employees conducted between May and November 2025 found that 57% use personal GenAI accounts for work purposes, while 33% admit to uploading sensitive information to tools their organizations haven’t sanctioned. Those numbers should alarm every CISO reading this. A third of your workforce is actively feeding proprietary data into tools you can’t audit.

Gartner recommends shifting from general awareness training to adaptive behavioral programs that include AI-specific tasks. Generic compliance videos won’t cut it here. The organizations getting this right are making approved GenAI tools easy to access and unsanctioned tools hard to justify. Trying to ban GenAI outright just drives usage underground and costs you talent.

Strengthening governance, embedding secure practices, and establishing clear policies for authorized GenAI use will reduce exposure to privacy breaches and intellectual property loss. The governance gap on GenAI usage is, in my view, the most underestimated risk on this entire list. Every other trend has a spending line item attached to it. This one requires behavioral change, which is harder to buy.

Total market trajectory: $173.5 billion to $323.5 billion

Gartner’s year-by-year spending trajectory shows the acceleration curve these six trends are riding:

Source: Gartner Forecast: Information Security, Worldwide, 2023–2029, 4Q25 Update (G00843183, December 18, 2025). Current U.S. dollars.

CSPM and CASB lead all security categories with 31% and 26% CAGR through 2029. Source: Gartner 4Q25 Forecast. (Please click on the image to expand for easier reading)

What this means for CISOs

Three of the six trends (agentic AI oversight, IAM for machine actors, and GenAI awareness) are fundamentally about the same problem: autonomous AI systems operating inside enterprise environments without adequate governance. The other three (regulatory volatility, post-quantum readiness, and AI-driven SOCs) are the structural forces those governance failures will collide with. That convergence is the signal about where 2026 budgets need to go.

The organizations that will navigate this environment successfully are doing three things simultaneously:

Mapping their AI agent footprint now. If you don’t know how many AI agents are operating across your environment, sanctioned and unsanctioned, you can’t govern what you can’t see. Gartner’s 75% AI-amplified product adoption projection by 2028 means this window for establishing control is narrow.

Building cryptographic agility into their architecture. The 2030 quantum deadline means migration planning starts in 2026, not 2028. The encryption market’s 2.0x growth reflects early movers. Late movers face rip-and-replace costs that compound every quarter they wait.

Investing in people alongside AI tooling. AI-enabled SOCs work when human operators have the skills to oversee them. The ISC2 data is unambiguous: a 4.8 million professional gap growing at 19% year-over-year. Managed security services growth at 11.1% tells you where CISOs are finding capacity.

Gartner’s numbers aren’t projections anymore. They’re procurement trends already hitting finance systems. The $244.2 billion flowing into information security this year will fund agentic AI governance, quantum migration, and SOC transformation, whether your organization participates or not.

Bottom line: CISOs planning for 2027 are watching their competitors buy the tools they’ll be scrambling for in 18 months. The data says move now.

Dec 30

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AI Security market 2025 funding data, top startups, and the ServiceNow factor

ServiceNow dropped $11.6 billion on security acquisitions in 2025 alone. Armis for $7.75 billion. Moveworks for $2.85 billion. Veza for roughly $1 billion. In 2025, just one company, ServiceNow, spent more on acquiring security startups than 175 startups raised in two years. Meanwhile, the entire AI security startup ecosystem raised $8.5 billion across 175 companies over 24 months. That single data point should reshape how security leaders think about vendor consolidation and how AI builders think about their exit paths.

I analyzed Crunchbase data covering every AI security startup that raised Series A, B, or C funding between January 2024 and December 2025. The patterns are striking.

The acceleration is real

Q1 2024: $274 million across 8 deals. Q4 2025: $2.17 billion across 28 deals. That’s 8x growth in quarterly funding over two years.

The full-year numbers tell the story more clearly. 2024 saw $2.16 billion in total funding. 2025 hit $6.34 billion, nearly tripling. Average deal sizes jumped from $34 million to $54 million. This isn’t a gentle upward trend. The market is restructuring in real time.

Where the money flows

Network and Zero Trust infrastructure captured $1.9 billion across 44 companies. Tailscale‘s $161 million Series C reflects what enterprises already know. VPN architectures are dying. Identity-based access is replacing them.

Threat Detection and SOC automation drew $1.2 billion across 28 companies. 7AI‘s $130 million Series A stands out as one of the largest A funding rounds in this category. The bet: AI agents can handle the full security operations lifecycle at a scale human analysts cannot match.

Identity and Access Management pulled $990 million. But here’s what matters: that money went to just 6 companies. Saviynt‘s $700 million Series B dominates the category. When one company captures 71% of a category’s funding at Series B, investors see platform consolidation ahead. ServiceNow’s Veza acquisition, three weeks later, validated that thesis.

Insights into deal sizes

Median tells a different story from average deal sizes. Series A median: $20 million. Series A average: $28 million. The gap widens at later stages. Series C median: $85 million. Series C average: $119 million.

Translation: mega-deals skew the data significantly. Eighteen companies raised $100 million or more. Those 18 deals represent 10% of companies but 40% of total funding. For every Saviynt raising $700 million, dozens of startups are raising $15-25 million Series A rounds.

The AI/LLM security gap

Only 13 companies focus specifically on securing AI systems, LLMs, and agentic applications. Total funding: $414 million. That’s less than 5% of the $8.5 billion total. For context: ServiceNow paid more for Veza alone than the entire AI/LLM security category raised in two years.

The players building in this space:

• Noma Security ($100M, Series B). Unified AI and agent security platform.

• Credo AI ($21M, Series B). AI governance and compliance automation.

• Lakera ($20M, Series A). Real-time GenAI security against LLM vulnerabilities.

• Prompt Security ($18M, Series A). Enterprise generative AI adoption platform.

• GetReal Security ($17.5M, Series A). Deepfake and AI-generated impersonation defense.

• Jericho Security ($15M, Series A). Training against generative AI-powered attacks.

Enterprises are deploying AI systems at unprecedented rates. Shadow AI breaches cost $4.63 million per incident. That’s $670,000 more than standard breaches, according to IBM’s 2025 Cost of a Data Breach Report. Model Context Protocol vulnerabilities. Prompt injection attacks. Data exfiltration through AI assistants. The attack surface expands while protection lags.

Either these 13 companies scale rapidly, established players acquire their way into the space, or CISOs face a protection gap without commercial solutions.

How spending breaks out geographically

The U.S. captured $6.1 billion across 119 companies. That’s 71% of total funding. Israel remains the second hub: 15 companies, $738 million. Germany, the UK, and Canada trail with single-digit percentages.

Within the U.S., California dominates: $2.7 billion across 62 companies. That’s more than all non-U.S. markets combined ($2.4 billion). Texas ($865M), New York ($667M), and Colorado ($295M) round out the top states.

The concentration creates vendor risk. Regulatory fragmentation between the U.S. and EU markets. Geopolitical tensions affecting Israeli companies. Single-region dependency in security infrastructure. These are fundamental considerations for enterprise security architects.

ServiceNow’s acquisitions signal large-scale consolidation

ServiceNow’s 2025 acquisition spree warrants its own analysis. Armis brings cyber-physical security and OT/IoT visibility. Moveworks adds agentic AI capabilities. Veza delivers identity security for the AI era. The company calls it an “AI control tower.” A unified security stack that sees, decides, and acts across the entire technology footprint.

The driver: ServiceNow’s Security and Risk business crossed $1 billion in annual contract value in Q3 2025. They expect Armis alone to triple their market opportunity. When a platform vendor invests $11.6 billion in its own security workflows, point solutions become acquisition targets or competitors.

What this means for 2026

For security leaders: Map your vendor portfolio against both funding momentum and M&A activity. Startups with strong backing will survive consolidation. Others won’t. Audit your AI deployment pipeline against available protections. The gap between AI adoption and AI security is widening. Accelerate zero-trust adoption while solutions mature.

For AI builders: Security isn’t a feature to add later. The $414 million flowing into AI/LLM security represents smart money recognizing that unprotected AI systems are enterprise liabilities. Build with guardrails or build vulnerabilities.

Analysis based on Crunchbase data covering 175 AI security startups that raised Series A, B, or C funding between January 2024 and December 2025. ServiceNow acquisition data from the company’s press releases dated December 2025.

Nov 26

15 fastest-growing security categories in Gartner’s 3Q25 Information Security Forecast

Cloud Security Posture Management is growing at a 31.23% CAGR. Zero Trust Network Access at 23.25%. Threat Intelligence at 22.17%. The overall security market? Just 10.55%. Fifteen categories are outpacing the market by two to three times, collectively capturing $106 billion in new spending by 2029. Enterprise security budgets aren’t just expanding. They’re being redirected.

And the driver? Brutally simple.

Gartner estimates 99% of cloud security failures through 2025 will be the customer’s fault, primarily due to misconfigurations. Organizations are responding by investing aggressively in technologies that automate what humans simply can’t manage manually across hundreds of cloud accounts, thousands of APIs, and millions of potential attack vectors.

What these growth rates say about Gartner’s view of the market

These fifteen categories represent $106.4 billion in new spending by 2029, growing from today’s baseline. What do they have in common? Three characteristics that explain why enterprises are pouring money into them:

Automation at Scale. Every high-growth category automates processes that break when done manually, whether it’s scanning cloud configurations, managing consent across jurisdictions, or detecting behavioral anomalies in network traffic. There’s no other way to keep pace.
Proactive vs. Reactive. These technologies prevent problems rather than clean up after them. CSPM catches misconfigurations before breaches. ZTNA eliminates the attack surface that VPNs create. Tokenization protects data even if systems are compromised. Security teams are finally getting ahead of the threat curve instead of playing catch-up.
Measurable ROI. IBM’s 2025 Cost of a Data Breach Report shows organizations using AI and automation extensively save $1.9 million per breach and reduce breach lifecycle by 80 days. With U.S. breach costs hitting $10.22 million, these investments pay for themselves with a single prevented incident.

The 15 categories reshaping security architecture

1. Cloud Security Posture Management (CSPM) | 31.23% CAGR | $2.5B → $13.0B

CSPM tools continuously scan infrastructure across AWS, Azure, and Google Cloud. With 82% of misconfigurations caused by human error and organizations managing 100+ cloud accounts, CSPM automates what’s mathematically impossible to do manually. The market will reach $15.6 billion by 2032.

2. Cloud Access Security Brokers (CASB) | 25.82% CAGR | $1.5B → $5.8B

Here’s a reality check. Enterprises average 112 SaaS applications, but shadow IT, or unauthorized apps, accounts for 42% of all applications. IT remains unaware of one-third of the apps on its networks. The damage? 65% of shadow IT companies suffer data loss, and 52% experience breaches. CASBs transform this chaos into visibility and control.

3. Zero Trust Network Access (ZTNA) | 23.25% CAGR | $1.6B → $5.6B

ZTNA kills the VPN model. Instead of network access, it provides application-specific connections verified for every request. Gartner predicts 70% of new remote access deployments will use ZTNA by 2025. With 65% of companies planning to replace VPNs, this shift represents a wholesale rethinking of secure access. The perimeter-based model is dying. Good riddance.

4. Cloud Workload Protection Platforms (CWPP) | 22.78% CAGR | $3.9B → $13.5B

CWPP platforms secure everything from traditional VMs to containers that exist for milliseconds. Legacy endpoint security can’t protect ephemeral containers or serverless functions—it wasn’t designed for workloads that appear and disappear in seconds. The shift to microservices demands purpose-built security.

5. Consent and Preference Management | 22.39% CAGR | $0.5B → $1.7B

GDPR fines reached €5.88 billion by January 2025, according to the DLA Piper GDPR Fines and Data Breach Survey. California’s CCPA penalties continue climbing; the California Privacy Protection Agency fined Todd Snyder $345,178 for inadequate opt-out and privacy request processes. Manual handling can’t meet regulatory deadlines. Automation prevents massive fines.

6. Threat Intelligence | 22.17% CAGR | $1.8B → $5.8B

IBM data shows threat intelligence reduces detection and escalation costs by $1.63 million while cutting incidents by 30%. Modern platforms aggregate data about bad actors and vulnerabilities, transforming raw threat data into automated responses across security stacks. The days of threat feeds sitting in dashboards, unused, are over.

7. Subject Rights Request Automation | 16.53% CAGR | $0.8B → $2.1B

When users demand “delete my data,” these platforms automate the process across all systems. Manual handling doesn’t scale, not when you’re managing requests across multiple jurisdictions with different requirements and tight deadlines.

8. Tokenization | 14.26% CAGR | $1.0B → $2.2B

Tokenization replaces sensitive data with meaningless tokens that can’t be mathematically reversed. Why the urgency now? NIST standardized quantum-resistant algorithms, including ML-KEM (formerly CRYSTALS-Kyber), in August 2024. Organizations are preparing for quantum threats expected within five to ten years.

9. Network Detection and Response (NDR) | 14.05% CAGR | $1.6B → $3.5B

NDR platforms use AI to establish behavioral baselines and detect anomalies signaling compromise. Here’s the mindset shift: rather than hoping to prevent all attacks, innovative organizations invest in rapid detection that minimizes damage when sophisticated attackers inevitably get through. Prevention isn’t enough anymore.

10. Vulnerability Assessment | 13.98% CAGR | $2.6B → $5.7B

Cloud infrastructure changes constantly. Quarterly scans are obsolete before they finish. Modern platforms provide continuous scanning in CI/CD pipelines, prioritizing based on real-world exploit data. DevOps teams deploying daily need vulnerability detection that keeps pace. Anything less is theater.

11. Endpoint Protection Platform (EPP) | 13.61% CAGR | $13.5B → $29.1B

The largest category doubles to $29.1 billion as ransomware attacks surge. According to Cyble analysis cited by TechTarget, U.S. ransomware attacks increased by 149% year-over-year in the first five weeks of 2025. Manufacturing led targets with 638 attacks in 2023, per Statista data compiled by Fortinet. Next-gen EPP uses behavioral analytics to stop ransomware before encryption begins—catching what traditional antivirus misses.

12. Secure Web Gateway (SWG) | 13.26% CAGR | $3.3B → $7.0B

Malicious sites appear and disappear in hours. Cloud-delivered SWGs update threat intelligence in real-time, protecting remote workers wherever they connect. Integration with ZTNA creates comprehensive security that follows users across devices and locations. The old perimeter? It no longer exists.

13. Web Application Firewalls (WAF) | 11.93% CAGR | $2.0B → $3.8B

Organizations expose hundreds of APIs, each a potential attack vector. Traditional network firewalls can’t inspect application-layer attacks. Modern WAFs use machine learning to distinguish legitimate users from attackers without blocking customers. Getting that balance right is harder than it sounds.

14. Encryption | 11.90% CAGR | $1.0B → $2.0B

NIST’s standardization of quantum-resistant algorithms signals urgency. Attackers already practice “harvest now, decrypt later”—collecting encrypted data for future quantum decryption. Organizations must transition to post-quantum cryptography now, as full integration takes years. This isn’t theoretical risk anymore.

15. Security Information and Event Management (SIEM) | 11.74% CAGR | $5.8B → $11.3B

AI transforms SIEM from reactive to proactive. Organizations using AI-powered automation save $1.9 million per breach, according to IBM’s newsroom. Machine learning models identify attack patterns and detect zero-day threats before signatures exist, turning security operations into a competitive advantage.

The Investment Thesis behind the numbers

These growth rates reflect three converging realities:

Cloud Complexity Is Exponential. With 79% of organizations using multiple cloud providers and managing hundreds of accounts, manual security is mathematically impossible. The 31.23% CAGR for CSPM isn’t optimism, it’s survival.
AI Changes Everything. Shadow AI breaches cost $4.63 million, $670,000 more than standard incidents. But AI also powers the defense, with automated security tools reducing breach lifecycles by 80 days. The same technology that creates vulnerabilities offers the best defense.
Compliance Costs Are Skyrocketing. Between GDPR, CCPA, and emerging regulations, manual compliance is a liability that grows daily. Automation platforms turn regulatory requirements into competitive advantages.

The Bottom Line

The organizations winning this race aren’t those with the most significant security budgets; they’re those investing in the right categories at the right time. These fifteen segments aren’t just growing fast; they’re defining what modern security architecture looks like.

The message from Gartner’s data is unambiguous: security spending is shifting from reactive to proactive, from manual to automated, from perimeter-based to zero-trust. Organizations still relying on legacy approaches aren’t just falling behind; they’re accepting risks that the market has already priced as unacceptable.

Source: Gartner Information Security Forecast 3Q25 Update (Document G00839334), showing overall market growth from $215.8B (2025) to $322.2B (2029) at 10.55% CAGR

Nov 10

Top 10 Identity Security Insights from Forrester’s 2025 Security & Risk Summit

Bottom line: Identity security stands at an unprecedented crossroads, with machine identities creating greater complexity and potential chaos every security professional needs to plan for.

At Forrester’s 2025 Security & Risk Summit, Merritt Maxim, VP and Research Director at Forrester, delivered critical insights highlighting the escalating threats shaping identity security’s evolution. CISOs and security leaders find themselves navigating surging threats driven by generative AI, the rapid proliferation of non-human identities, and outdated IAM infrastructures originally designed solely for compliance. Maxim emphasized a pressing urgency: identity strategies must adapt or risk catastrophic breaches and compliance failures.

Here’s a detailed breakdown of the top 10 insights from Forrester’s Summit, including the specific slides from Maxim’s presentation and deeper insights from Forrester’s latest data:

1. Identity Security Budgets Accelerate Toward $27.5B by 2029

IAM investment is growing explosively, set to nearly double from $13.4 billion in 2024 to $27.5 billion by 2029, driven by the escalating complexity and severity of identity-related threats such as AI-driven deepfakes, sophisticated supply-chain attacks, and rampant cloud misconfigurations. This positions IAM as cybersecurity’s third fastest-growing segment, underscoring identity security as a business-critical imperative.

2. Hybrid IAM Still Dominates—77% Keep On-Premise Components

Despite the relentless push to the cloud, 77% of organizations continue relying on hybrid IAM deployments due to legacy infrastructure and regulatory constraints. Fully cloud-based identity management remains a distant reality, with only 9% fully transitioned. Maxim stressed hybrid IAM’s persistence, highlighting the necessity for seamless integration capabilities between on-premises systems and cloud IAM platforms.

3. Third-party Risk Matches Compliance as a Top IAM Driver

Forrester revealed a pivotal shift: managing third-party identities (32%) is now equally critical as regulatory compliance (32%) in driving IAM investments. High-profile breaches at Okta and CyberArk underscore vulnerabilities introduced by third-party identities, necessitating robust governance models that go beyond basic compliance checklists.

4. Static Entitlements Are Obsolete; Zero Standing Privilege Is Now Mandatory

The static entitlement model—assigning privileges during onboarding—is officially outdated. Forrester highlighted Zero Standing Privilege (ZSP) architectures as the definitive new standard, utilizing the Continuous Access Evaluation Protocol (CAEP) to dynamically assign permissions at runtime. This strategy mitigates rampant privilege sprawl, dramatically reducing attack surfaces.

5. Identity Management Converges Across Security, Marketing, and CX

Enterprises are rapidly integrating fragmented identity management systems across marketing, customer experience (CX), fraud prevention, and security. Maxim emphasized that businesses consolidating these functions significantly improve detection speed, minimize breaches, and enhance end-user experience. Leveraging customer preference and security data together is becoming a strategic advantage.

6. Vendor Consolidation Radically Reshapes IAM Markets

IAM vendor consolidation accelerated significantly, highlighted by major moves such as Palo Alto Networks acquiring CyberArk, Ping Identity merging with ForgeRock, and CrowdStrike purchasing Adaptive Shield. Enterprises increasingly demand integrated identity platforms combining PAM, IGA, and Identity Threat Detection & Response (ITDR), driving these high-profile acquisitions.

7. Generative AI Exacerbates Identity Threats but Offers Transformational Defenses

Generative AI escalates identity threats dramatically through enhanced phishing and sophisticated deepfake impersonations. Conversely, GenAI’s defensive capabilities are equally transformative, enabling automated identity threat detection, rapid response, and real-time entitlement adjustments. Maxim described these dual dynamics as essential to future IAM strategies.

8. Machine Identities Are a Critical Emerging Attack Vector

The explosive growth in non-human identities (IoT, APIs, AI agents) vastly expands attack surfaces. Enterprises urgently need automated platforms from vendors like CyberArk, Venafi, and HashiCorp to manage this surge. Forrester highlighted machine identities as a rapidly intensifying risk requiring immediate attention and robust governance.

9. Phishing-Resistant MFA Is Dangerously Under-Deployed

Alarmingly, only 21% of companies deploy phishing-resistant MFA after breaches, despite the increasing sophistication of MFA-bypass attacks. Forrester insists enterprises must urgently adopt solutions like FIDO2 and WebAuthn. Maxim warned that neglecting these standards leaves companies dangerously exposed to credential-based compromises.

10. Context-Aware IAM Becomes a Real-time Security Necessity

Static IAM fails against machine-speed threats. Context-aware IAM, powered by dynamic authorization, continuously assesses real-time user behavior, device posture, and threat intel. Forrester identifies this adaptive approach as critical, turning identity from a passive gatekeeper to a proactive defender, which is essential for stopping attacks before damage occurs

Bottom Line: Adaptive identity security defines enterprise survival

Identity security has become synonymous with enterprise survival. Merritt Maxim’s compelling insights from Forrester’s 2025 Security & Risk Summit underscore a new identity imperative: convergence, consolidation, and context must drive strategic identity transformations. Following Forrester’s lead, enterprises must prioritize investment in dynamic Zero Standing Privilege architectures, integrated identity platforms, generative AI-enabled threat response, robust machine identity management, and phishing-resistant MFA immediately. The future of enterprise resilience hinges directly on evolving identity security today.

Nov 3

Top 10 insights from Forrester’s 2026 Cybersecurity Budget Report

“With volatility now the norm, security and risk leaders need practical guidance on managing existing spending and new budgetary necessities,” states Forrester’s 2026 Budget Planning Guide.

The research firm’s planning guide for next year provides security leaders with new insights into how their clients are allocating budgets, which gives a helpful overview of the next 12 months of cybersecurity spending.

Implicit in the guide is the need for new technologies that enable organizations to be more adaptive to threats and take action on them before they become breaches. There’s also a strong focus on getting a head start on new technologies, anticipating the severity of threats new developments in AI, generative AI (genAI), deepfakes, and all other forms of weaponized technologies can pose to an organization.

Software is a solid 40% of cybersecurity spending, exceeding hardware at 15.8%, outsourcing at 15% and surpassing personnel costs at 29% by 11 percentage points. Meanwhile, security leaders face escalating threats, with generative AI attacks executing in milliseconds, a stark contrast to the average Mean Time to Identify (MTTI) of 181 days, according to IBM’s latest Cost of a Data Breach Report.

A fast-changing threatscape is changing spending priorities

Three converging threats are flipping cybersecurity on its head. What once protected organizations is now working against them. Generative AI (gen AI) is enabling attackers to craft 10,000 personalized phishing emails per minute using scraped LinkedIn profiles and corporate communications. NIST’s 2030 quantum deadline threatens retroactive decryption of $425 billion in currently protected data. Deepfake fraud that surged 3,000% in 2024 now bypasses biometric authentication in 97% of attempts, forcing security leaders to reimagine defensive architectures fundamentally.

Top ten insights from Forrester’s 2026 cybersecurity budget benchmarks

1. Software now claims 40% of cybersecurity budgets, surpassing personnel spend. Forrester’s budget planning guide reports that software now accounts for approximately 40.2% of cybersecurity spending, eclipsing combined hardware and outsourcing budgets. It’s noteworthy that software spending is surpassing personnel costs by 11 percentage points.

Top 10 insights from Forrester’s 2026 Cybersecurity Budget Report — Source: Forrester Budget Planning Guide 2026: Security and Risk

2. Security budgets are accelerating, with 55% of global security and tech leaders forecasting significant increases next year. A robust 15% anticipate their budgets jumping more than 10%, and another 40% project hikes between 5% and 10%. Regional outlooks vary sharply: APAC is most bullish, with 22% expecting double-digit growth, compared to a cautious 9% in North America and just 12% in EMEA. However, nearly half (45%) remain reserved; 30% predict minimal budget bumps of 1%–4% or barely keeping pace with inflation, while another 10% expectSource: Forrester Budget Planning Guide 2026: Security and Risk no change, and 5% foresee cuts.

3. Cloud security, on-prem tech, and security awareness training are set to lead cybersecurity spending in 2026. Decision-makers are doubling down on cloud security, with 12% boosting budgets in this area by 10% or more, 11% doing the same for new on-premises solutions, and another 10% ramping up security awareness programs. Notably, investments in on-premises security technology appear twice among the top priorities, as 36% plan at least a 5% increase for both new deployments and upgrades to existing infrastructure. The numbers reflect an uneven global adoption of cloud strategies, driven by persistent concerns around cost, security, and data sovereignty. APAC is exceptionally bullish. 78% of companies there plan increased spending on new on-prem security, outpacing EMEA by 10% and North America by 8%.

4. Forrester recommends that security leaders broaden AI and ML security throughout the enterprise in 2026 as generative AI moves from standalone apps to essential business systems. Productivity suites, CRM platforms, and service tools now embed genAI natively, transforming workflows and widening potential attack surfaces. Enterprises urgently need comprehensive protection across AI models, data, applications, and user identities to counter risks such as model vulnerabilities, data leakage, and prompt jailbreaking. Hyperscalers like Google Cloud and Microsoft are responding quickly, while cybersecurity incumbents, notably Palo Alto Networks with its Protect AI acquisition, actively expand their footprint. Meanwhile, innovative startups, including Knostic and CalypsoAI, both featured at RSA’s Innovation Sandbox, target niche but critical genAI security gaps. Enterprises investing strategically now will securely scale genAI deployments and establish a clear competitive advantage.

5. Standalone SSE spending will sharply decline in 2026 as enterprises shift to unified SASE platforms, streamlining security operations and accelerating Zero Trust initiatives. Initially positioned to fill security gaps left by SD-WAN deployments and the surge in remote work, standalone SSE and isolated ZTNA solutions have now reached their functional limits. Leading companies increasingly adopt integrated platforms like Cato Networks’ cloud-native SASE, which consolidates SD-WAN, ZTNA, SWG, CASB, and firewall capabilities within a single, unified framework. As I’ve noted in VentureBeat, CISOs who pivot to unified SASE platforms benefit from simpler integration, superior AI-driven threat detection, and significant operational efficiencies that isolated solutions cannot deliver. Organizations proactively embracing integrated SASE from providers like Cato Networks will immediately enhance security resilience, improve operational agility, and significantly reduce vendor complexity.

6. Forrester predicts that by 2026, security leaders will seize a critical advantage by accelerating the adoption of post-quantum cryptography (PQC). With NIST’s landmark release of three core PQC standards in August 2024, organizations now have clear guidance to protect their data and applications against emerging quantum threats. Most governments align with NIST timelines, targeting legacy encryption deprecation by 2030, while Australia’s ASD urges adoption of approved PQC algorithms even sooner. Enterprises should immediately focus efforts on securing their most sensitive asymmetric cryptography, covering data at rest, data in transit, and data actively used within applications. Comprehensive cryptographic discovery and inventory tools provide the visibility required to assess readiness. Strategic partnerships with cryptoagility innovators, including Entrust, IBM, Keyfactor, Palo Alto Networks, QuSecure, SandboxAQ, and Thales, enable organizations to define a clear, secure migration path. Organizations acting decisively now will confidently navigate the quantum transition and fortify their competitive edge.

7. Machine identity management will become essential by 2026 as automated identities multiply rapidly across the IT infrastructure. Apps, AI agents, IoT devices, containers, cloud environments, and infrastructure scripts now generate identities faster than humans can manually track or manage. Enterprises urgently require solutions capable of managing these identities throughout their lifecycle, automating key rotations, and enforcing role-based access. Leading vendors, including Akeyless, BeyondTrust, CyberArk, Delinea, HashiCorp, Keyfactor, AppViewX, and emerging startups like Aembit, Astrix, Clutch, Entro, and Oasis Security, offer robust platforms to meet this challenge.

8. There will be a significant reallocation away from standalone interactive application security testing (IAST) in 2026, as operational hurdles continue to limit adoption. Originally designed to blend the runtime accuracy of dynamic application security testing (DAST) with static application security testing’s (SAST) code-level insights, standalone IAST has proven overly complex. Forrester recommends shifting budgets toward integrated IAST and DAST platforms, such as those from Invicti and HCLSoftware, that simplify deployment. Alternatively, APIs, microservices, and containers provide more transparent and consistent returns.

9. Consolidation of endpoint security and SIEM tools will accelerate in 2026. As extended detection and response (XDR) platforms gain momentum, security leaders have a clear opportunity to reduce agent sprawl, improve analyst efficiency, and lower the total cost of ownership. Vendors, including Microsoft, CrowdStrike, and Palo Alto Networks, now embed critical SIEM functions such as detection, correlation, third-party data ingestion (particularly from cloud, identity, and email), and response directly within their XDR offerings. While these integrated solutions currently don’t fully match standalone security analytics platforms, they deliver compelling advantages: simplified deployments, centralized threat context, and measurable operational savings. Organizations consolidating around unified XDR solutions today will streamline security operations and achieve faster, higher-quality threat detection.

10. By 2026, rapidly evolving generative AI will make deepfakes virtually indistinguishable from authentic media, rendering simplistic identity checks obsolete. Enterprises must proactively deploy sophisticated detection platforms using advanced ensemble modeling—spectral analysis, image artifacts, skin tone consistency, lighting anomalies, audio echo patterns, and device reputation, to ensure trusted employee verification and transaction authentication. Vendors such as GetReal Security, Sensity, and Reality Defender already offer real-time risk scoring, transparent reasoning, and integrated case management. Early adopters will safeguard identity security, sustain customer trust, and remain resilient against future deepfake threats.

Oct 29

Gartner: 60% of CISOs are piloting GenAI, but only 20% see results

Made with Imagen

The global threatscape is becoming dominated by all forms of weaponized LLMs, AI, and conversational agents, all aimed at launching lethal attacks that cripple companies and entire supply chains in minutes.

Nation‑state actors and organized eCrime groups now use artificial intelligence, including generative AI (GenAI), to automate reconnaissance, weaponize access, and strike faster than most defenses can respond. To keep pace, enterprises and the CISOs leading them are turning to GenAI as a defensive multiplier.

CISOs are remaining optimistic

Gartner’s latest research quantifies that adoption is accelerating, but measurable results remain elusive. Approximately 60 % of organizations are piloting or planning GenAI cybersecurity initiatives. Only 20% of security leaders say these programs have delivered beneficial outcomes so far. These figures are from the research firm’s recent research note, What GenAI Use Cases Are Organizations Pursuing Within Cybersecurity? published earlier this month. Forrester predicts that the first agentic AI breach will happen in 2026.

Yet, despite early hurdles, cybersecurity leaders remain optimistic. Nearly every CISO I’ve spoken with sees GenAI as pivotal for transforming threat detection, proactive hunting, rapid incident response, and extracting actionable insights from terabytes of telemetry data streaming from endpoints and events. They recognize GenAI as crucial to decoding adversary tradecraft, particularly as identity-based threats and weaponized machine-learning attacks accelerate, reshaping the global threatscape in real time.

Key takeaways

Code Analysis leads the pack. GenAI‑assisted code analysis is the most mature use case: 22% of enterprises use it today, and another 30% are piloting it. It addresses a persistent gap, as 69% of software‑engineering leaders cite insecure code remediation as a critical skills bottleneck.
GenAI shows potential in helping SOC teams spot vulnerabilities faster. Currently, 21% of organizations actively leverage GenAI to enhance vulnerability detection and remediation, with another 26% piloting these capabilities. Adoption is driven by GenAI’s ability to automate vulnerability identification and prioritize remediation workflows, addressing longstanding security bottlenecks and resource constraints. Despite intense interest, widespread implementation remains challenged by integration complexity and skepticism about AI-generated accuracy, emphasizing the need for incremental deployment aligned with existing cybersecurity metrics.
CISOs Shift from Ambition to Execution Gartner finds that the leaders gaining traction are those adopting “bite‑sized” implementations or use cases that fit into current processes, deliver quantifiable ROI, and build trust among analysts and engineers.

CISOs are dealing with a threatscape moving at machine speed

Given how lethal machine-driven attacks are becoming, exacerbated by the growing sophistication of weaponized AI, going on the offensive with GenAI is a choice more CISOs are considering.

Nearly every cybersecurity team wants to have a Gen AI pilot either complete or in process to see how it integrates with their planned arsenal for 2026. Most CISOs want some form of AI in their arsenals going into the new year, as many expect the intensity, ingenuity, and lethal impact of automated attacks will reach new levels next year. One told me confidentially she fully expects machine-on-machine breach attempts to grow six times over in 2026 as her financial services firm handles highly speculative assets, including cryptocurrency ETFs and investment products.
Breakout speed hits critical mass. CrowdStrike’s 2025 Global Threat Report reveals the alarming acceleration of attacks: the fastest observed eCrime intrusion took just 51 seconds to escalate from initial access to lateral movement, virtually eliminating defenders’ window to respond.
Living-off-the-Land tactics dominate and often evade legacy cyberdefense systems: Malware-free intrusions surged significantly, now comprising 81% of interactive attacks in 2025. This trend is corroborated by findings from Mandiant and IBM X-Force, indicating adversaries are bypassing traditional signature-based controls by exploiting legitimate tools native to the enterprise environment.
Nation-state activity reaching new record levels as weaponized tradecraft gains stealth and sophistication: CrowdStrike, Mandiant have documented triple-digit increases in operations linked to China, Iran, and North Korea. These attacks predominantly target telecommunications and critical infrastructure, reflecting geopolitical tensions and nation-states’ strategic prioritization of cyber-espionage.
Global threat consensus is clear and compelling: ENISA’s Threat Landscape 2025 report aligns precisely with intelligence from CrowdStrike, Mandiant, and IBM X-Force, verifying that nation-state actors now leverage AI-driven automation to execute attacks faster than enterprises can detect, let alone defend.

CrowdStrike Founder and CEO George Kurtz underscored the urgency clearly in a recent CNBC interview on October 23rd, stating, “Well, this is something that we’ve really been focused on for the last number of years is being able to protect agentic AI. And if you think about agentic AI, it has the capabilities to interact with data. It has the capabilities to interact with Compute. It has identities, non-human identities, but it operates at superhuman speed. So all of the challenges that we’ve seen over the many years of humans getting themselves into trouble is only going to be exasperated by agentic AI, and we need security like CrowdStrike is delivering to protect it”.

Practical guidance from CISOs adding GenAI to their arsenals

Gartner’s latest research, combined with interviews and discussions with CISOs, security leaders, and SOC leaders who are piloting and in some cases using GenAI-based platforms today, offers this advice:

Go deep on integration on pilots to see how strong the GenAI solution is as a contributor to your security tech stack: CISOs and SOC leaders tell me that this is the most reliable test of whether a GenAI platform or app will make the cut and get to production on their tech stack. Solid APIs that have been battle-tested by vendors who have a strong API management history have the inside track.
Outcome-driven use cases are a must-have:At its core, cybersecurity is a business decision. And in a digital-first world, protecting your brand is essential. Any Gen AI pilot needs to contribute to a use case that makes a solid contribution to solidifying a business’s ability to compete.
Start with time-tested, established metrics: Getting to a level of trust in GenAI is core to seeing if it is ready to progress from pilot into production. Evaluating GenAI effectiveness using established KPIs, including mean time to detect (MTTD) and mean time to respond (MTTR), at table stakes. CISOs and others running pilots caution about creating entirely new metrics just for GenAI. It obfuscates the total business impact of the technology.
Parallel human trust and governance: Gartner emphasizes investing in employee enablement and robust governance frameworks like NIST’s AI Risk Management Framework to foster confidence in GenAI adoption. Human oversight remains a vital layer of control. Human-in-the-middle is essential for any workflow.

Bottom Line

Nation-state adversaries measure their innovation in how lethal their attacks are, how stealth their tradecraft is, and how easily they can evade legacy security techniques. It’s a full cyberwar just a few steps away from a full-on kinetic war. Research from CrowdStrike, IBM, Mandiant, and many other companies shows machine-to-machine attacks orchestrated with Gen AI are accelerating, so much so that Forrester predicts an imminent AI breach next year. GenAI’s ability to identify new threats and stop them makes the technology work a look.

Aug 25

Top Ten Insights from Forrester’s 2024 Cybersecurity Budget Benchmarks

CISOs are being asked to do a lot more with less as their businesses are going all-in on new digital businesses that demand identity-based security while keeping budgets tight for securing infrastructure against attacks.

Cybersecurity budgets are, on average, just 5.7% of IT annual spending. That’s tight for many security teams. CISOs are rising to the challenge, however, and delivering revenue gains by protecting new digital businesses while keeping infrastructure safe. Achieving that is a quick way for CISOs to advance their careers.

Cybersecurity needs funding to match its business growth potential

The good news is that more CEOs and boards see cybersecurity as a business enabler. The challenge for CISOs, however, is that cybersecurity still gets funded purely for its defensive value – not its upside potential to drive growth.

Many security teams struggle to make ends meet in their budgets while still staying responsive to internal teams’ needs. Forrester’s 2024 Cybersecurity Benchmarks Global Report shows just how tight budgets can get for a CISO and their team. Project-related work and incident management are a constant balancing act for security teams, and keeping them both in check is key to staying under budget.

Top Ten Insights

Cybersecurity budgets are on the low side compared to the growing complexity of threats and risks organizations face.

That’s forcing CISOs to be selective about what they spend on and how they allocate limited resources. Add to that the average spend of $1,070 per enterprise user and $157,000 per cybersecurity employee, and cybersecurity teams have little, if any, room for inefficiencies.

The following are the top ten insights from Forrester’s latest cybersecurity benchmark report:

CISOs need to move out of the IT organization and report to their CEOs and board of directors to have a chance at a more realistic budget. Forrester finds that cybersecurity budgets increase when CISOs report directly to the CEO or board of directors. CISOs who can articulate the business value of cybersecurity, demonstrating how it can drive revenue and support strategic goals, are more likely to secure the necessary funding. This shift also reflects a growing recognition of cybersecurity’s strategic importance beyond mere IT operations.
Software will dominate cybersecurity budgets in 2024. The report reveals that 35.9% of cybersecurity budgets globally are allocated to software. This trend is particularly pronounced in large enterprises with up to 74,999 employees, where 39.4% of the budget is dedicated to software. Smaller organizations, conversely, spend a higher percentage on outsourcing services due to limited in-house capabilities, which underscores the scalability challenges smaller firms face in maintaining robust cybersecurity defenses.

Top Ten Insights from Forrester's 2024 Cybersecurity Budget Benchmarks

Source: Forrester 2024 Cybersecurity Benchmarks Global Report

Cybersecurity spending per user keeps climbing, reaching $1,070. This is another budget constraint CISOs have to factor into their total operations plans for a given year. Forrester notes that “the cybersecurity spend per enterprise user ranges from an average of $947 at extra-large organizations (75,000 or more users) to $1,210 at small organizations (fewer than 10,000 users).
Personnel costs consume 28% of the typical security budget. The report highlights that organizations are spending an average of $157,593 per cybersecurity employee. Full-time employees make up 73.5% of security teams, with the global average cost per contracted full-time equivalent (FTE) reaching $194,613. This significant expenditure on personnel underscores the critical role of skilled professionals in maintaining effective cybersecurity defenses.

System Defense is the leading functional spend category in 2024. Forrester finds that 29% of functional spending is in System Defense alone. The funding levels approved for this category reflect the critical need to protect endpoints and mobile devices against increasingly sophisticated attacks. With adversaries innovating faster than enterprises can keep up, System Defense is a must-have to protect new digital businesses and infrastructure. The following graphic shows cybersecurity spending by functional domain.

Identity and Access Management (IAM) takes up 21% of functional spending in the typical budget. Identity-driven attacks take many forms, from mass phishing to whale phishing, where senior executives of a company are targeted with tailored campaigns IAM also enhances operational efficiency and fraud reduction, making it a strategic investment for many organizations. Its broad applicability across both internal and customer-facing applications drives its substantial share of the cybersecurity budget.
Security analytics and incident handling reach 13% and 14%, respectively. Forrester notes that each of these separate services accounts for a relatively low percentage of the overall cybersecurity budget. Still, most organizations combine spending on these two categories into “detection and response.” Both areas combined equal 26% of the overall security budget, on average.
Getting compliance and governance right is a growing concern for many CISOs who are willing to spend their budget to stay in good standing with the SEC. The Security and Exchange Commission’s Cybersecurity Risk Management, Strategy, Governance, and Incident Disclosure adopted on July 26, 2023. The rules adopted by the SEC define a standardized process for cybersecurity disclosures for public companies. These rules require companies to disclose material cybersecurity incidents on Form 8-K or Form 6-K within four business days of determining the incident’s materiality. Additionally, companies must include cybersecurity risk management, strategy, and governance information in their annual reports (Forms 10-K and 20-F). The rules also mandate the use of Inline XBRL for tagging these disclosures.
Incident handling is on average, 13.5% of a global cybersecurity budget. This category is the most unpredictable, as it deals with responding to intrusions and breaches that cannot be forecasted. Spending on incident handling varies by company size, with small organizations (fewer than 10,000 employees) aligning with the global average of 13.5%. Larger organizations tend to allocate slightly less, likely due to more extensive preventative measures and diversified cybersecurity resources.
Privacy is core to customer trust today and gets funded, even in tough budgeting cycles. The two departments that use privacy-related solutions the most frequently are legal and marketing, which dedicate on average 12% of a cybersecurity budget to them. Forrester notes that this 12% figure is not the total privacy spend of an organization. Rather, the report says, “Data privacy spans multiple areas of the organization, including marketing and legal. Its share of the security budget doesn’t represent the total spending on privacy-related initiatives across the entire technology estate.

Balancing the scales of cybersecurity budgeting

The bottom line is that cybersecurity is a business decision and needs to be funded with that mindset. Organizations need to see the CISO role as a more board-level one so they can share their technology expertise in helping to manage risk.

It’s time for cybersecurity to be funded as a growth engine, not just one used for deterrence alone.

CISOs can balance the scales by looking for an opportunity to elevate their role to a CEO direct report and, ideally, be on the board to help guide their companies through an increasingly complex threat landscape.

Jul 7

Forrester’s top ten trends defining identity and access management in 2024

Stolen identity and privileged access credentials now account for 61% of all data breaches. This figure continues to increase as nation-state attackers, cybercrime groups, and rogue attackers integrate AI into their attack tradecraft.

Adversarial AI is taking aim at identities

80% or more of breach attempts aim first at identities and the systems that manage them. CrowdStrike’s 2024 Global Threat Report found that identity-based and social engineering attacks are reaching a new level of intensity. CrowdStrike found that attackers are using AI to launch advanced phishing attacks to impersonate legitimate users and infiltrate secure accounts. Attackers have long sought account credentials, but in 2023, their goals centered on authentication tools and systems, including API keys and OTPs.

“What we’re seeing is that the threat actors have really been focused on identity, taking a legitimate identity. logging in as a legitimate user. And then laying low, staying under the radar by living off the land by using legitimate tools,” Adam Meyers, senior vice president counter adversary operations at CrowdStrike, told VentureBeat in an interview early this year. Two of the most infamous Russian nation-state attackers, Fancy Bear and Cozy Bear, led these efforts, with the former exploiting a Microsoft Outlook vulnerability (CVE-2023-23397) for unauthorized server access.

Top ten trends defining identity and access management (IAM) in 2024

Forrester’s recent report, The Top Trends Shaping Identity And Access Management In 2024, provides an insightful view into the future of Identity and Access Management (IAM) and Privileged Identity Management (PIM). The report predicts that threat detection and remediation will improve with the help of A.I. Forrester also predicts that FIDO passkey authentication will go mainstream. In contrast, biometric authentication will slow down due to concerns regarding deepfakes.

Leading IAM providers include AWS Identity and Access Management, CrowdStrike, Delinea, Cradlepoint, ForgeRock, Ivanti, Google Cloud Identity, IBM Cloud Identity, Microsoft Azure Active Directory, Palo Alto Networks, and Zscaler.

Here is a summary of the top ten trends Forrester believes will shape IAM in 2024:

Trend 1: AI Will Improve Identity-Based Threat Detection and Remediation. Generative AI (genAI) is helping to redefine the future of IAM by improving outlier behavior analysis, increasing alerts’ accuracy, and streamlining administrative tasks while guarding against new threats.

98% of security professionals believe AI and machine learning (ML) will be beneficial in fighting identity-based breaches and see it as a pivotal technology in unifying their many identity frameworks. The majority, 63%, predict AI’s leading use case will be greater accuracy in identifying outlier behavior. 56% believe AI will help improve the accuracy of alerts, and 52% believe AI will help streamline administrative tasks.

Forrester asserts that AI will help short-staffed security teams triage alerts and automate time-consuming, mundane aspects of their jobs. Forrester also envisions genAI being used to query, “Which five applications are the riskiest from an identity entitlement perspective?” CrowdStrike announced at RSAC 2024 that Charlotte AI, CrowdStrike’s Generative AI security analyst, can automatically correlate all related contexts into a single incident and generate an LLM-powered incident summary for security analysts.

Trend 2: IAM Platforms Face Increased Scrutiny Of Their Underlying Security. High-profile breaches that began with impersonation leading to identity theft, including MGM and Okta, reflect how social engineering can still bypass IAM safeguards. CISOs are pushing back on their IAM vendors to improve operational processes and security practices and prioritize security for cloud-based SaaS applications and multi-cloud configurations. Forrester writes that their clients running IAM systems expect their vendors to comply with standards like SOC 2, FedRAMP, ISO 27002, and PCI. CISOs and security teams are also asking to vet a vendor’s workforce, including both employees and contractors and understand how the vendor communicates about and addresses security issues.

Forrester’s advice to security and risk management professionals is to “Demand multifactor authentication for all workforce business and admin users, without exception. Prioritize IAM vendors that embrace secure-by-design and secure-by-default principles and value continuous two-way customer engagement to improve their overall cybersecurity posture.”

Trend 3: IAM And Non-IAM Vendors Respond To Identity-Centric Threats. More CISOs and their security teams are taking a zero trust mindset to breaches. They see them as inevitable, and as part of their zero trust frameworks, they’re looking to shut down lateral movement after an intrusion. Forrester observes that “both IAM vendors and non-IAM cybersecurity vendors keep making advances in identity threat detection and response (ITDR). As a result of organic development and acquisitions, ITDR capabilities are being incorporated in platforms from privileged identity management (PIM) vendors like ARCON, BeyondTrust, CyberArk, and Delinea, as well as XDR vendors, such as Cisco, CrowdStrike, Proofpoint, and SentinelOne.”

Trend 4: FIDO Passkey Authentication Goes Mainstream For Workforce And B2C Uses. Forrester notes that a large number of customer-facing sites, including H&R Block, PayPal, and Verizon, are moving to passwordless authentication. At the same time, smaller financial institutions like coinbase.com offer optional fast identity online (FIDO) Authentication and FIDO passkey-based authentication. The research firm expects 30% of B2C websites and apps to offer FIDO passkeys by the end of 2024.

Trend 5: Biometric Adoption Slows Due To Concerns Around Deepfakes. Despite biometric authentication being a security standard on smartphones, CISOs and consumers alike are becoming more concerned about deepfakes. Designing liveness detection and other advanced features for facial and fingerprint recognition systems reduces the threat of spoofing generated by deepfake technology.

As multiple breach attempts have proven, voice biometrics are more susceptible to attack. Forrester notes that in response, the FTC set a Voice Cloning Challenge to “encourage the development of multidisciplinary solutions—from products to procedures—aimed at protecting consumers from artificial intelligence-enabled voice cloning harms, such as fraud and the broader misuse of biometric data and creative content.” Vendors will add additional deepfake detection to their solutions in 2024, resulting in a rebound in biometrics adoption in 2025.

Trend 6: IMG And PIM Vendors Expand Coverage Of Cloud Administrator Identities. Getting multicloud and hybrid cloud security right is getting more challenging and complex to achieve at scale due to configuration complexity. Forrester notes that “zero trust in the cloud starts with understanding the data access entitlements of identities like cloud infrastructure administrators, SaaS administrators, and business users.” Security and risk management professionals need to review cloud administrators’ entitlements that grant access to sensitive data assets and, when necessary, cancel them. Forrester writes, “While tools offer detection and remediation automation, they are no substitute for documented and consistent identity governance processes.”

Trend 7: Government-Issued Digital Identities Continue To Spread. Forrester believes acceptance of government-issued decentralized digital identities (DDIDs) beyond government use cases will grow in 2024. Mobile digital identities, including driver’s licenses, are now available in the US states of Arizona, California, Florida, and Iowa. Jurisdictions that have or will soon issue mobile driver’s licenses include the European Union (based on the eIDAS 2.0 approved set of standards), Estonia, Hungary, and Sweden. Nigeria and the Philippines have digital identities active today. .

Trend 8: B2B IAM Becomes A Differentiating Feature. Security teams and CISOs running them who are operating without an extended IAM ecosystem for partners like contractors, suppliers, and resellers face more severe security risks. B2B IAM involves managing joiner, mover, and leaver (JML) processes differently than internal employees. Forrester predicts that in 2024, IAM vendors will enhance platforms with features like simplified federation onboarding, verifiable credentials for ID verification, and improved access review processes for the extended enterprise.

Trend 9: Commercial and homegrown IAM Solutions Face Growing Demand For Upgrades. Maintaining on-premises IAM systems is becoming more costly and inefficient, making it more attractive to move to a cloud-based platform. Forrester is finding that the brittle, less secure nature of on-premise legacy systems also makes them more difficult to upgrade. Demand is so high for replacing legacy systems that a recent Forrester survey found that the intention to replace homegrown solutions jumped from 4% in 2022 to 18% in 2023.

Trend 10: The Fine-Grained Authorization Market Heats Up. As digital platforms and business app creation continue to proliferate, the need for dynamic and fine-grained access controls is extending beyond security. Forrester says that the IAM market is moving toward centralized and external authorization patterns because of B2B2E and B2B2C relationships and the possibility that genAI could make it easier to create and manage authorization policies.

Researching the intersection of AI, machine learning and cybersecurity in the enterprise

Posts tagged ‘cybersecurity’

Key takeaways

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The full market breakdown

Infrastructure takes 54% of every AI dollar

The agentic crossover nobody is planning for

AI cybersecurity is two markets, not one

Shadow AI is not just employees using ChatGPT

The smallest market with the biggest growth rate

Indirect services are the governance blind spot

Servers are a bigger market than AI software

The enterprise agentic stack is showing up in spending data

The numbers that belong in your next board deck

Where I think this lands

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The spending backdrop: $244 billion and accelerating

Trend 1: Agentic AI demands cybersecurity oversight

Trend 2: Global regulatory volatility drives cyber resilience efforts

Trend 3: Post-quantum computing moves into action plans

Trend 4: Identity and access management adapts to AI agents

Trend 5: AI-driven SOC solutions destabilize operational norms

Trend 6: GenAI breaks traditional cybersecurity awareness tactics

Total market trajectory: $173.5 billion to $323.5 billion

What this means for CISOs

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The acceleration is real

Where the money flows

Insights into deal sizes

The AI/LLM security gap

How spending breaks out geographically

ServiceNow’s acquisitions signal large-scale consolidation

What this means for 2026

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What these growth rates say about Gartner’s view of the market

The 15 categories reshaping security architecture

The Investment Thesis behind the numbers

The Bottom Line

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1. Identity Security Budgets Accelerate Toward $27.5B by 2029

2. Hybrid IAM Still Dominates—77% Keep On-Premise Components

3. Third-party Risk Matches Compliance as a Top IAM Driver

4. Static Entitlements Are Obsolete; Zero Standing Privilege Is Now Mandatory

5. Identity Management Converges Across Security, Marketing, and CX

6. Vendor Consolidation Radically Reshapes IAM Markets

7. Generative AI Exacerbates Identity Threats but Offers Transformational Defenses

8. Machine Identities Are a Critical Emerging Attack Vector

9. Phishing-Resistant MFA Is Dangerously Under-Deployed

10. Context-Aware IAM Becomes a Real-time Security Necessity

Bottom Line: Adaptive identity security defines enterprise survival

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A fast-changing threatscape is changing spending priorities

Top ten insights from Forrester’s 2026 cybersecurity budget benchmarks

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CISOs are remaining optimistic

Key takeaways

CISOs are dealing with a threatscape moving at machine speed

Practical guidance from CISOs adding GenAI to their arsenals

Bottom Line

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Cybersecurity needs funding to match its business growth potential

Top Ten Insights

Balancing the scales of cybersecurity budgeting

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Adversarial AI is taking aim at identities

Top ten trends defining identity and access management (IAM) in 2024

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