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Posts tagged ‘AI CyberSecurity’

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.

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).

Data readiness and security are driving AI’s $4.7 trillion run

Gartner Projects $4.7 Trillion AI Market by 2029 as Security and Data Drive Growth

Gartner’s most comprehensive AI spending forecast reveals the fundamental growth catalysts. AI-ready data predicted to deliver a 155% CAGR. Cybersecurity at 74%. Agentic capabilities crossing 50% of software spend by 2028.

Infrastructure gets the headlines. Hyperscalers are spending over $300 billion on data centers in 2025. McKinsey projects $5.2 trillion in data center investment by 2030. NVIDIA Blackwell deployments are driving 76% growth in accelerated server spending.

Gartner’s newly released Forecast Analysis: AI Spending, 4Q25 (December 17, 2025) tells a different story about where the acceleration is happening. Global AI spending reaches $1.8 trillion in 2025 and $4.7 trillion by 2029 at 33% CAGR. The growth catalysts:

  • AI Data. 155.4% CAGR. Spending increases 7x as enterprises recognize AI-ready data is non-negotiable for scaling.
  • AI Cybersecurity. 73.9% CAGR. From $26 billion to $172 billion. Over 50% of successful AI agent attacks will exploit prompt injection through 2029.
  • AI Models. 67.7% CAGR. Reasoning models underpin 70%+ of agentic AI applications by 2029.
  • AI Software. 47.0% CAGR. Agentic capabilities cross 50% of application software spend by the end of 2028. Non-agentic spending declines starting in 2027.

Infrastructure dominates absolute spending ($965 billion in 2025, growing to $2.25 trillion by 2029). At 29.2% CAGR, it’s the slower-growth segment. The acceleration is in data, security, and agentic capabilities.

The infrastructure buildout in context

The hyperscalers are building at a pace that strains global power grids. Dell’Oro Group’s Q2 2025 analysis shows worldwide data center capex up 43% year-over-year, with accelerated server spending surging 76% on NVIDIA Blackwell deployments. Amazon, Google, Meta, and Microsoft are collectively spending over $300 billion on data center infrastructure in 2025. CreditSights estimates aggregate hyperscaler capex reaches $602 billion in 2026, with approximately 75% earmarked for AI.

Gartner’s forecast aligns with infrastructure volume. AI-optimized server spending jumps 49% in 2026, representing 17% of total AI spending. GPUs account for over 90% of AI-optimized server spending on training throughout the forecast period. Infrastructure is table stakes. The differentiation is elsewhere.

Gartner’s bubble chart mapping 2026 growth rate (X-axis) against 2024-2029 CAGR (Y-axis), with bubble size representing 2025 spending. AI Data sits alone in the upper right quadrant. AI Cybersecurity and AI Models cluster at 70%+ CAGR. AI Infrastructure anchors the center as the dominant bubble. Source: Gartner Forecast Analysis: AI Spending, 4Q25, December 2025.

Gartner’s AI spending forecast by market, 2024-2029

The maturity gap

McKinsey’s 2025 State of AI survey explains why growth rates matter more than absolute spending for most organizations. 88% of organizations now use AI in at least one business function, up from 78% a year ago. Only 6% qualify as “AI high performers”, capturing meaningful enterprise-wide financial impact. Only 1% describe themselves as “mature” in AI deployment. Gartner’s CFO survey found just 11% of finance leaders from organizations implementing AI reported seeing actual financial returns.

The bottleneck is rarely compute. Gartner identifies three categories of readiness: infrastructure, data, and human. For every 100 days of AI implementation, 25 or more days may be consumed solely by change management and workforce resistance. Sharing work tasks with an AI agent, trusting results, and managing handoffs. That’s a fundamental shift in how employees work.

What the growth rates signal

AI cybersecurity’s 73.9% CAGR reflects a threat model shift. Security teams are spending because AI agents introduce attack surfaces that traditional security architectures weren’t designed to address. Gartner projects that over 50% of successful attacks against AI agents will exploit access control issues via prompt injection through 2029. By 2028, over 75% of enterprises will use AI-amplified cybersecurity products for most use cases, up from less than 25% in 2025.

AI data’s 155.4% CAGR signals enterprises are finally investing in foundations. The smallest segment by absolute spending is the fastest-growing because organizations scaling beyond pilots are discovering that AI-ready data isn’t optional. Labeled, annotated, quality-checked. By 2029, 61% of data integration software spend will focus on delivering GenAI-ready data, up from 8% in 2025. Synthetic data becomes dominant. 77% of data used for LLM training will be synthetic by 2029, up from 4% in 2025.

Agentic AI is reshaping software economics. By the end of 2028, software with agentic capabilities crosses 50% of total application software spend, up from 2% in 2024. Starting in 2027, non-agentic software spending declines. Investment in reasoning models underpins 70%+ of agentic AI applications by 2029. Open-source agentic frameworks will power more than 75% of enterprise AI agent deployments by 2028, eroding proprietary platform pricing power.

The inference shift is underway. By 2029, 66% of AI-optimized IaaS spending supports inference, not training. The balance shifts as embedded fine-tuned models become the norm in production applications.

Forecast assumptions by segment

AI Services. By 2029, 50% of all AI projects moving into production will be GenAI-centric, up from 12% in 2025. POC abandonment rates improve from 60% in 2024 to 35% in 2029. Specialized AI services command 20-30% price premiums.

AI Software. From 2027, spending on software without agentic capabilities starts declining. By 2027, one-third of agentic AI implementations will use combinations of agents with different skills for complex tasks.

AI Models. Starting in 2027, the shift toward in-house domain-specific language models constrains new spending in the specialized model market. Open-source model adoption erodes proprietary pricing power through 2029.

AI Platforms. By 2029, over 60% of enterprises will adopt AI agent development platforms to automate complex workflows. By 2030, enterprise application portfolios will include 40% custom applications built using AI-native development platforms, up from 2% in 2025.

AI Infrastructure. Export restrictions keep Chinese ASPs at about 50% of North American levels throughout the forecast. By 2026, NVL72 will become the de facto standard for large clusters. By the end of 2027, all hyperscalers will have reaffirmed Ethernet as their primary networking choice for AI workloads.

Devices. By 2029, more than 99% of PC microprocessors will have integrated on-device AI functionality, up from 15% in 2024. By 2027, efficient small language models will enable advanced GenAI to run locally on smartphones without cloud reliance.

The capital flow

The 2026 Gartner CIO Survey found GenAI and traditional AI among the most common technology areas selected for funding increases. 84% and 81% respectively. Nearly two-thirds of U.S. VC deal value went to AI companies in the first three quarters of 2025.

By 2027, the majority of AI buyers will define business outcomes from project launch. The market matures from technology-first experimentation to outcome-driven deployment. That shift from supply-push to demand-pull separates organizations capturing value from those still running pilots.

The infrastructure buildout continues. The growth signal is clear. Data readiness, security architecture, and agentic capabilities are where the acceleration is happening.

Top ten cybersecurity startups to watch in 2025 according to $3.21B in investor bets

Top Ten Cybersecurity Startups to Watch in 2025 According to $3.21B in Investor Bets

While the industry still debates whether AI will transform cybersecurity, investors have already made up their minds.

Based on an analysis of the latest Crunchbase data compiled recently that spans January 2024 to October 2025, ten standout startups captured $1.41 billion in new funding, signaling that machine-speed defense against AI-driven threats is no longer optional; it’s an operational reality. Together, these ten startups have raised $3.21 billion, which represents one of the heaviest capital concentrations in cybersecurity startups to date.

Investors are gravitating to cybersecurity startups that solve complex problems

CrowdStrike’s Falcon 2025 event, held earlier this year in Las Vegas, showcased a series of new agentic AI developments that, taken together, reflect how cross-platform and cross-competitor collaboration aimed at shutting down increasingly complex weaponized AI threats leads to faster innovation. VentureBeat’s analysis of the many announcements there explains how the cybersecurity company is betting on agentic AI to defeat adversaries.

Interested in quantifying how AI is impacting investors’ decisions, I completed an analysis using Crunchbase data covering 342 verified cybersecurity startups with active funding. Selection was weighted toward recent momentum, total funding scale, stage maturity, AI integration, and proof through multiple rounds.

The key takeaway: Institutional capital is consolidating around companies that make autonomous security practical, and agentic AI is at the core of that direction. But AI is not enough; investors are looking for the ability to scale in enterprises once they have AI integrated into their core platforms.

AI in cybersecurity: Tablestakes, not a ticket to premium valuation

Sixty percent of startups integrate AI into their core technology. Yet contrary to hype, that hasn’t bought them higher valuations.

  • AI-integrated startups average $283M in funding.
  • Non-AI specialists average $378M.

Crunchbase data shows investors reward defensible specialization as much as AI capability. Quantinuum’s $925M for post-quantum cryptography and Zama’s $139M for homomorphic encryption prove that solving foundational security problems often supersedes AI as a differentiator.

Still, AI holds weight in investment decisions. Six AI-driven startups pulled $1.70B (52.8%), while four non-AI companies captured $1.51B (47.2%). Both models earn trust by underscoring AI for operational speed and deep tech for architectural resilience. And with seven of ten now at Series B maturity, investors are backing platforms that have already demonstrated enterprise traction, not experiments.

1. Quantinuum ($925M, Series B) Post-Quantum Defense. Closed a $600M Series B in August 2025. The company is building the only mathematical safeguard against the inevitable collapse of RSA and ECC encryption under quantum computing.

2. Saronic ($845M, Series B) Autonomous Maritime Security, Raised $175M in July 2024 for AI-powered unmanned surface vessels. With 90% of trade moving across exposed waterways, Saronic brings AI defense to the physical infrastructure that most enterprises overlook.

3. Auradine ($314M, Series B) AI Silicon for Security. Raised $80M to expand custom silicon that accelerates cryptographic workloads 10x faster than general-purpose hardware, eliminating bottlenecks in AI-driven security deployments.

4. Tines ($271M, Series B) No-Code Automation. Secured $50M Series B. Turns analysts into automation builders, saving 40+ hours weekly with drag-and-drop workflows that are proving critical for overextended SOC teams.

5. Dream Security ($198M, Series B) Critical Infrastructure Defense. Closed $100M in 2025. Their sovereign AI platform equips critical infrastructure with defenses calibrated to nation-state-level threats, providing a layer that traditional enterprise tools cannot reach.

6. Upwind Security ($180M, Series A)  Runtime Cloud Visibility. Raised $100M in December 2024. Focused on runtime intelligence, detecting abnormal behavior live rather than flagging static misconfigurations. Reduces false positives, elevates real threats.

7. Zama ($139M, Series B)  Homomorphic Encryption. Raised $57M in June 2025 after a $73M Series A in March 2024. Provides production-ready fully homomorphic encryption, enabling AI models to compute securely on encrypted data.

8. Noma Security ($132M, Series B)  Securing AI Agents. Closed $100M in 2025. Built to harden AI systems against prompt injection and model poisoning as enterprises push decision-making into autonomous agents.

9. ZeroEyes ($107M, Series B)  Firearm Detection AI. Raised $53M in 2025. Eleven rounds in, their AI models detect firearms on video feeds in seconds—cutting active shooter response time dramatically.

10. Upscale AI ($100M, Seed)  AI Networking Infrastructure. Raised a $100M Seed round in 2025. Building AI-native networking with hardware-accelerated encryption, aimed at high-performance compute environments.

The Bottom Line

Series B dominance (70%) shows that capital is flowing into platforms with market traction, not speculative bets. Forty-six rounds across these ten companies demonstrate durability and enterprise validation. The signal to security leaders is becoming clear based on the escalating nature of weaponized AI attacks: manual security processes are now liabilities. Defending at human speed against AI-enabled attackers is untenable. Investors understand this. $1.41B in recent capital confirms it.

Gartner Predicts Solid Growth for Information Security, Reaching $287 Billion by 2027

Gartner Predicts Solid Growth for Information Security, Reaching $287 Billion by 2027

Image created in DALL-E

AI continues to become more weaponized with nation-state attackers and cybercrime gangs experimenting with LLMs and gen AI-based attack tradecraft. The age of weaponized LLMs is here.

At the same time, multi-cloud-based infrastructures more businesses rely on are coming under attack. Exfiltrating any identity data available from endpoints and then traversing a network to gain more access by collecting more credential data is often the goal.

Cyberattacks that combine AI and social engineering are just beginning  

Attackers have a version of human-in-the-middle, too, but their goal is to unleash AI’s offensive attack capabilities within social engineering campaigns. Last year’s social engineering-based attacks on MGM, Comcast, Shield Healthcare Group, and others serve as a case in point.

CrowdStrike’s 2024 Global Threat Report finds that cloud intrusions jumped 75% last year. There was a 76% increase in data theft victims named on data leak sites and a 60% increase in interactive intrusion campaigns. Worse, 75% of attacks were malware-free, making them difficult to identify and stop. There was also a 110% YoY increase in cloud-conscious cases.

PwC’s 2024 Digital Trust Insights Report finds that 97% of senior management teams have gaps in their cloud risk management plans. 47% say cloud attacks are their most urgent threat. One in three senior management teams is prioritizing cloud security as their top investment this year.

Gartner sees a more complex threatscape driving growth

Gartner’s Forecast: Information Security and Risk Management, Worldwide, 2021-2027, 4Q23 Update report predicts the information security and risk management market will grow from $185 billion in 2023 to $287 billion in 2027, attaining a compound annual growth rate of 11% in constant currency.

Nation-state attackers are picking up the pace of their stealthy AI arms race. They’re looking to score offensive first victories on an increasingly active digital battlefield. Gartner predicts that in 2027, 17% of the total cyberattacks and data leaks will involve generative AI.

Another key assumption driving Gartner’s latest forecast is that by 2025, user efficiency improvements will drive at least 35% of security vendors to offer large language model (LLM)-driven chat capabilities for users to interact with their applications and data, up from 1% in 2022.

Gartner has also factored in the surge in cloud attacks and the continued growth of hybrid workforces. One of their key assumptions driving the forecast is that “by the end of 2026, the democratization of technology, digitization, and automation of work will increase the total available market of fully remote and hybrid workers to 64% of all employees, up from 52% in 2021.”

Gartner Predicts Solid Growth for Information Security, Reaching $287 Billion by 2027

Source: Gartner, Forecast Analysis: Information Security and Risk Management, Worldwide, Published February 29, 2024

Source: Gartner, Forecast Analysis: Information Security and Risk Management, Worldwide, Published 29 February 2024

Key takeaways from Gartner’s forecast

Market subsegments predicted to see the most significant growth through 2027 include the following:

  • Gartner has high expectations for Zero Trust Network Access (ZTNA) growth, stating the worldwide market was worth $575.7 million in 2021 and predicting it will soar to $3.99 billion in 2027, attaining a 31.6% CAGR in the forecast period.
  • Identity Access Management (IAM) is predicted to grow from $4 billion in 2021 to $11.1 billion in 2027, attaining a 17.6% CAGR. Identity Governance and Administration software is predicted to grow from $2.8 billion in 2021 to $5.77 billion in 2027, attaining a 12.8% CAGR.
  • Endpoint Protection Platforms (EPP) are predicted to grow from $9.8 billion in 2021 to $26.9 billion in 2027, achieving a 17.2% CAGR.
  • Threat Intelligence software is predicted to grow from $1.1 billion in 2021 to $2.79 billion in 2027, growing at a 15.6% CAGR through the forecast period.
  • Cloud Access Security Brokers (CASB) is predicted to grow from $928M in 2021 to $4.75 billion in 2027, attaining a CAGR of 30.2%. Gartner believes that the market share of cloud-native solutions will continue to grow. They are predicting that the combined market for cloud access security brokers (CASBs) and cloud workload protection platforms (CWPPs) will reach $12.8 billion in constant currency by 2027, up from $4.6 billion in 2022. Gartner continues to also see strong demand for cloud-based detection and response solutions that include endpoint detection and response (EDR) and managed detection and response (MDR).

How To Redefine The Future Of Fraud Prevention

How To Redefine The Future Of Fraud Prevention

Bottom Line: Redefining the future of fraud prevention starts by turning trust into an accelerator across every aspect of customer lifecycles, basing transactions on identity trust that leads to less friction and improved customer experiences.

Start By Turning Trust Into A Sales & Customer Experience Accelerator

AI and machine learning are proving to be very effective at finding anomalies in transactions and scoring, which are potentially the most fraudulent. Any suspicious transaction attempt leads to more work for buying customers to prove they are trustworthy. For banks, e-commerce sites, financial institutes, restaurants, retailers and many other online businesses, this regularly causes them to lose customers when a legitimate purchase is being made, and trusted customer is asked to verify their identity. Or worse, a false positive that turns away a good customer all together damages both that experience and brand reputation.

There’s a better way to solve the dilemma of deciding which transactions to accept or not. And it needs to start with finding a new way to establish identity trust so businesses can deliver better user experiences. Kount’s approach of using their Real-Time Identity Trust Network to calculate Identity Trust Levels in milliseconds reduces friction, blocks fraud, and delivers an improved user experience. Kount is capitalizing on their database that includes more than a decade of trust and fraud signals built across industries, geographies, and 32 billion annual interactions, combined with expertise in AI and machine learning to turn trust into a sales and customer experience multiplier.

How Real-Time AI Linking Leads To Real-Time Identity Trust Decisions

Design In Identity Trust So It’s The Foundation of Customer Experience

From an engineering and product design standpoint, the majority of fraud prevention providers are looking to make incremental gains in risk scoring to improve customer experiences. None, with the exception of Kount, are looking at the problem from a completely different perspective, which is how to quantify and scale identity trust. Kount’s engineering, product development, and product management teams are concentrating on how to use their AI and machine learning expertise to quantify real-time identity trust scores that drive better customer experiences across the spectrum of trust. The graphic below illustrates how Kount defines more personalized user experiences, which is indispensable in turning trust into an accelerator.

An Overview of Kount’s Technology Stack

How To Redefine The Future Of Fraud Prevention

Realize Trust Is the Most Powerful Revenue Multiplier There Is

Based on my conversations with several fraud prevention providers, they all agree that trust is the most powerful accelerator there is to reducing false positives, friction in transactions, and improving customer experiences. They all agree trust is the most powerful revenue multiplier they can deliver to their customers, helping them reduce fraud and increase sales. The challenge they all face is quantifying identity trust across the wide spectrum of transactions their customers need to fulfill every day.

Kount has taken a unique approach to identity trust that puts the customer at the center of the transactions, not just their transactions’ risk score. By capitalizing on the insights gained from their Identity Trust Global Network, Kount can use AI and machine learning algorithms to deliver personalized responses to transaction requests in milliseconds. Using both unsupervised and supervised machine learning algorithms and techniques, Kount can learn from every customer interaction, gaining new insights into how to fine-tune identity trust for every customer’s transaction.

In choosing to go in the direction of identity trust in its product strategy, Kount put user experiences at the core of their platform strategy. By combining adaptive fraud protection, personalized user experience, and advanced analytics, Kount can create a continuously learning system with the goal of fine-tuning identity trust for every transaction their customers receive. The following graphic explains their approach for bringing identity trust into the center of their platform:

Putting Customers & Their Experiences First Is Integral To Succeeding With Identity Trust

How To Redefine The Future Of Fraud Prevention

 

Improving customer experiences needs to be the cornerstone that drives all fraud prevention product and services road maps in 2020 and beyond. And while all fraud prevention providers are looking at how to reduce friction and improve customer experiences with fraud scoring AI-based techniques, their architectures and approaches aren’t going in the direction of identity trust. Kount’s approach is, and it’s noteworthy because it puts customer experiences at the center of their platform. How to redefine the future of fraud prevention needs to start by turning trust into a sales and customer experience accelerator, followed by designing in identity trust. Hence, it’s the foundation of all customer experiences. By combining the power of networked data and adaptive AI and machine learning, more digital businesses can turn trust into a revenue and customer experience multiplier.

Top 10 Cybersecurity Companies To Watch In 2020

Worldwide spending on information security and risk management systems will reach $131B in 2020, increasing to $174B in 2022 approximately $50B will be dedicated to protecting the endpoint according to Gartner’s latest Information Security and Risk Management forecast. Cloud Security platform and application sales are predicted to grow from $636M in 2020 to $1.63B in 2023, attaining a 36.8% Compound Annual Growth Rate (CAGR) and leading all categories of Information & Security Risk Management systems. Application Security is forecast to grow from $3.4B in 2020 to $4.5B in 2023, attaining a 9.7% CAGR. Security Services is projected to be a $66.9B market this year, increasing from $62B in 2019. AI, Machine Learning And The Race To Improve Cybersecurity The majority of Information Security teams’ cybersecurity analysts are overwhelmed today analyzing security logs, thwarting breach attempts, investigating potential fraud incidents and more. 69% of senior executives believe AI and machine learning are necessary to respond to cyberattacks according to the Capgemini study, Reinventing Cybersecurity with Artificial Intelligence. The following graphic compares the percentage of organizations by industry who are relying on AI to improve their cybersecurity. 80% of telecommunications executives believe their organization would not be able to respond to cyberattacks without AI, with the average being 69% of all enterprises across seven industries. Top 10 Cybersecurity Companies To Watch In 2020 STATISTA The bottom line is all organizations have an urgent need to improve endpoint security and resilience, protect privileged access credentials, reduce fraudulent transactions, and secure every mobile device applying Zero Trust principles. Many are relying on AI and machine learning to determine if login and resource requests are legitimate or not based on past behavioral and system use patterns. Several of the top ten companies to watch take into account a diverse series of indicators to determine if a login attempt, transaction, or system resource request is legitimate or not. They’re able to assign a single score to a specific event and predict if it’s legitimate or not. Kount’s Omniscore is an example of how AI and ML are providing fraud analysts with insights needed to reduce false positives and improve customer buying experiences while thwarting fraud. The following are the top ten cybersecurity companies to watch in 2020: Absolute – Absolute serves as the industry benchmark for endpoint resilience, visibility and control. Embedded in over a half-billion devices, the company enables more than 12,000 customers with self-healing endpoint security, always-connected visibility into their devices, data, users, and applications – whether endpoints are on or off the corporate network – and the ultimate level of control and confidence required for the modern enterprise. To thwart attackers, organizations continue to layer on security controls — Gartner estimates that more than $174B will be spent on security by 2022, and of that approximately $50B will be dedicated protecting the endpoint. Absolute’s Endpoint Security Trends Report finds that in spite of the astronomical investments being made, 100 percent of endpoint controls eventually fail and more than one in three endpoints are unprotected at any given time. All of this has IT and security administrators grappling with increasing complexity and risk levels, while also facing mounting pressure to ensure endpoint controls maintain integrity, availability and functionality at all times, and deliver their intended value. Organizations need complete visibility and real-time insights in order to pinpoint the dark endpoints, identify what’s broken and where gaps exist, as well as respond and take action quickly. Absolute mitigates this universal law of security decay and empowers organizations to build an enterprise security approach that is intelligent, adaptive and self-healing. Rather than perpetuating a false sense of security, Absolute provides a single source of truth and the diamond image of resilience for endpoints. Centrify - Centrify is redefining the legacy approach to Privileged Access Management (PAM) with an Identity-Centric approach based on Zero Trust principles. Centrify’s 15-year history began in Active Directory (AD) bridging, and it was the first vendor to join UNIX and Linux systems with Active Directory, allowing for easy management of privileged identities across a heterogeneous environment. It then extended these capabilities to systems being hosted in IaaS environments like AWS and Microsoft Azure, and offered the industry’s first PAM-as-a-Service, which continues to be the only offering in the market with a true multi-tenant, cloud architecture. Applying its deep expertise in infrastructure allowed Centrify to redefine the legacy approach to PAM and introduce a server’s capability to self-defend against cyber threats across the ever-expanding modern enterprise infrastructure. Centrify Identity-Centric PAM establishes a root of trust for critical enterprise resources, and then grants least privilege access by verifying who is requesting access, the context of the request, and the risk of the access environment. By implementing least privilege access, Centrify minimizes the attack surface, improves audit and compliance visibility, and reduces risk, complexity, and costs for the modern, hybrid enterprise. Over half of the Fortune 100, the world’s largest financial institutions, intelligence agencies, and critical infrastructure companies, all trust Centrify to stop the leading cause of breaches – privileged credential abuse. Research firm Gartner predicts that by 2021, approximately 75% of large enterprises will utilize privileged access management products, up from approximately 50% in 2018 in their Forecast Analysis: Information Security and Risk Management, Worldwide, 4Q18 Update published March 29, 2019 (client access reqd). This is not surprising, considering that according to an estimate by Forrester Research, 80% of today’s breaches are caused by weak, default, stolen, or otherwise compromised privileged credentials. Deep Instinct – Deep Instinct applies artificial intelligence’s deep learning to cybersecurity. Leveraging deep learning’s predictive capabilities, Deep Instinct’s on-device solution protects against zero-day threats and APT attacks with unmatched accuracy. Deep Instinct safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet. By applying deep learning technology to cybersecurity, enterprises can now gain unmatched protection against unknown and evasive cyber-attacks from any source. Deep Instinct brings a completely new approach to cybersecurity enabling cyber-attacks to be identified and blocked in real-time before any harm can occur. Deep Instinct USA is headquartered in San Francisco, CA and Deep Instinct Israel is headquartered in Tel Aviv, Israel. Infoblox - Infoblox empowers organizations to bring next-level simplicity, security, reliability and automation to traditional networks and digital transformations, such as SD-WAN, hybrid cloud and IoT. Combining next-level simplicity, security, reliability and automation, Infoblox is able to cut manual tasks by 70% and make organizations’ threat analysts 3x more productive. While their history is in DDI devices, they are succeeding in providing DDI and network security services on an as-a-service (-aaS) basis. Their BloxOne DDI application, built on their BloxOne cloud-native platform, helps enable IT, professionals, to manage their networks whether they're based on on-prem, cloud-based, or hybrid architectures. BloxOne Threat Defense application leverages the data provided by DDI to monitor network traffic, proactively identify threats, and quickly inform security systems and network managers of breaches, working with the existing security stack to identify and mitigate security threats quickly, automatically, and more efficiently. The BloxOne platform provides a secure, integrated platform for centralizing the management of identity data and services across the network. A recognized industry leader, Infoblox has a 52% market share in the DDI networking market comprised of 8,000 customers, including 59% of the Fortune 1000 and 58% of the Forbes 2000. Kount – Kount’s award-winning, AI-driven fraud prevention empowers digital businesses, online merchants, and payment service providers around the world to protect against payments fraud, new account creation fraud, and account takeover. With Kount, businesses approve more good orders, uncover new revenue streams, improve customer experience and dramatically improve their bottom line all while minimizing fraud management cost and losses. Through Kount’s global network and proprietary technologies in AI and machine learning, combined with flexible policy management, companies frustrate online criminals and bad actors driving them away from their site, their marketplace, and off their network. Kount’s continuously adaptive platform provides certainty for businesses at every digital interaction. Kount’s advances in both proprietary techniques and patented technology include mobile fraud detection, advanced artificial intelligence, multi-layer device fingerprinting, IP proxy detection and geo-location, transaction and custom scoring, global order linking, business intelligence reporting, comprehensive order management, as well as professional and managed services. Kount protects over 6,500 brands today. Mimecast – Mimecast improves the way companies manage confidential, mission-critical business communication and data. The company's mission is to reduce the risks users face from email, and support in reducing the cost and complexity of protecting users by moving the workload to the cloud. The company develops proprietary cloud architecture to deliver comprehensive email security, service continuity, and archiving in a single subscription service. Its goal is to make it easier for people to protect a business in today’s fast-changing security and risk environment. The company expanded its technology portfolio in 2019 through a pair of acquisitions, buying data migration technology provider Simply Migrate to help customers and prospects move to the cloud more quickly, reliably, and inexpensively. Mimecast also purchased email security startup DMARC Analyzer to reduce the time, effort, and cost associated with stopping domain spoofing attacks. Mimecast acquired Segasec earlier this month, a leading provider of digital threat protection. With the acquisition of Segasec, Mimecast can provide brand exploit protection, using machine learning to identify potential hackers at the earliest stages of an attack. The solution also is engineered to provide a way to actively monitor, manage, block, and take down phishing scams or impersonation attempts on the Web. MobileIron – A long-time leader in mobile management solutions, MobileIron is widely recognized by Chief Information Security Officers, CIOs and senior management teams as the de facto standard for unified endpoint management (UEM), mobile application management (MAM), BYOD security, and zero sign-on (ZSO). The company’s UEM platform is strengthened by MobileIron Threat Defense and MobileIron’s Access solution, which allows for zero sign-on authentication. Forrester observes in their latest Wave on Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 that “MobileIron’s recently released authenticator, which enables passwordless authentication to cloud services, is a must for future-state Zero Trust enterprises and speaks to its innovation in this space.” The Wave also illustrates that MobileIron is the most noteworthy vendor as their approach to Zero Trust begins with the device and scales across mobile infrastructures. MobileIron’s product suite also includes a federated policy engine that enables administrators to control and better command the myriad of devices and endpoints that enterprises rely on today. Forrester sees MobileIron as having excellent integration at the platform level, a key determinant of how effective they will be in providing support to enterprises pursuing Zero Trust Security strategies in the future. One Identity – One Identity is differentiating its Identity Manager identity analytics and risk scoring capabilities with greater integration via its connected system modules. The goal of these modules is to provide customers with more flexibility in defining reports that include application-specific content. Identity Manager also has over 30 direct provisioning connectors included in the base package, with good platform coverage, including strong Microsoft and Office 365 support. Additional premium connectors are charged separately. One Identity also has a separate cloud-architected SaaS solution called One Identity Starling. One of Starling’s greatest benefits is its design that allows for it to be used not only by Identity Manager clients, but also by clients of other IGA solutions as a simplified approach to obtain SaaS-based identity analytics, risk intelligence, and cloud provisioning. One Identity and its approach is trusted by customers worldwide, where more than 7,500 organizations worldwide depend on One Identity solutions to manage more than 125 million identities, enhancing their agility and efficiency while securing access to their systems and data – on-prem, cloud, or hybrid. SECURITI.ai - SECURITI.ai is the leader in AI-Powered PrivacyOps, that helps automate all major functions needed for privacy compliance in one place. It enables enterprises to give rights to people on their data, be responsible custodians of people’s data, comply with global privacy regulations like CCPA and bolster their brands. The AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. These include a Personal Data Graph Builder, Robotic Automation for Data Subject Requests, Secure Data Request Portal, Consent Lifecycle Manager, Third-Party Privacy Assessment, Third-Party Privacy Ratings, Privacy Assessment Automation and Breach Management. SECURITI.ai is also featured in the Consent Management section of Bessemer’s Data Privacy Stack shown below and available in Bessemer Venture Partner’s recent publication How data privacy engineering will prevent future data oil spills (10 pp., PDF, no opt-in). Top 10 Cybersecurity Companies To Watch In 2020 SOURCE: BESSEMER VENTURE PARTNERS, HOW DATA PRIVACY ENGINEERING WILL PREVENT FUTURE DATA OIL SPILLS , SEPTEMBER, 2019. (10 PP., PDF, NO OPT-IN). Transmit Security - The Transmit Security Platform provides a solution for managing identity across applications while maintaining security and usability. As criminal threats evolve, online authentication has become reactive and less effective. Many organizations have taken on multiple point solutions to try to stay ahead, deploying new authenticators, risk engines, and fraud tools. In the process, the customer experience has suffered. And with an increasingly complex environment, many enterprises struggle with the ability to rapidly innovate to provide customers with an omnichannel experience that enables them to stay ahead of emerging threats.

  • Worldwide spending on information security and risk management systems will reach $131B in 2020, increasing to $174B in 2022 approximately $50B will be dedicated to protecting the endpoint according to Gartner’s latest Information Security and Risk Management forecast.
  • Cloud Security platform and application sales are predicted to grow from $636M in 2020 to $1.63B in 2023, attaining a 36.8% Compound Annual Growth Rate (CAGR) and leading all categories of Information & Security Risk Management systems.
  • Application Security is forecast to grow from $3.4B in 2020 to $4.5B in 2023, attaining a 9.7% CAGR.
  • Security Services is projected to be a $66.9B market this year, increasing from $62B in 2019.

AI, Machine Learning And The Race To Improve Cybersecurity  

The majority of Information Security teams’ cybersecurity analysts are overwhelmed today analyzing security logs, thwarting breach attempts, investigating potential fraud incidents and more. 69% of senior executives believe AI and machine learning are necessary to respond to cyberattacks according to the Capgemini study, Reinventing Cybersecurity with Artificial Intelligence. The following graphic compares the percentage of organizations by industry who are relying on AI to improve their cybersecurity. 80% of telecommunications executives believe their organization would not be able to respond to cyberattacks without AI, with the average being 69% of all enterprises across seven industries.

The bottom line is all organizations have an urgent need to improve endpoint security and resilience, protect privileged access credentials, reduce fraudulent transactions, and secure every mobile device applying Zero Trust principles. Many are relying on AI and machine learning to determine if login and resource requests are legitimate or not based on past behavioral and system use patterns. Several of the top ten companies to watch take into account a diverse series of indicators to determine if a login attempt, transaction, or system resource request is legitimate or not. They’re able to assign a single score to a specific event and predict if it’s legitimate or not. Kount’s Omniscore is an example of how AI and ML are providing fraud analysts with insights needed to reduce false positives and improve customer buying experiences while thwarting fraud.

The following are the top ten cybersecurity companies to watch in 2020:

Absolute – Absolute serves as the industry benchmark for endpoint resilience, visibility and control. Embedded in over a half-billion devices, the company enables more than 12,000 customers with self-healing endpoint security, always-connected visibility into their devices, data, users, and applications – whether endpoints are on or off the corporate network – and the ultimate level of control and confidence required for the modern enterprise.

To thwart attackers, organizations continue to layer on security controls — Gartner estimates that more than $174B will be spent on security by 2022, and of that approximately $50B will be dedicated protecting the endpoint. Absolute’s Endpoint Security Trends Report finds that in spite of the astronomical investments being made, 100 percent of endpoint controls eventually fail and more than one in three endpoints are unprotected at any given time. All of this has IT and security administrators grappling with increasing complexity and risk levels, while also facing mounting pressure to ensure endpoint controls maintain integrity, availability and functionality at all times, and deliver their intended value.

Organizations need complete visibility and real-time insights in order to pinpoint the dark endpoints, identify what’s broken and where gaps exist, as well as respond and take action quickly. Absolute mitigates this universal law of security decay and empowers organizations to build an enterprise security approach that is intelligent, adaptive and self-healing. Rather than perpetuating a false sense of security, Absolute provides a single source of truth and the diamond image of resilience for endpoints.

CentrifyCentrify is redefining the legacy approach to Privileged Access Management (PAM) with an Identity-Centric approach based on Zero Trust principles. Centrify’s 15-year history began in Active Directory (AD) bridging, and it was the first vendor to join UNIX and Linux systems with Active Directory, allowing for easy management of privileged identities across a heterogeneous environment. It then extended these capabilities to systems being hosted in IaaS environments like AWS and Microsoft Azure, and offered the industry’s first PAM-as-a-Service, which continues to be the only offering in the market with a true multi-tenant, cloud architecture. Applying its deep expertise in infrastructure allowed Centrify to redefine the legacy approach to PAM and introduce a server’s capability to self-defend against cyber threats across the ever-expanding modern enterprise infrastructure.

Centrify Identity-Centric PAM establishes a root of trust for critical enterprise resources, and then grants least privilege access by verifying who is requesting access, the context of the request, and the risk of the access environment. By implementing least privilege access, Centrify minimizes the attack surface, improves audit and compliance visibility, and reduces risk, complexity, and costs for the modern, hybrid enterprise. Over half of the Fortune 100, the world’s largest financial institutions, intelligence agencies, and critical infrastructure companies, all trust Centrify to stop the leading cause of breaches – privileged credential abuse.

Research firm Gartner predicts that by 2021, approximately 75% of large enterprises will utilize privileged access management products, up from approximately 50% in 2018 in their Forecast Analysis: Information Security and Risk Management, Worldwide, 4Q18 Update published March 29, 2019 (client access reqd). This is not surprising, considering that according to an estimate by Forrester Research, 80% of today’s breaches are caused by weak, default, stolen, or otherwise compromised privileged credentials.

Deep Instinct – Deep Instinct applies artificial intelligence’s deep learning to cybersecurity. Leveraging deep learning’s predictive capabilities, Deep Instinct’s on-device solution protects against zero-day threats and APT attacks with unmatched accuracy. Deep Instinct safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet. By applying deep learning technology to cybersecurity, enterprises can now gain unmatched protection against unknown and evasive cyber-attacks from any source. Deep Instinct brings a completely new approach to cybersecurity enabling cyber-attacks to be identified and blocked in real-time before any harm can occur. Deep Instinct USA is headquartered in San Francisco, CA and Deep Instinct Israel is headquartered in Tel Aviv, Israel.

Infoblox – Infoblox empowers organizations to bring next-level simplicity, security, reliability and automation to traditional networks and digital transformations, such as SD-WAN, hybrid cloud and IoT. Combining next-level simplicity, security, reliability, and automation, Infoblox can cut manual tasks by 70% and make organizations’ threat analysts 3x more productive.

While their history is in DDI devices, they are succeeding in providing DDI and network security services on an as-a-service (-aaS) basis. Their BloxOne DDI  application, built on their BloxOne cloud-native platform, helps enable IT professionals to manage their networks, whether they’re based on on-prem, cloud-based, or hybrid architectures.  BloxOne Threat Defense  application leverages the data provided by DDI to monitor network traffic, proactively identify threats, and quickly inform security systems and network managers of breaches, working with the existing security stack to identify and mitigate security threats quickly, automatically, and more efficiently. The BloxOne platform provides a secure, integrated platform for centralizing the management of identity data and services across the network. A recognized industry leader, Infoblox has a 52% market share in the DDI networking market comprised of 8,000 customers, including 59% of the Fortune 1000 and 58% of the Forbes 2000.

Kount – Kount’s award-winning, AI-driven fraud prevention empowers digital businesses, online merchants, and payment service providers around the world to protect against payments fraud, new account creation fraud, and account takeover. With Kount, businesses approve more good orders, uncover new revenue streams, improve customer experience, and dramatically improve their bottom line all while minimizing fraud management cost and losses. Through Kount’s global network and proprietary technologies in AI and machine learning, combined with flexible policy management, companies frustrate online criminals and bad actors driving them away from their site, their marketplace, and off their network. Kount’s continuously adaptive platform provides certainty for businesses at every digital interaction. Kount’s advances in both proprietary techniques and patented technology include mobile fraud detection, advanced artificial intelligence, multi-layer device fingerprinting, IP proxy detection and geo-location, transaction and custom scoring, global order linking, business intelligence reporting, comprehensive order management, as well as professional and managed services. Kount protects over 6,500 brands today.

MimecastMimecast improves the way companies manage confidential, mission-critical business communication and data. The company’s mission is to reduce the risks users face from email, and support in reducing the cost and complexity of protecting users by moving the workload to the cloud. The company develops proprietary cloud architecture to deliver comprehensive email security, service continuity, and archiving in a single subscription service. Its goal is to make it easier for people to protect a business in today’s fast-changing security and risk environment. The company expanded its technology portfolio in 2019 through a pair of acquisitions, buying data migration technology provider Simply Migrate to help customers and prospects move to the cloud more quickly, reliably, and inexpensively. Mimecast also purchased email security startup DMARC Analyzer to reduce the time, effort, and cost associated with stopping domain spoofing attacks. Mimecast acquired Segasec earlier this month, a leading provider of digital threat protection. With the acquisition of Segasec, Mimecast can provide brand exploit protection, using machine learning to identify potential hackers at the earliest stages of an attack. The solution also is engineered to provide a way to actively monitor, manage, block, and take down phishing scams or impersonation attempts on the Web.

MobileIron – A long-time leader in mobile management solutions, MobileIron is widely recognized by Chief Information Security Officers, CIOs and senior management teams as the de facto standard for unified endpoint management (UEM), mobile application management (MAM), BYOD security, and zero sign-on (ZSO). The company’s UEM platform is strengthened by MobileIron Threat Defense and MobileIron’s Access solution, which allows for zero sign-on authentication. Forrester observes in their latest Wave on Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 that “MobileIron’s recently released authenticator, which enables passwordless authentication to cloud services, is a must for future-state Zero Trust enterprises and speaks to its innovation in this space.” The Wave also illustrates that MobileIron is the most noteworthy vendor as their approach to Zero Trust begins with the device and scales across mobile infrastructures. MobileIron’s product suite also includes a federated policy engine that enables administrators to control and better command the myriad of devices and endpoints that enterprises rely on today. Forrester sees MobileIron as having excellent integration at the platform level, a key determinant of how effective they will be in providing support to enterprises pursuing Zero Trust Security strategies in the future.

One Identity – One Identity is differentiating its Identity Manager identity analytics and risk scoring capabilities with greater integration via its connected system modules. The goal of these modules is to provide customers with more flexibility in defining reports that include application-specific content. Identity Manager also has over 30 direct provisioning connectors included in the base package, with good platform coverage, including strong Microsoft and Office 365 support. Additional premium connectors are charged separately. One Identity also has a separate cloud-architected SaaS solution called One Identity Starling. One of Starling’s greatest benefits is its design that allows for it to be used not only by Identity Manager clients, but also by clients of other IGA solutions as a simplified approach to obtain SaaS-based identity analytics, risk intelligence, and cloud provisioning. One Identity and its approach is trusted by customers worldwide, where more than 7,500 organizations worldwide depend on One Identity solutions to manage more than 125 million identities, enhancing their agility and efficiency while securing access to their systems and data – on-prem, cloud, or hybrid.

SECURITI.ai – SECURITI.ai is the leader in AI-Powered PrivacyOps, that helps automate all major functions needed for privacy compliance in one place. It enables enterprises to give rights to people on their data, be responsible custodians of people’s data, comply with global privacy regulations like CCPA, and bolster their brands.

The AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. These include a Personal Data Graph Builder, Robotic Automation for Data Subject Requests, Secure Data Request Portal, Consent Lifecycle Manager, Third-Party Privacy Assessment, Third-Party Privacy Ratings, Privacy Assessment Automation and Breach Management. SECURITI.ai is also featured in the Consent Management section of Bessemer’s Data Privacy Stack shown below and available in Bessemer Venture Partner’s recent publication How data privacy engineering will prevent future data oil spills (10 pp., PDF, no opt-in).

Worldwide spending on information security and risk management systems will reach $131B in 2020, increasing to $174B in 2022 approximately $50B will be dedicated to protecting the endpoint according to Gartner’s latest Information Security and Risk Management forecast. Cloud Security platform and application sales are predicted to grow from $636M in 2020 to $1.63B in 2023, attaining a 36.8% Compound Annual Growth Rate (CAGR) and leading all categories of Information & Security Risk Management systems. Application Security is forecast to grow from $3.4B in 2020 to $4.5B in 2023, attaining a 9.7% CAGR. Security Services is projected to be a $66.9B market this year, increasing from $62B in 2019. AI, Machine Learning And The Race To Improve Cybersecurity The majority of Information Security teams’ cybersecurity analysts are overwhelmed today analyzing security logs, thwarting breach attempts, investigating potential fraud incidents and more. 69% of senior executives believe AI and machine learning are necessary to respond to cyberattacks according to the Capgemini study, Reinventing Cybersecurity with Artificial Intelligence. The following graphic compares the percentage of organizations by industry who are relying on AI to improve their cybersecurity. 80% of telecommunications executives believe their organization would not be able to respond to cyberattacks without AI, with the average being 69% of all enterprises across seven industries. Top 10 Cybersecurity Companies To Watch In 2020 STATISTA The bottom line is all organizations have an urgent need to improve endpoint security and resilience, protect privileged access credentials, reduce fraudulent transactions, and secure every mobile device applying Zero Trust principles. Many are relying on AI and machine learning to determine if login and resource requests are legitimate or not based on past behavioral and system use patterns. Several of the top ten companies to watch take into account a diverse series of indicators to determine if a login attempt, transaction, or system resource request is legitimate or not. They’re able to assign a single score to a specific event and predict if it’s legitimate or not. Kount’s Omniscore is an example of how AI and ML are providing fraud analysts with insights needed to reduce false positives and improve customer buying experiences while thwarting fraud. The following are the top ten cybersecurity companies to watch in 2020: Absolute – Absolute serves as the industry benchmark for endpoint resilience, visibility and control. Embedded in over a half-billion devices, the company enables more than 12,000 customers with self-healing endpoint security, always-connected visibility into their devices, data, users, and applications – whether endpoints are on or off the corporate network – and the ultimate level of control and confidence required for the modern enterprise. To thwart attackers, organizations continue to layer on security controls — Gartner estimates that more than $174B will be spent on security by 2022, and of that approximately $50B will be dedicated protecting the endpoint. Absolute’s Endpoint Security Trends Report finds that in spite of the astronomical investments being made, 100 percent of endpoint controls eventually fail and more than one in three endpoints are unprotected at any given time. All of this has IT and security administrators grappling with increasing complexity and risk levels, while also facing mounting pressure to ensure endpoint controls maintain integrity, availability and functionality at all times, and deliver their intended value. Organizations need complete visibility and real-time insights in order to pinpoint the dark endpoints, identify what’s broken and where gaps exist, as well as respond and take action quickly. Absolute mitigates this universal law of security decay and empowers organizations to build an enterprise security approach that is intelligent, adaptive and self-healing. Rather than perpetuating a false sense of security, Absolute provides a single source of truth and the diamond image of resilience for endpoints. Centrify - Centrify is redefining the legacy approach to Privileged Access Management (PAM) with an Identity-Centric approach based on Zero Trust principles. Centrify’s 15-year history began in Active Directory (AD) bridging, and it was the first vendor to join UNIX and Linux systems with Active Directory, allowing for easy management of privileged identities across a heterogeneous environment. It then extended these capabilities to systems being hosted in IaaS environments like AWS and Microsoft Azure, and offered the industry’s first PAM-as-a-Service, which continues to be the only offering in the market with a true multi-tenant, cloud architecture. Applying its deep expertise in infrastructure allowed Centrify to redefine the legacy approach to PAM and introduce a server’s capability to self-defend against cyber threats across the ever-expanding modern enterprise infrastructure. Centrify Identity-Centric PAM establishes a root of trust for critical enterprise resources, and then grants least privilege access by verifying who is requesting access, the context of the request, and the risk of the access environment. By implementing least privilege access, Centrify minimizes the attack surface, improves audit and compliance visibility, and reduces risk, complexity, and costs for the modern, hybrid enterprise. Over half of the Fortune 100, the world’s largest financial institutions, intelligence agencies, and critical infrastructure companies, all trust Centrify to stop the leading cause of breaches – privileged credential abuse. Research firm Gartner predicts that by 2021, approximately 75% of large enterprises will utilize privileged access management products, up from approximately 50% in 2018 in their Forecast Analysis: Information Security and Risk Management, Worldwide, 4Q18 Update published March 29, 2019 (client access reqd). This is not surprising, considering that according to an estimate by Forrester Research, 80% of today’s breaches are caused by weak, default, stolen, or otherwise compromised privileged credentials. Deep Instinct – Deep Instinct applies artificial intelligence’s deep learning to cybersecurity. Leveraging deep learning’s predictive capabilities, Deep Instinct’s on-device solution protects against zero-day threats and APT attacks with unmatched accuracy. Deep Instinct safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet. By applying deep learning technology to cybersecurity, enterprises can now gain unmatched protection against unknown and evasive cyber-attacks from any source. Deep Instinct brings a completely new approach to cybersecurity enabling cyber-attacks to be identified and blocked in real-time before any harm can occur. Deep Instinct USA is headquartered in San Francisco, CA and Deep Instinct Israel is headquartered in Tel Aviv, Israel. Infoblox - Infoblox empowers organizations to bring next-level simplicity, security, reliability and automation to traditional networks and digital transformations, such as SD-WAN, hybrid cloud and IoT. Combining next-level simplicity, security, reliability and automation, Infoblox is able to cut manual tasks by 70% and make organizations’ threat analysts 3x more productive. While their history is in DDI devices, they are succeeding in providing DDI and network security services on an as-a-service (-aaS) basis. Their BloxOne DDI application, built on their BloxOne cloud-native platform, helps enable IT, professionals, to manage their networks whether they're based on on-prem, cloud-based, or hybrid architectures. BloxOne Threat Defense application leverages the data provided by DDI to monitor network traffic, proactively identify threats, and quickly inform security systems and network managers of breaches, working with the existing security stack to identify and mitigate security threats quickly, automatically, and more efficiently. The BloxOne platform provides a secure, integrated platform for centralizing the management of identity data and services across the network. A recognized industry leader, Infoblox has a 52% market share in the DDI networking market comprised of 8,000 customers, including 59% of the Fortune 1000 and 58% of the Forbes 2000. Kount – Kount’s award-winning, AI-driven fraud prevention empowers digital businesses, online merchants, and payment service providers around the world to protect against payments fraud, new account creation fraud, and account takeover. With Kount, businesses approve more good orders, uncover new revenue streams, improve customer experience and dramatically improve their bottom line all while minimizing fraud management cost and losses. Through Kount’s global network and proprietary technologies in AI and machine learning, combined with flexible policy management, companies frustrate online criminals and bad actors driving them away from their site, their marketplace, and off their network. Kount’s continuously adaptive platform provides certainty for businesses at every digital interaction. Kount’s advances in both proprietary techniques and patented technology include mobile fraud detection, advanced artificial intelligence, multi-layer device fingerprinting, IP proxy detection and geo-location, transaction and custom scoring, global order linking, business intelligence reporting, comprehensive order management, as well as professional and managed services. Kount protects over 6,500 brands today. Mimecast – Mimecast improves the way companies manage confidential, mission-critical business communication and data. The company's mission is to reduce the risks users face from email, and support in reducing the cost and complexity of protecting users by moving the workload to the cloud. The company develops proprietary cloud architecture to deliver comprehensive email security, service continuity, and archiving in a single subscription service. Its goal is to make it easier for people to protect a business in today’s fast-changing security and risk environment. The company expanded its technology portfolio in 2019 through a pair of acquisitions, buying data migration technology provider Simply Migrate to help customers and prospects move to the cloud more quickly, reliably, and inexpensively. Mimecast also purchased email security startup DMARC Analyzer to reduce the time, effort, and cost associated with stopping domain spoofing attacks. Mimecast acquired Segasec earlier this month, a leading provider of digital threat protection. With the acquisition of Segasec, Mimecast can provide brand exploit protection, using machine learning to identify potential hackers at the earliest stages of an attack. The solution also is engineered to provide a way to actively monitor, manage, block, and take down phishing scams or impersonation attempts on the Web. MobileIron – A long-time leader in mobile management solutions, MobileIron is widely recognized by Chief Information Security Officers, CIOs and senior management teams as the de facto standard for unified endpoint management (UEM), mobile application management (MAM), BYOD security, and zero sign-on (ZSO). The company’s UEM platform is strengthened by MobileIron Threat Defense and MobileIron’s Access solution, which allows for zero sign-on authentication. Forrester observes in their latest Wave on Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 that “MobileIron’s recently released authenticator, which enables passwordless authentication to cloud services, is a must for future-state Zero Trust enterprises and speaks to its innovation in this space.” The Wave also illustrates that MobileIron is the most noteworthy vendor as their approach to Zero Trust begins with the device and scales across mobile infrastructures. MobileIron’s product suite also includes a federated policy engine that enables administrators to control and better command the myriad of devices and endpoints that enterprises rely on today. Forrester sees MobileIron as having excellent integration at the platform level, a key determinant of how effective they will be in providing support to enterprises pursuing Zero Trust Security strategies in the future. One Identity – One Identity is differentiating its Identity Manager identity analytics and risk scoring capabilities with greater integration via its connected system modules. The goal of these modules is to provide customers with more flexibility in defining reports that include application-specific content. Identity Manager also has over 30 direct provisioning connectors included in the base package, with good platform coverage, including strong Microsoft and Office 365 support. Additional premium connectors are charged separately. One Identity also has a separate cloud-architected SaaS solution called One Identity Starling. One of Starling’s greatest benefits is its design that allows for it to be used not only by Identity Manager clients, but also by clients of other IGA solutions as a simplified approach to obtain SaaS-based identity analytics, risk intelligence, and cloud provisioning. One Identity and its approach is trusted by customers worldwide, where more than 7,500 organizations worldwide depend on One Identity solutions to manage more than 125 million identities, enhancing their agility and efficiency while securing access to their systems and data – on-prem, cloud, or hybrid. SECURITI.ai - SECURITI.ai is the leader in AI-Powered PrivacyOps, that helps automate all major functions needed for privacy compliance in one place. It enables enterprises to give rights to people on their data, be responsible custodians of people’s data, comply with global privacy regulations like CCPA and bolster their brands. The AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. These include a Personal Data Graph Builder, Robotic Automation for Data Subject Requests, Secure Data Request Portal, Consent Lifecycle Manager, Third-Party Privacy Assessment, Third-Party Privacy Ratings, Privacy Assessment Automation and Breach Management. SECURITI.ai is also featured in the Consent Management section of Bessemer’s Data Privacy Stack shown below and available in Bessemer Venture Partner’s recent publication How data privacy engineering will prevent future data oil spills (10 pp., PDF, no opt-in). Top 10 Cybersecurity Companies To Watch In 2020 SOURCE: BESSEMER VENTURE PARTNERS, HOW DATA PRIVACY ENGINEERING WILL PREVENT FUTURE DATA OIL SPILLS , SEPTEMBER, 2019. (10 PP., PDF, NO OPT-IN). Transmit Security - The Transmit Security Platform provides a solution for managing identity across applications while maintaining security and usability. As criminal threats evolve, online authentication has become reactive and less effective. Many organizations have taken on multiple point solutions to try to stay ahead, deploying new authenticators, risk engines, and fraud tools. In the process, the customer experience has suffered. And with an increasingly complex environment, many enterprises struggle with the ability to rapidly innovate to provide customers with an omnichannel experience that enables them to stay ahead of emerging threats.

Transmit Security – The Transmit Security Platform provides a solution for managing identity across applications while maintaining security and usability. As criminal threats evolve, online authentication has become reactive and less effective. Many organizations have taken on multiple point solutions to try to stay ahead, deploying new authenticators, risk engines, and fraud tools. In the process, the customer experience has suffered. And with an increasingly complex environment, many enterprises struggle with the ability to rapidly innovate to provide customers with an omnichannel experience that enables them to stay ahead of emerging threats.

10 Charts That Will Change Your Perspective Of AI In Security

10 Charts That Will Change Your Perspective Of AI In Security

Rapid advances in AI and machine learning are defining cybersecurity’s future daily. Identities are the new security perimeter and Zero Trust Security frameworks are capitalizing on AI’s insights to thwart breaches in milliseconds. Advances in AI and machine learning are also driving the transformation of endpoint security toward greater accuracy and contextually intelligence.

69% of enterprise executives believe artificial intelligence (AI) will be necessary to respond to cyberattacks with the majority of telecom companies (80%) saying they are counting on AI to help identify threats and thwart attacks according to Capgemini. Gartner predicts $137.4B will be spent on Information Security and Risk Management in 2019, increasing to $175.5B in 2023, reaching a CAGR of 9.1%. Cloud Security, Data Security, and Infrastructure Protection are the fastest-growing areas of security spending through 2023. The following ten charts illustrate the market and technological factors driving the rapid growth of AI in security today:

  • AI shows the greatest potential for fraud detection, malware detection, assigning risk scores to login attempts on networks, and intrusion detection. Supervised and unsupervised machine learning algorithms are proving to be effective in identifying potentially fraudulent online transaction activity. By definition, supervised machine learning algorithms rely on historical data to find patterns not discernible with traditional rule-based approaches to fraud detection. Finding anomalies, interrelationships, and valid links between emerging factors and variables is unsupervised machine learning’s core strength. Combining each is proving to be very effective in identifying anomalous behavior and reducing or restricting access. Kount’s  Omniscore relies on these technologies to provide an AI-driven transaction safety rating. Source: Capgemini Research Institute, Reinventing Cybersecurity with Artificial Intelligence – The new frontier in digital security (28 pp., PDF, no opt-in).
  • 80% of telecommunications executives stated that they believe their organization would not be able to respond to cyberattacks without AI. Across all seven industries studied in a recent Capgemini survey, 69% of all senior executives say they would not be able to respond to a cyberattack without AI. 75% of banking executives realize they’ll need AI to thwart a cyberattack. Interestingly, 59% of Utilities executives, the lowest response to this question on the survey, see AI as essential for battling a cyberattack. Utilities are one of the more vulnerable industries to attacks given their legacy infrastructure. Source: Statistica, Share of organizations that rely on artificial intelligence (AI) for cybersecurity in selected countries as of 2019, by industry
  • 51% of enterprises primarily rely on AI for threat detection, leading prediction, and response. Consistent with the majority of cybersecurity surveys of enterprises’ AI adoption for cybersecurity in 2019, AI is relied the majority of the time for detecting threats. A small percentage of enterprises have progressed past detection to prediction and response, as the graphic below shows. Many of the more interesting AI projects today are in prediction and response, given how the challenges in these areas expand the boundaries of technologies fast. Source: Capgemini Research Institute, Reinventing Cybersecurity with Artificial Intelligence – The new frontier in digital security (28 pp., PDF, no opt-in).
  • Enterprises are relying on AI as the foundation of their security automation frameworks. AI-driven security automation frameworks are designed to flex and support new digital business models across an organization. Existing security automation frameworks can crunch and correlate threat patterns on massive volumes of disparate data, which introduces opportunities for advanced cybersecurity without disrupting business. Using alerts and prescriptive analytics for dynamic policies to address identified risks, enterprises can speed deployment of threat-blocking measures, increasing the agility of security operations. Source: Cognizant, Combating Cybersecurity Challenges with Advanced Analytics (PDF, 24 pp., no opt-in).
  • Cybersecurity leads all other investment categories this year of TD Ameritrade’s Registered Investment Advisors (RIA) Survey. The survey found RIAs are most interested in investment opportunities for their clients in AI-based cybersecurity new ventures. Source: TD Ameritrade Institutional 2019 RIA Sentiment Survey (PDF, 35 pp., no opt-in)
  • 62% of enterprises have adopted and implemented AI to its full potential for cybersecurity, or are still exploring additional uses. AI is gaining adoption in U.S.-based enterprises and is also being recommended by government policy influencers. Just 21% of enterprises have no plans for using AI-based cybersecurity today.  Source: Oracle, Security In the Age Of AI (18 pp., PDF. no opt-in
  • 71% of today’s organizations reporting they spend more on AI and machine learning for cybersecurity than they did two years ago. 26% and 28% of U.S. and Japanese IT professionals believe their organizations could be doing more. Additionally, 84% of respondents believe cyber-criminals are also using AI and ML to launch their attacks. When considered together, these figures indicate a strong belief that AI/ML based cybersecurity is no longer simply nice to have; it’s crucial to stop modern cyberattacks.   Source: Webroot, Knowledge Gaps: AI and Machine Learning in CyberSecurity Perspectives from the U.S. and Japanese IT Professionals (PDF, 9 pp., no opt-in)
  • 73% of enterprises have adopted security products with some form of AI integrated into them. Among enterprises that receive more than 1,000 alerts per day, the percentage that has AI-enabled products in their security infrastructure jumps to 84%. The findings suggest that some decision makers view AI as useful capability in dealing with the flood of alerts that they receive. Source: Osterman Research, The State of AI in Cybersecurity: The Benefits, Limitations and Evolving Questions (PDF, 10 pp., opt-in).
  • AI’s greatest benefit is the increase in the speed of analyzing threats (69%) followed by an acceleration in the containment of infected endpoints/devices and hosts (64%). Because AI reduces the time to respond to cyber exploits organizations can potentially save an average of more than $2.5 million in operating costs. Source: The Value of Artificial Intelligence in Cybersecurity – Sponsored by IBM Security Independently conducted by Ponemon Institute LLC, July 2018.