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Posts tagged ‘generative AI’

Jan 22

Gartner 4Q25: $4.71T AI market proves agentic AI and data readiness are the only race that matters

Created with Perplexity

Only 43% of organizations say their data is ready for AI. Meanwhile, AI Data spending is compounding at 155% annually. That’s six times faster than the infrastructure buildouts grabbing headlines. That disconnect defines the enterprise AI landscape in 2025.

Gartner’s 4Q25 AI Spending Forecast (December 17, 2025) projects $4.71 trillion by 2029. But I’ve been digging through the segment data, and the story isn’t the topline number. Four subsegments within Gartner’s AI Data market are growing between 136% and 178% CAGR. AI Infrastructure? Just 29.25%. The money is following the bottlenecks.

“Nearly everything today, from the way we work to how we make decisions, is directly or indirectly influenced by AI,” says Carlie Idoine, VP Analyst at Gartner. “But it doesn’t deliver value on its own. AI needs to be tightly aligned with data, analytics, and governance to enable intelligent, adaptive decisions and actions across the organization.”

McKinsey’s 2025 State of AI survey (1,993 participants, 105 countries) found 88% of organizations now use AI in at least one business function. But two-thirds remain stuck in pilot mode. Just 6% qualify as “AI high performers,” meaning organizations where more than 5% of EBIT comes from AI. The gap between adoption and value creation is where the real spending story unfolds.

Where the bottlenecks are breaking

Every high-growth segment in the forecast eliminates a constraint that stalls production of AI.

Synthetic data generation addresses the labeled data shortage. You can’t train models without it, and real world data comes with privacy constraints, bias problems, and collection costs that don’t scale. Data governance enforces quality standards because ungoverned data produces ungoverned outputs. Hallucinations, compliance violations, and bias incidents trace directly back to data quality failures. Data integration software connects fragmented sources. Most enterprise data sits across dozens of systems that don’t communicate.

“With AI investment remaining strong this year, a sharper emphasis is being placed on using AI for operational scalability and real-time intelligence,” says Haritha Khandabattu, Senior Director Analyst at Gartner. “This has led to a gradual pivot from generative AI as a central focus toward the foundational enablers that support sustainable AI delivery, such as AI-ready data and AI agents.” Infrastructure enables these capabilities. Data readiness and agentic AI determine whether they generate returns.

The $14.6 billion data readiness bet

Gartner tracks AI Data as a unified market with four subsegments. The aggregate grows from $134.35 million in 2024 to $14.59 billion by 2029. That’s 109x, making it the fastest-growing major category in the forecast.

Synthetic Data Generation: 178.29% CAGR, $40.71M to $6.80B. The fastest-growing subsegment adds $6.76 billion in new spending by 2029. A 167x increase from a small 2024 base. Gartner predicts 60% of data and analytics leaders will encounter failures in managing synthetic data by 2027, which explains why governance spending is accelerating in parallel.

AI Data Governance: 163.75% CAGR, $14.82M to $1.89B. Starting from just $14.82 million in 2024, this subsegment grows 128x by 2029. Legal and compliance teams won’t accept the alternative. When AI systems produce ungoverned outputs, the liability exposure is unacceptable.

AI Data Integration Software: 137.13% CAGR, $71.73M to $5.38B. The largest AI Data subsegment by 2029. Connects fragmented data sources, delivering context that transforms generic models into systems that understand specific business operations.

AI Ready Datasets: 136.16% CAGR, $7.09M to $520.45M. These are prepackaged, curated datasets structured for AI and ML workflows. Think labeled image libraries for computer vision, cleaned financial datasets for forecasting, and domain-specific corpora for fine-tuning LLMs. Organizations buy them to skip the months of data collection, cleaning, and annotation that delay projects. Smallest subsegment by revenue, but 73x growth signals enterprises are willing to pay for time to production shortcuts.

The 2027 crossover: When agents overtake chatbots

Agentic AI: 118.73% CAGR, $15.04B to $752.73B. This is the single most dramatic dollar growth in the forecast. Agentic AI expands from $15 billion to $753 billion by 2029. That’s 50x. Nothing else comes close.

Gartner predicts the crossover will happen in 2027. Chatbots peak at $264.75 billion that year, while Agentic AI surges to $371.40 billion. By 2029, Agentic AI is 3.3x larger ($752.73B vs. $228.50B).

McKinsey’s data reinforces the trajectory: 62% of organizations are experimenting with AI agents, 23% report scaling them in at least one function. But scaling remains limited. Most organizations deploying agents are only doing so in one or two functions, primarily IT service desk and knowledge management.

Organizations building chatbot-only strategies should note that the category dominating 2025 and 2026 is projected to decline after 2027.

The Security Tax on Agentic AI

AI Cybersecurity: 73.90% CAGR, $10.82B to $172.01B. AI agents introduce attack surfaces that traditional security architectures weren’t built for. Gartner’s Hype Cycle for Application Security, 2025 (July 2025) projects that through 2029, over 50% of successful attacks against AI agents will exploit access control issues via direct or indirect prompt injection. The 16x growth in AI Cybersecurity spending reflects enterprises grappling with that exposure.

Production AI deployment requires security architectures designed for agentic systems. That’s a capability most organizations don’t have yet.

Infrastructure: Dominant but decelerating

AI Infrastructure remains the largest absolute spending category: $624.76 billion in 2024, growing to $2.25 trillion by 2029. McKinsey (August 2025) projects hyperscalers alone will spend $300 billion in capex over 2025. Their April 2025 analysis projects $5.2 trillion in data center investment by 2030.

But at 29.25% CAGR, infrastructure grows slower than every other major AI market except Services (26.93%). Market share drops from 54.6% of total AI spending in 2024 to 47.8% by 2029. The buildout is real. Differentiation happens elsewhere.

The 6% problem

Only 6% of organizations qualify as AI high performers despite 88% adoption. McKinsey’s analysis shows high performers are 3x more likely to redesign workflows around AI rather than layering it onto existing processes. They’re also 3x more likely to have committed executive leadership driving AI as a strategic priority.

The 155% CAGR for AI Data reflects organizations investing to close that gap. The 2027 chatbot-to-agent crossover marks the inflection point when autonomous capabilities surpass conversational interfaces in market size.

Gareth Herschel, VP Analyst at Gartner, frames the pressure: “D&A is going from the domain of the few to ubiquity. At the same time, D&A leaders are under pressure not to do more with less, but to do a lot more with a lot more, and that can be even more challenging because the stakes are being raised.”

Where the value accrues

Organizations positioned to capture value from this transformation may not be the ones building the biggest data centers. The Gartner data suggests they’re investing in capabilities that make AI systems work at enterprise scale: data readiness, governance, integration, and security.

AI Data Market (aggregate): 155% CAGR, $134M to $14.6B (109x)

  • Synthetic Data Generation: 178% CAGR, $41M to $6.8B (167x)
  • AI Data Governance: 164% CAGR, $15M to $1.9B (128x)
  • AI Data Integration: 137% CAGR, $72M to $5.4B (75x)
  • AI Ready Datasets: 136% CAGR, $7M to $520M (73x)

Other High-Growth Segments:

  • Agentic AI: 119% CAGR, $15B to $753B (50x)
  • AI Cybersecurity: 74% CAGR, $11B to $172B (16x)
  • AI Infrastructure: 29% CAGR, $625B to $2.25T (4x)

Gartner’s 4Q25 data points to a directional shift: AI spending is moving from infrastructure-first to data and capabilities-first architectures. The organizations treating data readiness as an afterthought are the ones most likely to stay stuck in the 94% that never make it past pilot.

Dec 22

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.

Nov 10

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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

10. Context‑Aware IAM Defines the Future of Access Control Best Slide: Slide 21 – Runtime Context and Adaptive IAM Model The next generation of IAM is contextual, continuous, and AI‑assisted  Convergence, Consolidation, And… . Static permissions are being replaced with adaptive models that evaluate risk in real time — factoring in behavioral biometrics, device posture, and environmental signals. This “runtime context” turns identity from a passive gatekeeper into an active defender capable of making split‑second decisions as threats unfold.

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.

Oct 19

Gartner’s 13 ways GenAI is improving B2B Sales is the roadmap every business needs

Gartner's 13 ways GenAI is improving B2B Sales is the roadmap every business needs

Generative AI (GenAI) ‘s potential for streamlining the most time-consuming processes in B2B sales is just getting started. As businesses increasingly rely on AI to enhance efficiency, automate routine tasks, and personalize customer engagement, GenAI is set to become a critical differentiator in the race for B2B sales and market leadership.

  • B2B sales organizations using GenAI-embedded sales technologies will reduce the time they spend prospecting and preparing for customer meetings by over 50% within two years.
  • Conversational interfaces based on GenAI will gain momentum and further revolutionize B2B selling. In 2028, they will be the driving force behind up to 60% of B2B sales interactions, up from less than 5% in 2023.
  • Centralized GenAI operations teams are also on the way, championed by Chief Revenue Officers (CROs). These teams will focus on integrating AI-driven strategies into sales and revenue operations. 35% of CROs will have GenAI operations teams online and incorporated into their companies’ strategic planning process by 2025.

The goal: find the most likely wins for GenAI in B2B Sales

Gartner’s recent report, 13 Generative AI Use Cases for B2B Sales, provides an analysis of where GenAI is helping improve B2B sales now and in the future.

“Generative artificial intelligence (GenAI) is reshaping the sales technology landscape, offering innovative solutions in areas such as prospecting, sales analytics, forecasting, and sales enablement. Tools infused with GenAI capabilities are embedded in use cases across the sales function, supporting key priorities such as revenue growth, GTM, cost optimization, and risk mitigation,” write the authors of Gartner’s study.

In defining and ranking the most valuable use cases of GenAI in B2B sales, Gartner examined where the technology is being most effectively applied to improve sales operations, increase seller productivity, and fuel future transformation.

The following multidimensional grid defines the use cases by value and feasibility.

Source: Generative AI Use Cases for B2B Sales, Gartner, Inc.

Gartner evaluated each use case for GenAI in B2B sales by scoring them on two key factors: business value and feasibility. The figure below shows the breakout of value and feasibility factors Gartner has used as a framework to rank the 13 use cases: “While we’ve defined the dimensions of value and feasibility according to our research criteria, companies are encouraged to customize these parameters to align with their own business needs,” the report states.

Source: Gartner, Inc. (2024) Generative AI Use Cases for B2B Sales

Mapping GenAI Use Cases Across Business Functions

Gartner also provides a GenAI use-case pipeline as part of their analysis to graphically explain how the 13 AI-driven strategies or use cases are distributed across business functions, including marketing, sales, and customer success.

The goal is to help organizations identify and take action on the use cases that will deliver the most significant potential impact. Gartner advises that use cases that span multiple stages of the pipeline typically deliver greater overall business value, making them strategic targets for investment. Additionally, the pipeline acts as a guide to identifying the relevant stakeholders within the organization, enabling more focused discussions and alignment on AI implementation priorities.

Source: Gartner, Generative AI Use Cases for B2B Sales.

GenAI is redefining the future of B2B Sales

Within the next three years, GenAI will emerge as one of the main factors that differentiate the most efficient and financially successful B2B sales organizations. With CROs creating operations teams to scale AI improvements across every phase of the sales process and sales teams using AI to automate reporting and manually-intensive tasks, GenAI is supposed to revamp the time-consuming work that gets in the way of selling.

Gartner’s analysis highlights that AI-driven strategies will soon dominate, with significant gains in efficiency and customer engagement. The message is clear: for sales organizations looking to stay ahead, embracing GenAI is not optional—it’s essential. Those who act now will position themselves as leaders in the evolving world of B2B sales, while those who hesitate risk being left behind.

 

Oct 6

Top ten insights CEOs need to know about GenAI going into 2025

Top ten insights CEOs need to know about GenAI going into 2025

CEOs and C-level executives, including line-of-business leaders managing enterprises, no longer have time for AI hype—they need actionable plans that deliver measurable results.

Every CEO I know has a Gen AI tech trends deck ready for board meetings. They’re all impatient for results.

Gartner’s 2024 Generative AI Planning Survey, published yesterday, reflects how impatient CEOs and their teams are gaining traction with GenAI pilots and AI initiatives. The survey involved 822 business executives from North America, Europe, and Asia/Pacific across eight corporate functions.

Key insights from the GenAI planning survey include the following:

  • 11.3% to 19.7% cost savings are expected from GenAI, with the lowest in finance and highest in marketing and HR, as predicted by CEOs and C-level leaders.

  • 87% of CEOs/C-suite are driving GenAI adoption in areas like sales and finance, pushing top-down initiatives for implementation.

  • Legal departments: 26% rolling out GenAI for contract review in 6 months; already widely used for legal research and analysis.

  • 19.7% cost savings in marketing driven by GenAI, making it the most impacted department for efficiency gains.

  • 28% of leaders cite technical challenges as the top barrier to GenAI implementation, followed by talent acquisition (26%) and costs (24%).

  • 69% of GenAI-advanced companies focus on upskilling staff, while 64% are creating new AI-specific roles to meet talent needs.

Cutting through the hype: What CEOs need to know about GenAI going into next year

Rhetoric into results is the new mantra of the C-suite going into 2025.

That’s especially the case with GenAI.

Board members are worried they’re about to get lapped or, worse, see their companies become gradually irrelevant by competitors who are more focused on making GenAI pay than they are. The greater the acuity and insight of how to turn GenAI into a competitive strength, the greater the speed at which an enterprise executes and gets solid results. Speed isn’t optional anymore, it’s table stakes to compete.

Just as every business needs to keep challenging itself to find new paths to reinvent itself to make AI a competitive strength, the same holds for working professionals. There has never been a better time to double down on new skills and master AI tools, technologies, and knowledge.

The following are ten insights every CEO needs to know about GenAI going into 2025:

  • Over the next 12-18 months, GenAI will boost productivity by 22.6%, outpacing revenue growth at 15.8% and cost savings at 15.2%. While cost efficiency and revenue gains matter, the most immediate and substantial impact will be on operational efficiency. Gartner predicts that enterprises that prioritize GenAI integration will see significant increases in both workflow optimization and financial performance.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 30% of leaders plan to reduce headcount by 3% to 5% in 2024 due to GenAI-driven automation, with an overall average savings of 4.6%. These reductions will primarily affect roles tied to repetitive or manual tasks as organizations seek to streamline operations. Another 18% anticipate more minor cuts of 1% to 3%, while 14% expect deeper reductions of 8% to 10%, signaling that GenAI’s impact will vary by function. Only 10% foresee no layoffs.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 87% of sales teams are following CEO or C-suite directives to implement GenAI, demonstrating a top-down strategy that prioritizes AI for revenue growth and a more significant competitive advantage. Supply chain (79%) and finance (74%) also see intense executive pressure, indicating that leadership views AI as critical for optimizing operational efficiency and financial management.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 84% of organizations prioritize embedding GenAI into existing applications as the top method for enabling their use cases, with 34% making it their first choice. Customizing existing models (74%) and training custom models (65%) follow, while only 59% opt for stand-alone tools. Enterprises are focusing on integrating GenAI within their current systems to drive efficiency and impact rather than relying on isolated or siloed solutions.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • HR leads GenAI budget allocation at 7.1%, followed closely by customer service (7.0%) and finance (6.9%). Across functions, business leaders plan to allocate 5.4% to 7.1% of their 2024 budgets to GenAI initiatives, including spending on technology licensing and employee deployment costs. Gartner observes that this shows a solid commitment to embedding GenAI across departments, with HR and customer service prioritizing it for operational efficiency and innovation.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 54% of C-level executives prioritize privacy concerns as the top GenAI risk, followed closely by misuse (49%) and job displacement fears (48%). These top concerns highlight the critical need for strong governance and risk management frameworks and plans to ensure ethical, secure AI deployment. CEOs need to step up the pace on this now if they’re going to compete in this dimension of their business in 2025.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • According to 28% of leaders, technical implementation, talent acquisition (26%), and governance issues (25%) are the top three barriers to GenAI adoption. North America struggles more with measuring value (30%), while Europe faces higher cultural resistance (24%). These barriers highlight the need for focused strategies to overcome implementation and talent gaps across regions.

Top ten insights CEOs need to know about GenAI going into 2025

  • 32% of service-centric industries struggle with measuring value from GenAI initiatives, significantly more than asset-centric industries. The top barriers for both include the cost of running AI, technical implementation (32% each), and getting the necessary talent (28%). To excel, enterprises need to address these common challenges and tailor strategies that overcome sector-specific obstacles, including data availability (28% for service-centric industries).

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • Customer service leads GenAI adoption with 40% using real-time speech and text translation, followed by marketing (38% with chatbots and digital humans), sales (34% with generative business intelligence), HR (29% for job descriptions and skills data), supply chain (30% for chatbots and code generation), finance (22% for coding assistance), legal/risk (17% for legal research), and procurement (18% for contract lifecycle management).

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 76% of mature AI organizations actively recruit additional headcount for existing roles to meet GenAI talent needs, significantly more than the 52% of less mature organizations. They also prioritize running AI literacy programs (67%) and upskilling staff with GenAI skills (67%) to ensure their workforce remains competitive. Mature organizations are also more likely to create new roles for GenAI (67%) and establish AI centers of excellence (45%), showing their commitment to both talent acquisition and long-term AI capability development.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

Sep 17

Top Seven Takeaways from Gartner’s 2024 CIO GenAI Survey

Top Seven Takeaways from Gartner's 2024 CIO GenAI Survey

For 87% of CIOs, generative AI (GenAI) represents more than a technological advancement—it’s a career-defining opportunity.

Gartner’s 2024 CIO Generative AI Survey finds that GenAI is gaining momentum with CIOs, with 95% believing in the technology’s significant potential to improve their organizations. A significant obstacle: a gap between CIOs and their C-suite peers — tempers their optimism.

While CIOs recognize AI’s potential to unleash productivity gains and improve customer experiences, only a fraction of the C-suite sees it as an urgent priority. Closing that gap underscores CIOs’ essential role in championing GenAI by committing to excel at learning every aspect of the new technology and how it can deliver long-term value to their organizations.

The top seven takeaways from Gartner’s survey provide CIOs with a roadmap on how to take a practical, pragmatic approach to bridge the gaps across the C-suite and help their organizations get results from their GenAI strategies.

Strategic Insights from Gartner’s 2024 CIO GenAI Survey

Gartner’s latest CIO survey on GenAI provides insights into how IT leaders can capitalize on the technology’s significant impact, from career growth and expertise development to helping CIOs achieve more support across the C-suite. Each takeaway focuses on how CIOs can leverage AI to drive success for themselves and their organizations.

Here are the survey’s seven most insightful takeaways:

  • More CIOs are starting to view GenAI as a career-enhancing opportunity. Eighty-seven percent of CIOs see GenAI as a pivotal career advancement opportunity, with 44% of those proficient in AI strongly affirming this view. GenAI’s rapid adoption in organizations is proving itself a technology capable of delivering productivity gains and is increasingly becoming a skill and expertise essential for career advancement. For CIOs leading AI initiatives, it’s not just about technology—it’s about positioning themselves as visionary leaders qualified to step into more senior positions. To maximize this opportunity, CIOs need to prioritize the development of AI strategies that demonstrate clear, measurable business outcomes. Continuous learning and certification programs are given to any IT professional, especially CIOs, who want to maintain a competitive edge and have their careers capitalize on GenAI’s growth trajectory.

Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • CIOs are more focused than ever on increasing their acumen about GenAI. CIOs are rapidly becoming the in-house experts on AI, with 52% now rating themselves as proficient or advanced, up from 38% nine months ago. This growing expertise is crucial, as 67% of CIOs are tasked with leading AI initiatives, often sharing this responsibility with other C-suite members. Gartner recommends that CIOs deepen their AI knowledge further and foster a culture of AI literacy across their teams to capitalize on this trend. Providing targeted training for IT and business leaders to ensure that AI strategies are fully integrated into broader business goals is quickly becoming table stakes.

Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • Disconnect between CIO optimism and C-suite prioritization. Despite 95% of CIOs believing in the potential for GenAI to deliver value, the survey reveals a disconnect with the C-suite—only 21% of CIOs who consider themselves highly knowledgeable about AI believe their C-suite sees it as a high priority. This gap suggests a need for more effective communication and strategic alignment. CIOs need to focus on translating AI’s potential into language that resonates with the C-suite. Regular briefings and ROI-focused presentations can help bridge this gap and elevate AI as a top priority for all executive leaders.

Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • CIOs are leading the charge in AI implementations. CIOs are increasingly in charge of GenAI initiatives, with 48% of CIOs responding to the survey indicating that they are the main executives responsible for these initiatives. Another 28% are part of the team responsible for developing AI strategy. This central role places CIOs at the forefront of digital transformation, requiring them to be strategic leaders and hands-on practitioners. CIOs need to establish clear governance frameworks and metrics for AI initiatives to ensure success and alignment with broader organizational goals. Additionally, partnering with other C-suite members, such as the CFO and CMO, can help secure the necessary resources and support for AI projects.


Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • Focus on productivity gains. GenAI is proving effective in streamlining operations and improving efficiencies organization-wide, with 74% of CIOs citing productivity as its top business value. AI also improves customer experience (49%) and helps streamline digital transformation (31%). These priorities demonstrate AI’s multifaceted role in modern businesses. Gartner recommends that CIOs integrate AI into crucial or core organizational areas, ensuring that AI initiatives align with organizational objectives and are designed to deliver measurable, scalable outcomes.


Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • Concerns over AI hallucinations. Although GenAI holds great potential, there are significant risks. According to 59% of CIOs, the biggest worry is “hallucinations” or misleading or incorrect outputs. In close succession, 44% and 48% of CIOs express concern about privacy violations and false information spread by malicious attackers. These dangers highlight the importance of solid governance, ongoing oversight, and continued investments in cybersecurity. According to Gartner, CIOs need to prioritize creating AI ethics guidelines and investing in auditing tools. Gartner also notes that reducing these risks will require cultivating a culture of accountability and transparency.


Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • C-Suite engagement in AI is growing but still lags. The survey shows that while C-suite engagement with AI is growing, 42% of CIOs note increased investment in understanding AI, and 53% still consider their peers novices, highlighting a critical need for further education and alignment. CIOs need to take the lead and champion targeted AI education and strategy sessions to close this gap, ensuring AI initiatives are fully supported and integrated into the organization’s strategic goals.

Conclusion

In Gartner’s 2024 CIO Generative AI Survey, GenAI is more than a technological advancement—it’s a strategic imperative for CIOs seeking business transformation and career advancement. GenAI is rapidly becoming a cornerstone of modern enterprise strategy, with 87% of CIOs seeing it as a career-enhancing tool and 95% as a business value driver.

With only 21% of CIOs seeing AI as a high priority for their executive peers, the journey is difficult. 74% of CIOs are focused on productivity gains, but the C-suite is cautious. CIOs must gain AI expertise and lead the way in aligning AI initiatives with organizational goals to mitigate risks like AI hallucinations through robust governance. CIOs can use GenAI to achieve business success and career growth by strategically navigating these dynamics to cement their role as digital visionaries.

Bibliography:

Struckman, C. (2024). Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc. https://www.gartner.com/document/820936  (Client access required).

Sep 15

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

 

Eighty percent of enterprises have increased their investment in GenAI over the past year, with nearly one-quarter (24%) now integrating the technology into their operations, up from just 6% in the previous year.

Capgemini Research Institute’s recent report, Harnessing the value of generative AI: 2nd edition: Top use cases across sectors, highlights enterprises’ accelerating pace of GenAI adoption and growing importance across their operations and industries.

“Generative AI is not just a technological innovation; it’s a catalyst for transformative change across multiple sectors, driving productivity gains, operational efficiency, and strategic shifts in business models,” write the report’s authors. Enterprise leaders’ sentiment underscores the increasing recognition of GenAI as a critical technology for staying competitive in an increasingly turbulent economic environment.

According to the report, GenAI’s rapid adoption across IT and marketing indicates that companies are actively integrating it into their core operations to drive tangible, measurable benefits. Capgemini’s findings highlight the need for a strong data governance framework, strategic talent development, and vigilant cybersecurity to maximize GenAI’s potential as companies scale their initiatives.

How enterprises are maximizing GenAI’s value

Capgemini found ten key ways enterprises are positioning themselves to maximize GenAI’s potential. These strategies demonstrate how all companies can potentially invest in and integrate GenAI to boost growth, efficiency, and innovation across departments and industries.

Investment surge reflects growing confidence in GenAI. 89% of large businesses with annual revenues over $20 billion are leading this investment surge, highlighting GenAI’s significance for future growth. Additionally, 73% of companies with revenues between $1 billion and $5 billion have significantly increased their GenAI budgets, showing that this trend is not limited to the largest companies. This investment trend indicates that many companies believe GenAI can drive enterprise evolution and deliver substantial returns, with many expecting double-digit productivity and customer engagement growth.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

GenAI maturity grows steadily across industries. GenAI implementations have continued to mature across industry sectors over the past year. Up from 6% in 2023, 18% of organizations will fully integrate GenAI into most or all functions in 2024. With 64% and 53% of companies enabling GenAI, high-tech and financial services lead. Retail grew 17%–40% and industrial manufacturing 14%–35%. With 53% and 47% of telecom and energy/utilities adopting GenAI, respectively, progress has been made.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

GenAI’s integration across organizational functions is growing. In one year, GenAI IT adoption rose from 4% to 27% across organizational functions. GenAI is improving enterprise productivity and innovation through this broad integration across sales, marketing, operations, and R&D. Capgemini also found that GenAI is transforming operations and creating value across all business areas.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

Productivity and customer engagement gains. Over the last year, organizations that have implemented GenAI have reported a 7.8% increase in productivity and a 6.7% increase in customer engagement. These tangible benefits demonstrate GenAI’s ability to provide real, measurable value to enterprises. Early adopters report significant improvements in key performance metrics, highlighting the strategic importance of incorporating GenAI into business operations.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

Small Language Models (SLM) are gaining momentum. 24% of organizations have implemented SLMs, and 56% plan to do so within three years. These models are cheaper and less computationally intensive than larger AI models, so many companies are piloting and eventually moving them into production. SLMs excel in industry-specific applications, allowing businesses to harness AI’s potential without the infrastructure and resource demands of larger models. SLMs are becoming a good option for companies trying to compete in an AI-driven market as they seek efficient and scalable AI solutions.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

GenAI is enabling enterprises to advance from chatbots to autonomous multi-agent systems. GenAI is helping 62% of organizations upgrade from chatbots to AI agents that autonomously manage complex goals. 48% of users use multi-agent systems, where AI agents operate independently in changing environments. As businesses automate and optimize complex processes with these systems, decision-making and operational efficiency improve across industries. AI has evolved from simple user interactions to complex, agentic use cases, as shown in the image.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

GenAI agents are accelerating the shift to autonomous operations. GenAI agents are increasingly used in enterprise automation, with 82% of companies planning to implement them in 1–3 years. These agents are evolving from supportive tools to autonomous entities that can perform complex tasks without interaction. This shift is significant, with 71% of organizations expecting AI agents to automate workflows and 64% expecting customer service and productivity improvements. AI agents are not just efficient; they are a radical shift toward fully autonomous, AI-driven operations that will transform enterprise productivity and strategic decision-making.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

GenAI is forcing major business strategy shifts. 54% of companies expect GenAI to improve their strategies, up from 39% in 2023. 40% of companies are revising their business models to stay competitive as GenAI becomes more important. As GenAI becomes more important, 74% of businesses believe they must use it to grow revenue and stay ahead of the competition.

Capgemini report finds top 10 ways enterprises are harnessing the value of GenAI

Strengthening data foundations is crucial for GenAI’s success. More than 60% of companies realize GenAI’s potential depends on solid data foundations. Only 51% have documented data integration processes and 46% have AI data management policies. Even enterprises that have adopted GenAI still struggle to make the most of all their external data sources. Capgemini makes it clear that for GenAI initiatives to succeed, companies need scalable, secure data infrastructure.

Tighten AI controls or risk trust and compliance. Ethics in AI deployment is a priority for 57% of organizations, which recognize the need for control mechanisms that can flex and adapt as their business goals change. While 46% have clear AI governance frameworks, 73% agree that human oversight is necessary to validate AI-driven decisions. Without strong governance, bias, and accountability issues could counteract GenAI’s benefits, so organizations must act now.

Conclusion

With 80% of organizations increasing their investment and almost a quarter already including it in their operations, GenAI is fast changing how businesses run. This general acceptance emphasizes GenAI’s importance as a main engine of efficiency and creativity, providing real advantages in customer interaction and output.

Organizations are not only embracing GenAI as AI agents and Small Language Models (SLMs) acquire traction; they are also including GenAI in their basic strategies. Those who match GenAI with their business models, make investments in solid data foundations, and develop the knowledge required to maximize its possibilities will inherit the future. They will lead in the era of artificial intelligence by doing this, establishing new benchmarks for operational excellence and creativity.

Mar 10

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).

Feb 11

Top 10 Insights From Forrester’s State of Generative AI in 2024 Report

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Created with DALL-E

Over 90% of enterprise AI decision-makers have concrete plans to adopt generative AI (gen AI) for internal and customer-facing use cases. Nearly half, 47%, say productivity gains are the primary goal. Those anticipated gains are closely followed by greater innovation (44%) and cost efficiency (41%). One in three, or 34%, expect AI to deliver greater revenue growth.

Productivity gains are happening faster than enterprises can track because Shadow AI is growing quicker than many IT and security teams anticipated. OpenAI says their enterprise adoption is soaring, with over 80% of Fortune 500 companies’ workers and departments having accounts.

Enterprise workers are achieving a 40% performance boost thanks to ChatGPT based on a recent Harvard study. A second study from MIT discovered that ChatGPT reduced skill inequalities and accelerated document creation times while enabling enterprise workers to be more efficient with their time. Seventy percent haven’t told their bosses about it.

Forrester: A Wave Of Disruption Is Coming

Forrester’s recent report, The State of Generative AI, 2024, warns enterprises not to discount the impact of generative AI on their operations and to start planning for greater experimentation, governance, and security now.

Get ready for the challenges of defining and managing bring your own AI (BYOAI) as workers are inventing and adopting gen AI tools and apps faster than IT or security can keep up. Forrester advises that enterprises need to have forward-thinking governance and security guardrails in place before launching their AI-based apps.

With nearly every enterprise app and platform integrating gen AI into its feature set, it’s up to IT, security, and senior management to have an AI plan that can adapt and flex fast to the fast-growing feature set gen AI is delivering.

Enterprise AI leaders also need to define where they stand on the controversial and complex state of model training data. Forrester says that questions regarding the quality of training data using copyright material, model and data bias, and frequent “hallucinations” by models.

“In 2024, as organizations embrace the generative AI (genAI) imperative, governance and accountability will be a critical component to ensure that AI usage is ethical and does not violate regulatory requirements,” writes Forrester in their cybersecurity predictions late last year. “This will enable organizations to safely transition from experimentation to implementation of new AI-based technologies,” the report continues.

Top 10 Insights From Forrester’s State of Generative AI

The ten most valuable insights from Forrester’s State of Generative AI report provide a comprehensive overview of the current and future landscape of generative AI. Noteworthy for its balance between opportunities and risks, the report explains the hurdles in front of enterprises looking to gain value from gen AI now and in the future.

Here are the top 10 insights from the report:

Gen AI shows strong potential to improve and scale enterprise operations. Forrester is optimistic regarding the potential of gen AI to increase productivity and deliver measurable business value. “Forrester expects that gen AI will add convenience to and remove friction from a variety of experiences, reshape jobs in ways we are only beginning to contemplate and disrupt organizations and industries,” writes Forrester’s research team in the report. The report explains that there are three broad tiers of generative AI suppliers, further supporting the market’s expansion and growth.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

 

Large Language Models will continue to dominate the gen AI narrative. Large language models (LLMs), including Anthropic, Google, Meta, and OpenAI’s GPT series, will continue to dominate the gen AI landscape. Forrester notes that significant data and infrastructure requirements make the task of creating and maintaining an LLM difficult for companies considering competing in the market. Open-source LLMs are redefining the market, a point Forrester touches on briefly.

Gen AI is becoming part of planning cycles in enterprises: Forrester found that over 90% of global enterprise AI decision-makers have definite plans to implement generative AI. Internal use cases are dominating the planning cycles of enterprise AI leaders today.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

Overcoming technical skills shortages and integration challenges stand in the way of achieving benefits. A third of enterprise AI leaders say that lack of technical skills in their organizations is the single greatest roadblock to their gaining the benefits they’re looking for from gen AI. Twenty-eight percent say they’re having difficulty integrating gen AI into their existing tech stacks and infrastructure. The potential to gain significant benefits from gen AI motivates enterprise AI leaders to look for new ways to overcome technical skills shortages and find new ways to integrate gen AI into their infrastructure.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

Ethical and safe gen AI use will require new cybersecurity and governance approaches. Enterprises need to decide how they approach the most challenging and controversial aspects of LLMs, gen AI, and the future of AI at scale in their companies now rather than later. The core message of Forrester’s report is for enterprises not to procrastinate but to start making plans now for their stance on the issues of model bias, data security, regulatory compliance, and ethics of model training.

Weaponized LLMs are a fact of life for every enterprise looking to adopt these technologies today. There’s also the growing threat of intellectual property and confidential data being accidentally shared with LLMs via ChatGPT and comparable chatbots. The intensity cybersecurity providers are putting behind this problem makes it one of the fastest evolving areas in the industry today.

While not mentioned by Forrester in their report, these vendors are defining the state of the art when it comes to protecting confidential data being entered into LLMs. Cisco, Ericom Security by Cradlepoint’s Generative AI isolation, Menlo Security, Nightfall AI,  Wiz, and Zscaler have all developed and launched solutions to reduce the threat of confidential data making it into LLMs via chatbots.

The use of a virtual browser that is separate from an organization’s network environment in the Ericom Cloud distinguishes Ericom’s Generative AI Isolation. Data loss protection, sharing, and access policy controls are applied in the cloud to prevent confidential data, PII, or other sensitive information from being submitted to the LLM and potentially exposed.

“Generative AI websites provide unparalleled productivity enhancements, but organizations must be proactive in addressing the associated risks,” said Gerry Grealish, Vice President of Marketing Ericom Cybersecurity Unit of Cradlepoint. “Our Generative AI Isolation solution empowers businesses to attain the perfect balance, harnessing the potential of generative AI while safeguarding against data loss, malware threats, and legal and compliance challenges.”

Early adopters are implementing gen AI in a wide variety of use cases, ranging from operations to customer engagement and product development. Forrester notes that they’re seeing organizations use knowledge management bots to accelerate workflows, automate tasks, generate new ideas, and drive innovation across a broad base of use cases. Early adopters are also piloting gen AI for diverse use cases across operations, customer engagement, and product development. Forester emphasizes that for external use cases, they’re seeing enterprises adopt a main-in-the-middle workflow to strengthen model training with human intelligence – and avert potential errors in model response.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

Internal use cases precede external use cases as enterprises look to gain expertise in controlled environments. Companies will initially focus on internal use cases for generative AI to refine their models before slowly expanding to customer-facing applications, employing heavy human-in-the-loop management. Forrester is seeing gen AI being used internally to drive employee productivity and workflow optimization gains first. The top three use cases of employee productivity, knowledge management, and software development are all focused on internal improvements.

Legal and intellectual property uncertainty will continue to surround gen AI. Forrester implies there’s going to be an increasingly complex, controversial legal landscape regarding the data models are trained on, especially when it comes to copyrighted content.

Privacy and regulatory concerns are going to continue influencing adoption. Forrester is seeing enterprises in heavily regulated industries exercising extreme caution to protect company and customer data, with some even banning tools like ChatGPT over concerns about data protection and regulatory backlash.

Enterprises need to get a sense of urgency about preparing for gen AI governance and experimentation. Having a clear vision of how they’re going to adopt gen AI is essential if enterprises are going to succeed in governing these new technologies at scale. The combination of growing and recruiting in-house skills, having a solid plan for BYOAI, and defining guardrails for internal use cases are all needed to avoid being blindsided by risks.