Gartner says frontier AI turns patch speed into a vanity metric. Spending bars show the exposure-focused categories in Gartner’s 3Q26 security forecast. Click any chart to open it full size. Sources: Gartner (G00859901, Aug. 6, 2026; G00862059, Sept. 24, 2026), analysis by softwarestrategiesblog.com.
Gartner’s new research on frontier AI vulnerability management says the patch-speed metric most security teams report to their boards no longer measures anything useful.
Gartner analysts Rob McMillan and Alex Michaels put it bluntly in a research note published August 6: “Measuring ‘how fast we patch’ is a vanity metric; the only metric that matters now is ‘tolerable exposure time.'”
The note covers one of Gartner’s nine top cybersecurity trends for 2026: frontier AI models transforming vulnerability management. Its central argument runs against most vendor messaging. The real shock from frontier AI is not faster attackers. It is the volume of vulnerabilities that vendors and open-source projects will now find in their own code, and the flood of urgent updates that follows.
Gartner calls it a supply side shock, one that “permanently breaks traditional volume-based patching processes.”
The bars in the hero chart show 2026 and 2030 end-user spending for four exposure-focused categories. Six tiles underneath summarize the note’s core findings.
Why frontier AI breaks volume-based vulnerability management
Gartner is direct about where the pressure comes from. Frontier models can compress attacker cycle times by automating reconnaissance and payload iteration, the analysts write, but “attackers have historically always been faster than defenders.”
The change is on the supply side. As vendors and open-source projects use AI to uncover latent flaws, organizations “will face a greatly heightened volume of urgent security updates.” The note expects those updates to arrive in multiple waves, timed in large part to when new security-focused frontier models become available to IT suppliers.
The exploit window is shrinking at the same time. Gartner says the gap between vulnerability disclosure and active exploitation “has collapsed to minutes because AI models can autonomously reverse-engineer patches into exploits.”
Gartner’s four core insights:
Traditional vulnerability management was already misaligned with attacker timelines before AI. Without change, the gap is now unbridgeable.
Mandates to “patch everything faster” move risk from successful attacks to operational outages and increase self-inflicted downtime.
The bottleneck is testing and change management, not patching capacity. Each wave of AI-discovered vulnerabilities adds complexity and strains resources.
Regulatory pressure for rapid patching can conflict with operational reality. Storytelling about real business impact becomes a necessary skill.
“Patch everything faster” moves the risk, it doesn’t remove it
The note treats blanket speed mandates as a risk transfer. Unrealistic demands to patch everything immediately “merely transfer the risk from malicious actors to insufficient IT testing, increasing the likelihood of self-inflicted downtime.”
Gartner frames enterprise risk management as an explicit choice between breach risk and outage risk. The CISO, infrastructure and operations leaders and other stakeholders need business leaders to formally accept the relative risks of patching-related downtime against attack-related downtime.
Faster patching still helps at the margins. The note says the gains are capped by maintenance windows, the need for bespoke fixes in complex software stacks and other constraints.
From volume SLAs to exposure SLAs
Gartner’s replacement is a shift from volume-based patching service-level agreements to exposure-based ones.
What Gartner says breaks under AI-accelerated vulnerability discovery, and what replaces it. Source: Gartner (G00859901, Aug. 6, 2026), layout by softwarestrategiesblog.com.
Static vulnerability characteristics, including CVSS scores and scanning results, are “still necessary, but it is no longer sufficient for prioritization of remedies,” the note says. Prioritization must rest on real exploitability and business context.
Gartner wants the most urgent vulnerabilities, “not necessarily the highest impact,” first in the queue, and mitigated within the organization’s maximum tolerable exposure time.
Accountability moves too. Product and platform teams are held to their exposure limits, with the flexibility to use virtual patching or network isolation when change management blocks an immediate code fix.
CTEM becomes the operating model
Gartner tells organizations to abandon volume-based patching and adopt continuous threat exposure management, or CTEM. Its five stages run from scoping and discovery through prioritization, validation and mobilization.
Gartner’s CTEM cycle with stage notes drawn from the frontier AI research note. Source: Gartner (G00859901, Aug. 6, 2026), analysis by softwarestrategiesblog.com.
The note warns that “a failure to shift to a CTEM approach will result in continued patch deferral and therefore a slow but continuing escalation in risk profile.” Update complexity, and the time and collaboration needed to remediate, is likely to rise with each wave.
Gartner’s broader information security forecast points the same direction. Its 3Q26 report expects organizations to shift from reactive defense toward CTEM, with AI assistants automating event triage, false-positive reduction and code remediation.
The spending signal in Gartner’s security forecast
The categories that support exposure-based prioritization grow faster than the security market overall. Gartner’s 3Q26 forecast puts total information security spending at $247.5 billion in 2026 and $372.8 billion by 2030, a 10.8% CAGR in constant currency from 2025.
Category
2026
2030
2025-2030 CAGR
Threat intelligence
$3.1B
$6.1B
19.0%
Network detection and response
$2.6B
$4.1B
12.4%
Vulnerability assessment
$4.1B
$6.4B
12.0%
Managed security operations
$15.6B
$22.7B
+$7.0B added
Total information security
$247.5B
$372.8B
10.8%
End-user spending in current U.S. dollars; CAGRs in constant currency. Source: Gartner G00862059 (September 2026).
The note uses the AI-driven update surge to force a decision most organizations defer. Technical debt “generally falls into the ‘we will take care of it later’ bucket,” the analysts write. “‘Later’ must be ‘now.'”
CISOs guide the prioritization. CIOs, enterprise architecture and I&O teams have to execute the remediation in the short to medium term. Technical debt also appears separately in Gartner’s 2026 trends list, where it undermines organizational AI ambitions.
Use agentic application security testing selectively
Gartner recommends agentic application security testing, or AAST, for mission-critical applications. AAST can uncover business-logic vulnerabilities and multistep exploits by using context windows to reason through application logic.
The note pairs its reachability analysis, vulnerability prioritization and automated code remediation as the way to keep pace with AI-driven discovery volume.
There is a budget catch. Token consumption “is likely to drive an increase in application security budgets that many organizations will struggle to absorb under current assumptions.” Gartner’s advice is to use AAST selectively now and plan for the budget impact later.
Regulators want counts, CISOs need a story
Gartner says regulators, including the ECB and ESRB, already demand mitigation plans for systemic cyber risks caused by AI. One Gartner client reported pressure from a regulator to address a set number of vulnerabilities within 30 days.
The analysts read that as regulators not always understanding that a more surgical approach is sometimes needed “in order that one problem isn’t substituted for a worse problem.” In the short term, organizations may have to comply with both approaches in parallel.
Gartner expects regulation of AI in critical business processes to tighten. Third-party contracts will likely need vendors to disclose AI model usage and set contingencies for provider outages. Some frontier models may also face export controls or tighter access restrictions. The note cites Anthropic’s Fable 5 and Mythos 5 in 2026 as examples and advises building model-independent roadmaps.
Board talking points Gartner gives CISOs
Gartner’s Figure 1 gives CISOs three talking points for boards worried about Mythos, Daybreak and frontier AI risk:
Foundational controls. Threat actors must still chain attacks. Core controls still provide adequate protection against advanced threats.
Prioritization. A vulnerability does not equal exploitability. Environmental constraints, required privileges and mitigating controls make many flaws impractical to exploit.
Accelerator. Defensive AI scales the defender’s advantage through automated code analysis, threat intelligence and incident response.
The strategic shift, in Gartner’s words, is from asking “how fast do we patch?” to asking “what is our tolerance for remaining exposed to a known vulnerability?”
Where this sits in Gartner’s 2026 trends
Gartner groups its top cybersecurity trends for 2026 into three themes: secure new frontiers, transform governance and normalize AI adoption. Frontier AI and vulnerability management sits under normalizing AI adoption, alongside AI-driven SOC solutions and the breakdown of traditional security awareness tactics.
Gartner’s top cybersecurity trends for 2026 by theme. Source: Gartner (G00859901, Aug. 6, 2026), layout by softwarestrategiesblog.com.
What security leaders should do now
Retire volume-based patch SLAs. Replace them with exposure-based SLAs tied to maximum tolerable exposure time, and adopt CTEM.
Get formal risk acceptance. Have business leaders sign off on the tradeoff between patch-related downtime and attack-related downtime.
Fund testing and change management. That is the bottleneck Gartner identifies, not patch deployment.
Pay down technical debt now. Each AI-driven update wave makes legacy remediation harder.
Pilot AAST on mission-critical apps. Budget for token costs before scaling it.
Build model-independent AI roadmaps. Plan for export controls, access limits and provider outages.
Frequently asked questions
What does Gartner say about frontier AI and vulnerability management? Gartner says frontier AI is driving an unprecedented volume of vulnerability discoveries that makes volume-driven patching obsolete. It recommends exposure-based SLAs and continuous threat exposure management.
What is tolerable exposure time? Gartner defines the meaningful metric as how long critical vulnerabilities remain unmitigated, measured against the organization’s maximum tolerable exposure time.
Why not just patch faster? Gartner says blanket faster-patching mandates shift risk from attacks to self-inflicted outages, because testing and change management are the real bottleneck.
What is AAST? Agentic application security testing uses AI agents to find business-logic flaws and multistep exploits. Gartner recommends using it selectively because token consumption raises application security costs.
How I built this analysis
Quotes and recommendations come from Gartner’s research note G00859901, published August 6, 2026, as part of its Top Trends in Cybersecurity, 2H26 research. Category spending and CAGRs come from Gartner’s 3Q26 information security forecast (G00862059). The pairing of the two documents, the comparison table and the CTEM stage notes are my analysis.
Security spending climbs to $372.8B by 2030, and post-quantum firewall refreshes drew the only upgrade. Click any chart to open it full size. Source: Gartner (G00862059, Sept. 24, 2026), analysis by softwarestrategiesblog.com.
The 3Q26 Gartner information security forecast raised exactly one growth rate.
Gartner now projects firewall equipment spending to grow 13.4% in 2027 in constant currency, up from the 7.8% in its June forecast. Network security equipment overall rises to 12.8% from 8.7%. Post-quantum cryptography (PQC) is the cause. Many installed firewalls can’t run the new algorithms, which forces early replacement.
Every other business category in the 41-category forecast kept the constant-currency outlook it had 91 days earlier.
Published September 24, the forecast puts worldwide end-user spending at $247.5 billion in 2026, up 13.6% in current U.S. dollars and 12.7% in constant currency.
Spending reaches $372.8 billion by 2030. Gartner frames that as $373 billion and a 10.8% compound annual growth rate in constant currency from 2025 through 2030.
I built this analysis from Gartner’s 3Q26 report (G00862059), the full detailed dataset of 13,489 rows covering 47 countries, 9 regions, 41 categories and 7 years, and a line-by-line comparison against the 2Q26 file Gartner released in June (G00855892).
Each bar in the hero chart stacks four parts of Gartner’s forecast in current U.S. dollars. Navy is business security software, mid-blue is security services, sky blue is network security and light blue is consumer security software. Bold figures above the bars give each year’s total, with Gartner’s constant-currency growth rate in italics.
Six tiles underneath carry the 2026 and 2030 totals, the $125.4 billion in new spending between 2026 and 2030, the 2030 firewall revision in constant currency, the change in Gartner’s 2027 firewall growth forecast and the securing AI trajectory.
Both the 56% software share and the $80.5 billion software tile include consumer security software.
Gartner information security forecast puts 2026 at $247.5B and 2030 at $372.8B
Gartner splits the market into security software, security services and network security. Software keeps gaining share in every year of the forecast.
Each column in the chart below adds to 100% of total spending. Navy is security software, including consumer. Mid-blue is security services and sky blue is network security.
A panel on the right lists each market’s 2024 and 2030 spending and share. I calculated the shares from Gartner’s current-dollar figures.
Share of worldwide information security spending by market, 2024 to 2030, current U.S. dollars. Data from Gartner G00862059 (September 2026). Shares calculated by softwarestrategiesblog.com.
Total market 2026. $247.5 billion, up $29.7 billion from $217.7 billion in 2025.
Security software 2026. $126.9 billion including $9.0 billion of consumer security software. Software reaches $207.4 billion by 2030, 55.6% of all spending, up from 49.6% in 2024.
Security services 2026. $93.5 billion. Services reach $125.4 billion by 2030, but their share falls from 39.3% in 2024 to 33.6%. Constant-currency CAGR is 7.5%, the slowest of the three markets.
Network security 2026. $27.0 billion, growing 15.0% in constant currency. It reaches $40.0 billion by 2030. Gartner raised the 2025 to 2030 CAGR for this market to 10.9%, up from 9.8% in 2Q26.
2026 to 2030 net new spending. $125.4 billion. Security software captures $80.5 billion of it, or 64%. Services add $31.9 billion. Network security adds $13.0 billion.
Gartner’s near-term call is unchanged from June. Growth slows to 11.2% in 2027 in constant currency, then decelerates to 9.6% by 2030.
Gartner names security service edge (SSE), cloud-native application protection platforms (CNAPPs), cloud security posture management, cloud access security brokers, web application firewalls, encryption and enterprise data loss prevention as the areas where 2027 budgets will grow.
It also expects AI trust, risk and security management (AI TRiSM) adoption to rise as generative AI use widens data, application and governance risk.
Post-quantum firewall refreshes drew the only growth upgrade
Gartner’s revision table compares 3Q26 against 2Q26 for all 11 subsegments. Ten of them show 0.0% growth-rate change in every year from 2026 through 2030. Network security equipment is the exception, at +4.1 points in 2027, +1.1 in 2028, +0.4 in 2029 and -0.2 in 2030.
I ran the same comparison across all 41 categories in the detailed files. In constant currency, firewall equipment is the only category Gartner raised.
It gains $1.08 billion in 2027, $1.50 billion in 2028, $1.77 billion in 2029 and $1.84 billion in 2030. The other 40 categories, including consumer security software, match the June file to the dollar in constant currency.
In the chart below, each bar is the firewall equipment increase in constant currency. Because no other category moved, the bars are also the net change for the whole market. The total is unchanged in 2025 and 2026 and turns positive in 2027, when the firewall upgrade starts.
3Q26 vs. 2Q26 revisions by year in constant currency. Firewall equipment is the only category Gartner raised; the other 40 are unchanged. Data from Gartner G00862059 and G00855892. Revision math by softwarestrategiesblog.com.
Gartner states the cause directly. “Postquantum cryptography (PQC) requirements will drive premature hardware refreshes, initially among government, financial and defense organizations, due to the inability of many existing firewalls to support the processing demands and crypto-agility required through software or firmware updates,” the report says.
Gartner’s timing is specific. The report says “selected products may support algorithms such as FIPS 203/ML-KEM by late 2026.” Broader vendor availability follows in 2027. By 2028, Gartner expects every major firewall vendor to offer PQC-capable platforms.
Gartner expects at least 20% of customers in government, financial services and defense to upgrade in 2027, rising to more than 30% in 2028.
Firewall equipment spending and year-over-year growth, 2Q26 vs. 3Q26 forecasts, constant currency. Data from Gartner G00862059 and G00855892. Chart by softwarestrategiesblog.com.
In the top panel, the chart compares firewall equipment spending in Gartner’s 2Q26 forecast (light blue) with 3Q26 (sky blue), in constant currency. Revised values carry dark-blue labels and the 2027 and 2030 increases are marked above the bars.
Year-over-year growth sits in the bottom panel, with June’s forecast dashed and September’s solid. Both lines match through 2026, split in 2027 and converge by 2030.
That shift shows up in one year. In June, Gartner expected firewall equipment growth to fall from 16.1% in 2026 to 7.8% in 2027. Now 2027 growth holds at 13.4%.
Gartner’s revision lifts the 2027 firewall market from $20.8 billion to $21.9 billion in constant currency, and the 2030 market from $25.7 billion to $27.6 billion.
In current dollars firewall equipment reaches $28.6 billion by 2030, still the largest network security category by a wide margin.
Every region gets the upgrade at nearly the same rate. Each region’s 2030 firewall forecast rose between 6.9% and 7.8%. North America takes $834 million of the $1.84 billion. Europe takes $414 million. Together they account for 68%.
Each bar in the next chart is one region’s 2030 firewall revision in constant currency. The label shows the dollar increase, that region’s share of the $1.84 billion total and its revised 2030 firewall market. Sky-blue bars mark North America and Europe. Lighter bars are the other seven regions.
2030 firewall equipment revision by region, 3Q26 vs. 2Q26, constant currency. Data from Gartner G00862059 and G00855892. Revision math by softwarestrategiesblog.com.
Why a firmware update will not close the gap
Gartner’s argument rests on hardware. Many installed firewalls cannot meet PQC processing and crypto-agility demands through software or firmware updates. The engineering behind that is straightforward. ML-KEM public keys and ciphertexts are larger than the elliptic-curve exchanges they replace, and hybrid key exchange runs both algorithms in the same handshake.
A firewall that inspects encrypted traffic at line rate has to absorb that overhead on every session.
Federal policy points the same way. The National Security Agency’s CNSA 2.0 guidance says traditional networking equipment such as VPNs and routers should “support and prefer CNSA 2.0 by 2026, and exclusively use CNSA 2.0 by 2030.”
According to Keyfactor’s summary of the federal timeline, new National Security System acquisitions are expected to be CNSA 2.0-compliant by default from January 1, 2027, and NIST IR 8547 proposes deprecating RSA, ECDSA, EdDSA and Diffie-Hellman at the 112-bit security level after 2030, with disallowance in 2035.
Vendor roadmaps line up with Gartner’s 2027 inflection. Cisco’s Secure Firewall PQC roadmap targets ML-KEM support in Secure Firewall Threat Defense 10.5 and ASA 9.25 for general availability in late 2026.
ML-DSA signature support is planned for FTD/ASA 11.0 in the second half of 2027, and SLH-DSA support is also planned for 11.0.
Gartner names the sectors with procurement mandates first. That is why the revision lands in 2027 and fades by 2030. Gartner models the refresh as a pull-forward, with 2030 growth now slightly below the June forecast at 6.8% versus 7.0%.
After two increases, the 2026 number dips
I have tracked Gartner’s 2026 security number through four quarterly updates. The 4Q25 update projected $244.2 billion. 1Q26 raised it to $246.2 billion. 2Q26 raised it again to $248.2 billion. 3Q26 is the first update in that run to come in lower, at $247.5 billion.
Gartner’s 2026 worldwide information security spending as published in each quarterly update, current U.S. dollars. Data from Gartner 4Q25, 1Q26, 2Q26 (G00855892) and 3Q26 (G00862059) forecasts. The y-axis starts at $240 billion to make the revisions visible.
Each bar in the chart above is the 2026 total as published in one quarterly update. The labels inside the bars show the change from the previous update, at +$2.0 billion, +$2.0 billion and -$0.8 billion.
An axis starting at $240 billion keeps the revisions visible. All four estimates sit within 2% of each other.
The entire $788 million drop is currency, not lower demand. Gartner’s revision table puts the 2026 change at -$788 million in current dollars, with 0.0% change in every 2026 growth rate. In the detailed files, the 2026 total is unchanged in constant currency.
Japan shows the currency effect most clearly. Its 2030 forecast is $1.37 billion lower in current dollars than in June, yet $49 million higher in constant currency, all of it from the firewall increase.
Gartner’s notes flag exchange-rate volatility, Strait of Hormuz disruption expected to continue into 2027, energy prices more than 50% above pre-war levels and the risk that inflation and rising interest rates erode business confidence.
Gartner expects the conflict’s main near-term effect on IT spending to be a rebalancing of sourcing, vendor relationships and regional exposure rather than a material cut.
Where the $125.4 billion in new spending goes
Growth rates show where momentum is. Dollar additions show where budgets actually move. Fifteen of the 41 categories capture 76% of all new spending between 2026 and 2030.
Bars in the next chart show the dollars each of the 15 largest categories adds between 2026 and 2030, colored by market. The indigo line, read on the right axis, is the cumulative share of the $125.4 billion total.
It reaches 15% with the first category, 46% after five, 65% after ten and 76% after fifteen.
Net new spending added between 2026 and 2030 by category, current U.S. dollars, with cumulative share. Data from Gartner G00862059. Dollar additions and shares calculated by softwarestrategiesblog.com.
Other security software, including securing AI. +$19.2 billion, from $18.3 billion to $37.5 billion. The largest single dollar gain in the forecast.
Cloud security posture management. +$9.8 billion, from $6.3 billion to $16.1 billion.
Firewall equipment. +$8.8 billion, from $19.7 billion to $28.6 billion. Post-quantum refreshes make firewalls the fourth-largest source of new dollars, ahead of cloud workload protection.
Cloud workload protection platforms. +$8.2 billion, from $7.5 billion to $15.7 billion.
Managed security operations. +$7.0 billion, from $15.6 billion to $22.7 billion. The largest services gain.
Five categories alone account for $57.8 billion, or 46% of new spending. Three of them sit in cloud security or in other security software, where Gartner counts securing AI. Endpoint protection and the firewall, a category many security leaders had written off as a replacement-cycle business, make up the other two.
The 10 fastest-growing categories through 2030
Ranked by 2025 to 2030 CAGR in constant currency, cloud security takes the top three spots. Gartner’s cloud security subsegment grows from $16.6 billion in 2026 to $38.4 billion by 2030, a 24.1% CAGR and the fastest of the 11 subsegments.
In the chart, bar length is each category’s 2025 to 2030 CAGR in constant currency. The label gives the CAGR and the category’s 2026 and 2030 market size in current dollars.
Navy marks security software and sky blue marks network security. The dashed line is the 10.8% market CAGR, so every bar crosses it by at least 1.2 points.
Top 10 of 41 categories by 2025-2030 CAGR in constant currency, with 2026 and 2030 market sizes in current U.S. dollars. Data from Gartner G00862059. Ranking by softwarestrategiesblog.com.
Cloud security posture management. 27.6% CAGR. $6.3 billion in 2026 to $16.1 billion in 2030.
Cloud access security brokers. 24.3%. $2.8 billion to $6.5 billion.
Cloud workload protection platforms. 21.0%. $7.5 billion to $15.7 billion.
Zero trust network access. 20.9%. $3.0 billion to $6.4 billion. The fastest-growing network security category.
Threat intelligence. 19.0%. $3.1 billion to $6.1 billion.
Consent and preference management. 18.6%. $1.0 billion to $2.0 billion.
Other security software, including securing AI. 18.5%. $18.3 billion to $37.5 billion.
Network detection and response. 12.4%. $2.6 billion to $4.1 billion.
Subject rights request automation. 12.3%. $1.5 billion to $2.3 billion.
Vulnerability assessment. 12.0%. $4.1 billion to $6.4 billion.
Gartner’s own opportunity map plots the 11 subsegments on two axes. The horizontal axis is the 2025 to 2030 CAGR. The vertical axis is dollars added over the same period. Bubble size is the 2030 market. The dashed vertical line marks the overall 10.8% CAGR.
Cloud security and other security software sit alone on the right, the only two subsegments growing faster than 15%. Infrastructure protection is the largest subsegment at $62.7 billion by 2030 and adds the most dollars, about $26 billion, while growing at the market average.
Figure 1: Information Security Market Opportunities, 2030 Segment Forecast. Source: Gartner, G00862059 (September 2026). Original figure by Gartner. Commentary and independent analysis by softwarestrategiesblog.com. Please click to expand.
Securing AI becomes the largest line item in 2029
Gartner places securing AI inside other security software. The report sizes the market for securing AI ecosystems and AI agents at $3 billion in 2026 and $16 billion by 2030, citing its companion analysis, Forecasting the $16.4 Billion Opportunity in Securing AI.
That makes securing AI about 16% of the other security software category in 2026 and about 43% by 2030, by my calculation.
Of the $19.2 billion the category adds over the period, roughly $13 billion comes from securing AI. The rest of the category grows from about $15.3 billion to about $21.5 billion.
Other security software is also the only category whose growth accelerates every year of the forecast, from 16.3% in 2026 to 20.1% in 2030 in constant currency. It passes enterprise endpoint protection in 2029, $31.1 billion against $30.1 billion, and finishes 2030 at $37.5 billion against $32.9 billion.
By 2030 securing AI alone, at $16 billion, is roughly the size of cloud security posture management ($16.1 billion), managed detection and response ($15.7 billion) or cloud workload protection ($15.7 billion), and larger than SIEM ($11.2 billion).
Gartner’s second AI number is larger. Gartner’s AI-amplified security forecast projects AI-amplified security, meaning existing security products with AI built in, rising from $49 billion in 2026 to $204 billion by 2030.
Each bar in the next chart equals Gartner’s 3Q26 total for that year. The navy segment is Gartner’s AI-amplified security spending. The light-blue segment is everything else in the information security market, calculated by subtracting AI-amplified spending from the total.
Each segment shows its dollars and its share of that year’s total. The indigo note repeats Gartner’s securing AI figures, which sit inside other security software rather than in the AI-amplified total.
Everything else, the light-blue segment, shrinks from $182.9 billion (95%) in 2024 to $168.4 billion (45%) in 2030, even as the total nearly doubles.
AI-amplified security spending as a share of total information security spending, 2024 to 2030. Data from Gartner, Forecast Analysis: AI-Amplified Security, Worldwide, 2026 (August 2026) and Gartner G00862059 (September 2026). The share combines two Gartner forecasts and is an illustrative softwarestrategiesblog.com calculation, not a Gartner-published ratio.
Set against the 3Q26 totals, AI-amplified spending rises from 20% of the market in 2026 to 39% in 2028, 47% in 2029 and 55% in 2030. Treat that as an illustration of direction, since the two forecasts were built separately.
By the end of the decade, most security dollars will buy products where AI does part of the detection, triage or response work.
Gartner’s report expects AI code security assistants and cybersecurity AI assistants to automate event triage, false-positive reduction and code remediation, and it expects organizations to shift from reactive defense toward continuous threat exposure management (CTEM).
North America is 53% of 2030 spending, and China grows fastest
On the left, the chart shows each region’s 2030 spending in current dollars and its share of the world total. On the right is each region’s 2025 to 2030 CAGR in constant currency. The dashed line marks the 10.8% world rate, and indigo marks China and Japan, the two fastest-growing regions.
2030 information security spending by region in current U.S. dollars and 2025-2030 CAGR in constant currency. Data from Gartner G00862059. Shares calculated by softwarestrategiesblog.com.
North America. $129.2 billion in 2026, 52.2% of the world. $197.7 billion by 2030, 53.0%. 11.4% CAGR. The United States alone reaches $181.1 billion in 2030.
Europe. $64.0 billion in 2026 to $91.3 billion by 2030. 8.6% CAGR, the slowest of the nine regions.
China. $10.7 billion in 2026, up 24.5% in current dollars. $18.7 billion by 2030. 15.4% CAGR, the fastest region.
Japan. $12.6 billion in 2026 to $22.2 billion by 2030. 13.1% CAGR, second fastest, with 17.6% constant-currency growth in 2026.
Emerging markets. Emerging Asia/Pacific grows at 11.1%, Sub-Saharan Africa at 10.5%, Latin America at 9.3%, and the Middle East and North Africa at 9.1%.
At the country level, China (16.2%), Indonesia (13.9%), Japan (13.1%) and Taiwan (12.4%) post the fastest constant-currency CAGRs among the 47 countries in the file.
All 41 categories, ranked
Growth rates spread wide across the full ranking. Seven categories grow faster than 18% a year. Twenty-nine grow below the 10.8% market rate. Two shrink.
Bars rank all 41 categories by 2025 to 2030 CAGR in constant currency. Each bar carries its CAGR, and the right-hand column lists the category’s 2030 market size in current dollars. Click the chart to open it full size.
Navy is security software, mid-blue is security services and sky blue is network security. Indigo marks the two shrinking categories, and a dashed line marks the 10.8% market rate.
All 41 information security categories ranked by 2025-2030 CAGR in constant currency, with 2030 market size in current U.S. dollars. Data from Gartner G00862059. Ranking by softwarestrategiesblog.com.
Network access control declines at a 17.7% CAGR, from $922 million in 2026 to $382 million in 2030. Intrusion detection and prevention systems fall at 8.3% a year, from $785 million to $548 million.
Both sit inside network security equipment, the same subsegment where firewalls, zero trust network access and network detection and response all grow. My read is that standalone network appliances are being absorbed into firewall platforms and ZTNA, which is consistent with Gartner’s comments on platform consolidation.
User authentication grows at 3.1%, the slowest positive rate in the forecast, while access management grows at 9.2% to $12.1 billion and identity governance and administration at 10.2% to $7.1 billion. My read is that identity spending is shifting from the login event to governing who and what holds access.
A reading note on Gartner’s Table 1
Readers working from the PDF of the Gartner information security forecast should check the growth columns in Table 1. For the last three rows, the growth rates appear offset by one row. The table shows 16.3% to 20.1% growth next to security consulting services and 9.0% to 5.6% next to other security software.
Gartner’s detailed dataset shows the reverse. Other security software accelerates from 16.3% to 20.1%, security consulting services slows from 9.6% to 5.0%, and security professional services slows from 9.0% to 5.6%. The dollar values in the table are correct. Every growth rate in this post comes from the detailed file.
What security leaders should do with this forecast
Inventory every firewall and VPN concentrator for PQC capability now. Gartner’s refresh window opens in 2027 for government, financial services and defense. Organizations that sell into those sectors, or connect to them, will face the same questions in their own procurement and supplier reviews. Ask vendors which appliance generations support ML-KEM in hardware at full inspection throughput, and get the answer in writing.
Budget the refresh as a 2027 and 2028 capital item. Gartner’s revision adds $1.08 billion to 2027 and another $0.43 billion in 2028, then only $0.26 billion and $0.07 billion more in 2029 and 2030. Waiting for 2029 means buying when lead times and pricing reflect peak demand.
Plan for securing AI as a line item, not a pilot. At $16 billion by 2030, securing AI will be comparable in size to CSPM and MDR. Governance gaps are already visible. Gartner’s first AI governance hype cycle found 34% of enterprises govern AI with policies they only partly follow, which I covered in Gartner’s 2026 AI Governance Hype Cycle.
Push cloud security consolidation. CSPM, CASB and CWPP are the three fastest-growing categories, and Gartner lists SSE and CNAPP adoption alongside tool consolidation and cost control as 2027 budget priorities. Consolidating onto those platforms is the most direct way to fund the growth without adding consoles and contracts.
Re-test services contracts against AI-assisted operations. Services share drops from 39.3% to 33.6% by 2030. Managed security operations still adds $7.0 billion, so outsourcing is not shrinking. What changes is the mix of human hours and AI triage inside each contract, and pricing should reflect it.
Frequently asked questions
How much will worldwide information security spending be in 2026? Gartner forecasts $247.5 billion in 2026, up 13.6% in current U.S. dollars and 12.7% in constant currency.
How big will the security market be by 2030? $372.8 billion, which Gartner frames as $373 billion and a 10.8% constant-currency CAGR from 2025 through 2030.
What changed in the 3Q26 Gartner information security forecast? Firewall equipment growth for 2027 rose to 13.4% from 7.8% in constant currency, driven by post-quantum firewall refreshes. Every other business category kept its constant-currency outlook from June.
Which security category grows fastest? Cloud security posture management, at a 27.6% CAGR from 2025 to 2030, reaching $16.1 billion.
How large is the securing AI market? Gartner sizes securing AI at $3 billion in 2026 and $16 billion by 2030, counted inside other security software.
How I built this analysis
All market sizes are Gartner end-user spending from the 3Q26 detailed forecast file (G00862059), in current U.S. dollars unless noted. All growth rates and CAGRs are constant currency, matching Gartner’s reporting convention, with 2024 as the constant-currency base year.
Revisions compare the 3Q26 and 2Q26 (G00855892) detailed files category by category in constant currency, which separates forecast changes from exchange-rate effects. Dollar additions, shares, rankings, regional splits and the AI-amplified ratio are my calculations.
Securing AI figures ($3 billion in 2026, $16 billion by 2030) are Gartner’s, as stated in the 3Q26 report. The AI-amplified figures come from Gartner’s August 2026 AI-amplified security forecast.
Gartner Hype Cycle for AI Governance, 2026, showing AI cybersecurity governance, AI governance platforms, and agentic AI risk innovations plotted across the innovation trigger, peak, trough, slope, and plateau phases. Please click on the graphic to expand for easier reading.
Gartner’s 2026 AI Leaders Effectiveness Survey found that 34% of organizations have well-defined AI governance structures and policies for managing risks, ethics, and compliance. Those same organizations report only partial adherence to the rules they wrote, while another 22% still rely on basic or ad hoc policies. Only 7% qualify as recognized leaders in ethical AI.
That gap between writing the policy and living by it is what Gartner’s first Hype Cycle for AI Governance, 2026 is built to address. Published July 21, 2026, the inaugural cycle plots 32 innovations and ranks each by benefit rating and years to mainstream adoption. CISOs and enterprise architects get a planning map that builds on Gartner’s forecast that agentic AI will overtake chatbot spending by 2027. Throughout this post, I use “rogue agents” as my editorial shorthand for unsanctioned AI agents operating outside governance perimeters.
The two clusters that carry the security agenda
The report organizes its 32 innovations around six enterprise trends. Two carry the security agenda. Agentic AI oversight and life cycle governance is the first, grouping agentic AI governance, agent development life cycle, AI agent identity, AI engineering, AI gateways and AI governance platforms under one trend. Advancing AI security is the second, covering AI TRiSM, AI cybersecurity governance, disinformation security, zero-trust data governance, mechanistic interpretability and AI product attribution and transparency. Together they define where governance stacks connect to identity systems, traffic controls and incident response playbooks. For how these gaps show up in spending data, see my analysis of Gartner’s $248.9B security forecast.
Five innovations that pay off in under two years
Table 1, the Priority Matrix, ranks every innovation by benefit rating and adoption timeline. Only five entries land in the “Less Than 2 Years” column. Responsible AI sits alone in the Transformational row, Gartner’s highest rating. AI guardrails, data access governance, digital ethics and ontologies all carry High benefit ratings at the same timeline. Gartner calls these the near-term priorities for scalable governance. CISOs should fund them first.
Please click on the image to expand for easier reading.
The two-to-five-year column is the densest band. Thirteen innovations carry a High benefit rating there, including agentic AI governance, AI agent identity, AI TRiSM, zero-trust data governance and third-party risk management. That band is where CISOs will build governance stacks over the next several budget cycles. For context on spending already flowing to AI-related capabilities, see my breakdown of Gartner’s $244.2B security forecast.
Where AI cybersecurity governance actually lands
AI cybersecurity governance carries a Moderate benefit rating at the Innovation Trigger, five to ten years from mainstream adoption. That placement may surprise CISOs who expected Gartner to rate it higher. The profile’s key goals are to prevent shadow AI, minimize attack surfaces and ensure visibility and response to incidents. The placement is a market signal, not a dismissal. Tooling is early, but the need is urgent enough that CISOs should treat AI cybersecurity governance as an architecture requirement today.
What the Priority Matrix tells your board
The report leads with two strategic planning assumptions that carry board-level weight. Enterprises implementing AI governance will outperform ungoverned competitors in AI adoption by 25% by 2029. The downside is just as concrete. Autonomous agents identifying minor consumer rights violations and turning them into lawsuits will increase corporate settlement costs by 15% over the same period. Growth-oriented executives respond to the first number. Risk-averse ones respond to the second.
Turning the curve into controls
Start by mapping your AI agent footprint, sanctioned and unsanctioned, across SaaS platforms, internal applications and shadow IT. From there, match the Hype Cycle’s innovations to four governance domains. The identity and access layer runs on AI agent identity and AI governance platforms. Data classification draws on AI guardrails, data access governance and zero-trust data governance, while AI gateways and AI TRiSM handle traffic mediation. Agent risk management anchors in agentic AI governance and the agent development life cycle. Build all four as shared services. For how agent sprawl is reshaping security spending, see my roundup of agentic AI forecasts and market estimates, 2026.
What these numbers add up to
Gartner’s inaugural Hype Cycle for AI Governance puts 32 innovations on the curve. Only five reach mainstream adoption in under two years. The security-relevant capabilities cluster in the two-to-five-year band, which means CISOs have a narrow window to build governance stacks before agent footprints outpace controls. The 34% adherence stat is the warning, and the Priority Matrix is the roadmap out of it.
This post is my personal reflection on Gartner’s AI governance research from a CISO and enterprise architecture perspective. It does not represent any employer or client.
Source: Gartner, Hype Cycle for AI Governance, 2026, Svetlana Sicular, Var Shankar, Lauren Kornutick, Sumit Agarwal, 21 July 2026, G00854164.
For each month’s AI agent attacks, exploited CVEs and breaches with primary sources, see my monthly AI security news briefing.
Spending on the chatbots and assistants embedded in enterprise software peaks at $272.6 billion in 2027 and then shrinks every year through 2030. Gartner buried that projection inside the 2Q26 update of its worldwide AI spending forecast, published July 24, and it matters more than the headline total. By 2030, embedded chatbot spending falls back to $205.8 billion, a hair above its 2025 starting point.
Embedded agenticAI takes the money instead, growing from $88.2 billion in 2025 to $1 trillion by 2030, an 11.4x expansion inside a single software category.
None of that slows the topline. Worldwide AI spending reaches $2.67 trillion in 2026, up 49.5% from 2025, on its way to $5.95 trillion by 2030. The figure Gartner published in May was $2.59 trillion for this year. Ninety days later, the client-facing number runs $74.8 billion higher, and the firm added $496.8 billion to its comparable 2025 through 2030 outlook in a single quarter.
Four tables below show where the money lands, which segments stall, and what Gartner changed its mind about between April and July.
Where $5.95 trillion lands
Infrastructure stays the biggest line through 2030 at $2.79 trillion, even as its share of total spending slides from 55% in 2025 to 46.9% at the end of the window. AI-optimized servers alone reach $981.7 billion by 2030, a 3.4x jump from 2025, and AI processing semiconductors add another $656.4 billion. O
One caution before quoting the total anywhere. Gartner’s note flags the forecast as a view across the whole AI value chain, so the chip and the server it ships inside both get counted. Read $5.95 trillion as the size of the AI economy, not as net end-user budgets.
Devices carry more of the infrastructure number than most readers expect. Business and consumer AI devices combine for $904.4 billion in 2030, and $647.4 billion of that is consumer hardware, the AI PCs and phones landing in shopping carts rather than data centers.
Growth flattens fast after next year. Total spending rises 49% in 2026 and 36% in 2027, then steps down to 21%, 18% and 15% through 2030, while infrastructure decelerates from 51% growth this year to 9% at the end of the forecast.
Of the $883.8 billion in net-new AI spending arriving in 2026, infrastructure absorbs $502.5 billion, or 57 cents of every new dollar. The shape of the curve says the buildout peaks now and software inherits the growth.
Farther down the board, AI cybersecurity at $220.9 billion and AI agents and assistants at $219.9 billion finish 2030 within $1 billion of each other. Gartner created the agents category only this quarter.
Agentic AI crosses $1 trillion inside enterprise software
Gartner rebuilt its segmentation this quarter, splitting cross-functional and consumer agents out of AI software and adding consumer agents to the forecast for the first time. The new structure exposes a replacement cycle the old rollup hid. Inside enterprise software, agentic AI overtakes chatbots in 2027, the same year chatbot spending tops out, and from that peak to 2030 the embedded chatbot line surrenders $66.8 billion.
Cross-functional agents, the ones that work across software from multiple vendors, start from a base of zero. Gartner books $347 million for cross-functional agentic AI in 2026 and $78.1 billion in 2030, a number it raised this quarter on the thesis that these agents begin cannibalizing traditional SaaS by decade’s end. The ceiling matters as much as the curve. Against $1.21 trillion in total 2030 AI software spending, $78.1 billion says the incumbents hold the decade, because data access, integration complexity and execution reliability hold the category back from serious SaaS competition until 2030, in Gartner’s read.
The buy-versus-build verdict is just as lopsided. Agent builder platforms, the tooling for constructing your own agents, reach only $12.6 billion by 2030, so embedded agentic AI outspends them nearly 80 to 1. The first production agent most companies run will ship inside software they already own. Gartner describes exactly that race, with vendors across software categories embedding agentic AI to defend their installed bases against cross-functional challengers.
Consumer agents barely register yet in dollar terms. Gartner carries $26.9 million for consumer agentic AI in 2026, then $17.7 billion in 2027 as paid consumer agents arrive at scale, building to $51.8 billion by 2030. Adding consumer agents and assistants lifted Gartner’s 2030 total by $133 billion. For how these agent numbers stack against other analyst estimates, see my roundup of agentic AI forecasts and market estimates, 2026.
AI security expands 8.5x and splits in two
AI cybersecurity grows from $25.9 billion in 2025 to $220.9 billion in 2030, an 8.5x expansion at a 53.5% compound rate. Spending in the category grew 140% in 2025, and Gartner models another 98% jump this year. AI cybersecurity and AI data were also the only two markets left completely untouched between the 1Q26 and 2Q26 forecasts, which makes security the steadiest conviction in the entire model. For the standalone security spending outlook, see my breakdown of Gartner’s 2Q26 information security forecast.
Two markets move at different speeds inside the category. AI-amplified security, meaning AI capability inside security tooling, carries the volume and reaches $204.5 billion by 2030. Securing AI, the discipline of protecting AI systems themselves, runs smaller and faster, from $1.5 billion in 2025 to $16.4 billion in 2030 at a 60.4% compound rate.
Set the security numbers against the agent forecast and an exposure gap opens. The 2030 outlook has enterprises running $1.08 trillion of embedded and cross-functional agentic software while spending $16.4 billion to secure AI systems, roughly $66 of agentic software for every $1 of securing-AI budget. AI observability and governance tooling adds just $3.9 billion more. A software wave that large riding on a security ratio that thin is the budget argument CISOs should be starting now.
The fastest growth goes to whatever cuts the bill
Rank every segment by compound growth and one pattern jumps out, because the fastest-growing lines are the ones that make AI cheaper. Synthetic data generation leads the entire forecast at a 142.5% compound rate, expanding 84x from $146 million in 2025 to $12.2 billion in 2030. AI-ready datasets, the licensed real-data alternative, peak at $583 million in 2029 and then decline, leaving synthetic data outselling licensed data 22 to 1 by 2030. Gartner is forecasting the substitution of purchased data itself.
Domain-specific language models tell the same cost story at larger scale. DSLMs and specialized models grow 210% in 2026 and compound at 84.5% through 2030, rising from 12.2% of all model spend to 24.3%. Cost pressure also explains the strangest revision in the update. Gartner cut $57.8 billion in cumulative dollars from its generative AI model forecast while raising the segment’s 2026 growth rate from 110% to 117%, which nets out to more deployments running on cheaper models and smaller checks. Arunasree Cheparthi, a senior principal research analyst at Gartner and one of the forecast’s authors, said in the firm’s July 20 platforms and models announcement that spending “is shifting toward providers who can demonstrate clear value.”
What Gartner changed in 90 days
Between the April forecast and this one, Gartner added $500.8 billion to AI infrastructure across the 2025 through 2030 window, the largest revision in the update, and did it while flagging memory-related price increases. The note calls infrastructure demand inelastic to that pricing pressure, because hyperscalers keep buying AI-optimized servers on the conviction that model capabilities improve through 2030.
Software took the other side of the trade. AI software gained $191.9 billion and application development platforms picked up $10.7 billion. Gartner lifted the 2026 app-dev growth rate from 28% to 39% as enterprises build custom AI applications and demand usage tracking to prove the spend. The cuts land on everything that resembles consulting or plumbing. AI services lost $80.7 billion across the window, with every single year revised down, and platforms for data science and machine learning lost $68.2 billion, including an 8% cut to 2027 alone.
The services cut hides a structural shift rather than a retreat. Gartner still sizes AI services at $1.25 trillion in 2030, but the growth belongs to indirect services, which compound at 34.5% and pass direct, consulting-led engagements in 2028. Direct AI services compound at 15.7%, less than half the indirect rate. Buyers are routing transformation budgets through software and cloud purchases instead of billable hours.
Three dates to plan against
2027 is the year chatbot spending tops out and agentic AI takes over inside enterprise software, which gives any vendor still selling assistant-branded features through the end of next year to ride what growth remains. By 2028, indirect services pass consulting-led engagements and infrastructure growth drops to 15%, so the buildout stops flattering everyone’s numbers. And 2030 arrives with $1.08 trillion of agentic software guarded by $16.4 billion of securing-AI spend. The first two dates decide where the money goes, and the third decides what happens when it arrives unprotected.
This post is my personal reflection on Gartner’s AI spending research from an industry analyst perspective. It does not represent my employer.
Source: Gartner, Forecast: AI Spending, Worldwide, 2025-2030, 2Q26, Kay Arnott, Jon Erensen, Amarendra, Adrian O’Connell, Arunasree Cheparthi, Naresh Singh, Peter Middleton, Hardeep Singh, Shailendra Upadhyay, Rishi Padhi, 24 July 2026, G00855896.
$30.6 billion in new security spending in a single year. Gartner's 1Q26 Information Security forecast projects $246.2 billion in 2026 spending across 41 categories. Cloud Security Posture Management leads at 33.4% growth, followed by Threat Intelligence at 27.3% and Cloud Access Security Brokers at 27.2%. Two legacy categories are declining. I analyzed the full dataset to rank the 10 fastest-growing categories by growth rate and what they mean for CISO budgets.
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.
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.
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.
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.
Over 57% of employees are using personal GenAI accounts for work. A third of them admit to uploading sensitive data into tools their security teams haven’t approved. Meanwhile, agentic AI is proliferating through no-code platforms and vibe coding, creating attack surfaces most CISOs can’t see, let alone govern. And quantum computing? No longer a 10-year planning horizon. It’s a 2030 action deadline.
Gartner’s Top Trends in Cybersecurity for 2026 report, released February 5, 2026, identifies six forces reshaping how CISOs must operate. These cut across governance, AI adoption, identity, workforce, and cryptographic strategy simultaneously. None of them is incremental.
The trends report lands alongside Gartner’s updated Forecast: Information Security, Worldwide, 2023–2029, 4Q25 (G00843183, December 18, 2025) and the Forecast Analysis: Information Security, Worldwide, 2026 (G00838442, February 5, 2026), which together project global information security spending reaching $244.2 billion in 2026, up 13.3% in current U.S. dollars. I’ve tracked this forecast through multiple quarterly updates. The trajectory keeps steepening. The six trends below explain where that money is going and why.
“Cybersecurity leaders are navigating uncharted territory this year as these forces converge, testing the limits of their teams in an environment defined by constant change,” said Alex Michaels, Director Analyst at Gartner. “This demands new approaches to cyber risk management, resilience, and resource allocation.”
The spending backdrop: $244 billion and accelerating
Before getting into the six trends, context matters. Gartner’s 4Q25 forecast shows the three major security segments all growing at double-digit constant currency rates in 2026:
Cloud security remains the fastest-growing subsegment at 28.8% growth in 2026. Nothing else comes close. The combined cloud security market (cloud security posture management, cloud access security brokers, and cloud workload protection platforms) is projected to reach $32.4 billion by 2029, with a 25% CAGR in constant currency. I’ve been watching this subsegment accelerate for three quarters straight. CSPM alone is growing at a 31.30% CAGR.
Cloud security spending reaches $32.4 billion by 2029. CSPM leads at 31.30% CAGR. Source: Gartner 4Q25 Forecast. (Please click on the image to expand for easier reading)
Trend 1: Agentic AI demands cybersecurity oversight
This is the trend that touches everything else on this list. Employees and developers are deploying AI agents through no-code/low-code platforms and “vibe coding” at a pace that outstrips security governance. Unmanaged AI agent proliferation. Unsecured code. Compliance violations that most security teams don’t even have visibility into yet. That’s the picture Gartner is painting.
Gartner’s recommendation is blunt: cybersecurity leaders must identify both sanctioned and unsanctioned AI agents operating within their environments, enforce access controls and data guardrails, and develop incident response playbooks specific to agent-driven threats.
“While AI agents and automation tools are becoming increasingly accessible and practical for organizations to adopt, strategic cybersecurity planning for these technologies is essential,” said Michaels. Cybersecurity leaders must work cross-functionally to manage agentic AI adoption, identifying sanctioned and unsanctioned AI agents, enforcing data access controls, and developing incident response playbooks.
Trend 2: Global regulatory volatility drives cyber resilience efforts
Regulators are getting personal. Boards and executives now face direct liability for compliance failures. Not just organizational fines, but individual accountability. The penalties for inaction have moved from theoretical to career-ending. Across multiple jurisdictions simultaneously.
Gartner advises cybersecurity leaders to formalize collaboration across legal, business, and procurement teams to establish clear accountability for cyber risk. Align control frameworks to recognized standards. Address data sovereignty concerns before they become enforcement actions. The organizations doing this well are treating regulatory preparedness as a core security function, not an annual compliance checkbox.
This is where the spending data gets interesting. Gartner’s forecast shows security consulting services growing from $24.2 billion (2024) to $36.6 billion (2029), adding $12.4 billion in five years. Security professional services follow a similar trajectory: $27.3 billion to $40.8 billion, adding $13.5 billion. Organizations are buying outside expertise because they can’t build regulatory competence fast enough in-house. I’ve been covering these numbers for three quarters, and the services growth is the part of the forecast that keeps surprising me.
Infrastructure protection adds $26.4 billion between 2024 and 2029, the largest absolute growth of any subsegment. Source: Gartner 4Q25 Forecast. (Please click on the image to expand for easier reading)
Trend 3: Post-quantum computing moves into action plans
Gartner predicts advances in quantum computing will render the asymmetric cryptography that organizations rely on unsafe by 2030. Four years. That’s the window to adopt post-quantum cryptography alternatives before “harvest now, decrypt later” attacks start cashing in on data that adversaries are collecting today.
Organizations need to identify their cryptographic deployments, assess data sensitivity and lifespan, and prioritize cryptographic agility. That last phrase keeps coming up in my conversations with CISOs. The ability to swap encryption methods without re-architecting entire systems. Swapping an algorithm is one thing. Doing it across a production environment without downtime is an entirely different problem.
“Post-quantum cryptography is reshaping cybersecurity strategies by prompting organizations to identify, manage, and replace traditional encryption methods, while prioritizing cryptographic agility,” said Michaels. “By investing in these capabilities and prioritizing migration now, assets will be secured when quantum threats become a reality.“
The encryption market in Gartner’s 4Q25 forecast grows from $1.04 billion in 2023 to $2.04 billion by 2029 at an 11.95% CAGR. A 2.0x increase. For what has historically been one of the slower-growing security subsegments, that’s a significant acceleration. Quantum urgency is changing the math.
Trend 4: Identity and access management adapts to AI agents
AI agents are breaking traditional IAM models. Plain and simple. Identity registration and governance, credential automation, and policy-driven authorization weren’t designed for autonomous machine actors that can initiate actions, access data, and interact with systems without human intervention. The scale problem compounds fast: when every employee can deploy dozens of AI agents, the identity surface area explodes.
Gartner recommends a targeted, risk-based approach. Invest where gaps and risks are greatest. Leverage automation where possible. The practical starting point is understanding which AI agents carry the most privilege and the least oversight. Those are your highest-risk identities right now, and most organizations haven’t inventoried them.
The identity market is already significant. Gartner’s 4Q25 forecast shows identity access management growing from $18.7 billion (2024) to $29.0 billion (2029), adding $10.3 billion in five years. That’s before the full scale of agentic AI identity requirements hits the market. IAM vendors that solve machine-actor identity at scale will capture a disproportionate share of that $10.3 billion growth.
AI-enabled security operations centers are enhancing alert triage and investigation workflows. The technology works. But deploying AI into a SOC doesn’t automatically reduce headcount needs. It changes the skill mix. Analysts who excelled at manual triage need different capabilities to oversee AI-driven workflows. Organizations are discovering this the hard way. That’s an organizational transformation challenge, and throwing more technology at it doesn’t help.
“To realize the full potential of AI in security operations, cybersecurity leaders must prioritize people as much as technology,” said Michaels. “Strengthening workforce capabilities, implementing human-in-the-loop frameworks into AI-supported processes and aligning adoption with clear strategic objectives will be critical to maintaining resilience as SOCs evolve.”
The talent dimension makes this harder than it already sounds. ISC2’s 2024 Cybersecurity Workforce Study, published in October 2024, documented a global workforce gap of 4.8 million professionals, a 19% year-over-year increase. The active workforce flatlined at 5.5 million (up just 0.1%). The numbers are brutal: 25% of organizations reported cybersecurity layoffs in 2024. 37% faced budget cuts. 90% report skills shortages. 58% believe the shortage puts their organization at significant risk. On the spending side, managed security services are growing at 11.1% in 2026, the fastest rate in the services segment. Organizations can’t hire fast enough, so they’re buying managed SOC capacity instead.
Trend 6: GenAI breaks traditional cybersecurity awareness tactics
Existing security awareness programs are failing. Full stop. A Gartner survey of 175 employees conducted between May and November 2025 found that 57% use personal GenAI accounts for work purposes, while 33% admit to uploading sensitive information to tools their organizations haven’t sanctioned. Those numbers should alarm every CISO reading this. A third of your workforce is actively feeding proprietary data into tools you can’t audit.
Gartner recommends shifting from general awareness training to adaptive behavioral programs that include AI-specific tasks. Generic compliance videos won’t cut it here. The organizations getting this right are making approved GenAI tools easy to access and unsanctioned tools hard to justify. Trying to ban GenAI outright just drives usage underground and costs you talent.
Strengthening governance, embedding secure practices, and establishing clear policies for authorized GenAI use will reduce exposure to privacy breaches and intellectual property loss. The governance gap on GenAI usage is, in my view, the most underestimated risk on this entire list. Every other trend has a spending line item attached to it. This one requires behavioral change, which is harder to buy.
Total market trajectory: $173.5 billion to $323.5 billion
Gartner’s year-by-year spending trajectory shows the acceleration curve these six trends are riding:
Source: Gartner Forecast: Information Security, Worldwide, 2023–2029, 4Q25 Update (G00843183, December 18, 2025). Current U.S. dollars.
CSPM and CASB lead all security categories with 31% and 26% CAGR through 2029. Source: Gartner 4Q25 Forecast. (Please click on the image to expand for easier reading)
What this means for CISOs
Three of the six trends (agentic AI oversight, IAM for machine actors, and GenAI awareness) are fundamentally about the same problem: autonomous AI systems operating inside enterprise environments without adequate governance. The other three (regulatory volatility, post-quantum readiness, and AI-driven SOCs) are the structural forces those governance failures will collide with. That convergence is the signal about where 2026 budgets need to go.
The organizations that will navigate this environment successfully are doing three things simultaneously:
Mapping their AI agent footprint now. If you don’t know how many AI agents are operating across your environment, sanctioned and unsanctioned, you can’t govern what you can’t see. Gartner’s 75% AI-amplified product adoption projection by 2028 means this window for establishing control is narrow.
Building cryptographic agility into their architecture. The 2030 quantum deadline means migration planning starts in 2026, not 2028. The encryption market’s 2.0x growth reflects early movers. Late movers face rip-and-replace costs that compound every quarter they wait.
Investing in people alongside AI tooling. AI-enabled SOCs work when human operators have the skills to oversee them. The ISC2 data is unambiguous: a 4.8 million professional gap growing at 19% year-over-year. Managed security services growth at 11.1% tells you where CISOs are finding capacity.
Gartner’s numbers aren’t projections anymore. They’re procurement trends already hitting finance systems. The $244.2 billion flowing into information security this year will fund agentic AI governance, quantum migration, and SOC transformation, whether your organization participates or not.
Bottom line: CISOs planning for 2027 are watching their competitors buy the tools they’ll be scrambling for in 18 months. The data says move now.
ServiceNow dropped $11.6 billion on security acquisitions in 2025 alone. Armis for $7.75 billion. Moveworks for $2.85 billion. Veza for roughly $1 billion. In 2025, just one company, ServiceNow, spent more on acquiring security startups than 175 startups raised in two years. Meanwhile, the entire AI security startup ecosystem raised $8.5 billion across 175 companies over 24 months. That single data point should reshape how security leaders think about vendor consolidation and how AI builders think about their exit paths.
I analyzed Crunchbase data covering every AI security startup that raised Series A, B, or C funding between January 2024 and December 2025. The patterns are striking.
The acceleration is real
Q1 2024: $274 million across 8 deals. Q4 2025: $2.17 billion across 28 deals. That’s 8x growth in quarterly funding over two years.
The full-year numbers tell the story more clearly. 2024 saw $2.16 billion in total funding. 2025 hit $6.34 billion, nearly tripling. Average deal sizes jumped from $34 million to $54 million. This isn’t a gentle upward trend. The market is restructuring in real time.
Where the money flows
Network and Zero Trust infrastructure captured $1.9 billion across 44 companies. Tailscale‘s $161 million Series C reflects what enterprises already know. VPN architectures are dying. Identity-based access is replacing them.
Threat Detection and SOC automation drew $1.2 billion across 28 companies. 7AI‘s $130 million Series A stands out as one of the largest A funding rounds in this category. The bet: AI agents can handle the full security operations lifecycle at a scale human analysts cannot match.
Identity and Access Management pulled $990 million. But here’s what matters: that money went to just 6 companies. Saviynt‘s $700 million Series B dominates the category. When one company captures 71% of a category’s funding at Series B, investors see platform consolidation ahead. ServiceNow’s Veza acquisition, three weeks later, validated that thesis.
Insights into deal sizes
Median tells a different story from average deal sizes. Series A median: $20 million. Series A average: $28 million. The gap widens at later stages. Series C median: $85 million. Series C average: $119 million.
Translation: mega-deals skew the data significantly. Eighteen companies raised $100 million or more. Those 18 deals represent 10% of companies but 40% of total funding. For every Saviynt raising $700 million, dozens of startups are raising $15-25 million Series A rounds.
The AI/LLM security gap
Only 13 companies focus specifically on securing AI systems, LLMs, and agentic applications. Total funding: $414 million. That’s less than 5% of the $8.5 billion total. For context: ServiceNow paid more for Veza alone than the entire AI/LLM security category raised in two years.
The players building in this space:
• Noma Security ($100M, Series B). Unified AI and agent security platform.
• Lakera ($20M, Series A). Real-time GenAI security against LLM vulnerabilities.
• Prompt Security ($18M, Series A). Enterprise generative AI adoption platform.
• GetReal Security ($17.5M, Series A). Deepfake and AI-generated impersonation defense.
• Jericho Security ($15M, Series A). Training against generative AI-powered attacks.
Enterprises are deploying AI systems at unprecedented rates. Shadow AI breaches cost $4.63 million per incident. That’s $670,000 more than standard breaches, according to IBM’s 2025 Cost of a Data Breach Report. Model Context Protocol vulnerabilities. Prompt injection attacks. Data exfiltration through AI assistants. The attack surface expands while protection lags.
Either these 13 companies scale rapidly, established players acquire their way into the space, or CISOs face a protection gap without commercial solutions.
How spending breaks out geographically
The U.S. captured $6.1 billion across 119 companies. That’s 71% of total funding. Israel remains the second hub: 15 companies, $738 million. Germany, the UK, and Canada trail with single-digit percentages.
Within the U.S., California dominates: $2.7 billion across 62 companies. That’s more than all non-U.S. markets combined ($2.4 billion). Texas ($865M), New York ($667M), and Colorado ($295M) round out the top states.
The concentration creates vendor risk. Regulatory fragmentation between the U.S. and EU markets. Geopolitical tensions affecting Israeli companies. Single-region dependency in security infrastructure. These are fundamental considerations for enterprise security architects.
ServiceNow’s acquisitions signal large-scale consolidation
ServiceNow’s 2025 acquisition spree warrants its own analysis. Armis brings cyber-physical security and OT/IoT visibility. Moveworks adds agentic AI capabilities. Veza delivers identity security for the AI era. The company calls it an “AI control tower.” A unified security stack that sees, decides, and acts across the entire technology footprint.
The driver: ServiceNow’s Security and Risk business crossed $1 billion in annual contract value in Q3 2025. They expect Armis alone to triple their market opportunity. When a platform vendor invests $11.6 billion in its own security workflows, point solutions become acquisition targets or competitors.
What this means for 2026
For security leaders: Map your vendor portfolio against both funding momentum and M&A activity. Startups with strong backing will survive consolidation. Others won’t. Audit your AI deployment pipeline against available protections. The gap between AI adoption and AI security is widening. Accelerate zero-trust adoption while solutions mature.
For AI builders: Security isn’t a feature to add later. The $414 million flowing into AI/LLM security represents smart money recognizing that unprotected AI systems are enterprise liabilities. Build with guardrails or build vulnerabilities.
Analysis based on Crunchbase data covering 175 AI security startups that raised Series A, B, or C funding between January 2024 and December 2025. ServiceNow acquisition data from the company’s press releases dated December 2025.
