Oct 19
Gartner's 3Q26 IT spending forecast reaches $6.39 trillion in 2026 and $9.76 trillion by 2030. Servers add $1.58 trillion, 38% of new IT spending, and pass all IT services by 2030, as data center systems drive 97% of the latest upward revision.
The new Gartner IoT forecast puts four out of every five dollars in devices, and the fastest growth in the software that runs them.
Published September 25, the forecast sizes the worldwide IoT market opportunity at $736.6 billion in 2026, up 9.6%, and $953.3 billion by 2030. That is a 7.2% compound annual growth rate from 2025 through 2030, landing just under $1 trillion.
Endpoint electronics account for $769.2 billion of the 2030 total, or 80.7%. Application software grows at 20.4% a year and infrastructure software at 14.8%. Together, the two software segments compound at 16.3%, 2.3 times the market.
The trillion-dollar mark also moved. Gartner’s previous edition, published in June 2024, put the 2028 market at $990.5 billion. The new edition puts 2028 at $850.3 billion, a $140.2 billion reduction, and does not cross $1 trillion before 2030.
I built this analysis from Gartner’s forecast report (G00858825) and the full detailed dataset behind it: 73,493 rows covering 6 technology segments, 28 subsegments, 12 sectors, 47 use cases, 9 regions and 7 years.
Each bar in the hero chart stacks Gartner’s six technology segments in current U.S. dollars. Navy is endpoint electronics, mid-blue is communication services, sky blue is services, teal is infrastructure software, purple is application software and red is security. Italic figures above each bar give year-over-year growth.
Six tiles underneath carry the 2026 and 2030 totals, the $281.0 billion in new spending between 2025 and 2030, the application software growth rate, the 5G growth rate and the 2028 revision against the 2024 edition.
Gartner sizes the market across six technology segments. Here is how each one moves from 2025 to 2030.
| Segment | 2025 | 2026 | 2030 | 2025-2030 CAGR | 2030 share |
|---|---|---|---|---|---|
| Endpoint electronics | $545.8B | $600.7B | $769.2B | 7.1% | 80.7% |
| Communication services | $56.7B | $58.8B | $66.3B | 3.2% | 7.0% |
| Services | $41.0B | $43.9B | $57.7B | 7.1% | 6.1% |
| Infrastructure software | $19.9B | $23.0B | $39.7B | 14.8% | 4.2% |
| Application software | $6.9B | $8.3B | $17.5B | 20.4% | 1.8% |
| Security | $1.9B | $2.1B | $2.9B | 8.6% | 0.3% |
| Total | $672.3B | $736.6B | $953.3B | 7.2% | 100% |
Current U.S. dollars. CAGR and shares calculated by softwarestrategiesblog.com from Gartner’s dataset.
Growth peaks early. Gartner forecasts 9.6% in 2026 and 8.5% in 2027, then 6.4% in 2028, 6.1% in 2029 and 5.7% in 2030. Endpoint electronics drive the near-term numbers, growing 10.0% in 2026 and 8.7% in 2027 before slowing to 5.1% by 2030.
Software moves the other way. Application software growth rises from 20.2% in 2026 to 21.8% in 2030, and security growth climbs from 8.2% to 9.4%.
The market adds $281.0 billion between 2025 and 2030. Endpoint electronics capture $223.4 billion of it, or 79.5%.
The bubble chart below rebuilds Gartner’s own segment view from the dataset. The horizontal axis is growth rate, the vertical axis is dollars added, and bubble size is 2030 market opportunity.
Application software grows 2.8 times faster than the market but adds only $10.6 billion. Infrastructure software adds $19.8 billion at 14.8%. Software’s share of IoT spending rises from 4.0% in 2025 to 6.0% in 2030.
Gartner ties the software growth to connecting devices with enterprise systems, predictive maintenance, operational optimization and digital twin projects that run on IoT platforms. Software, services and security together climb from 10.4% of spending in 2025 to 12.4% in 2030.
That is the strategic split in this forecast. Hardware sets the size of the market. Software, services and security decide who captures recurring value once the devices are installed.
Gartner’s Table 2 compares this edition with the June 2024 edition, which ran through 2028. The new forecast is $113.8 billion lower for 2025 and $140.2 billion lower for 2028.
Endpoint electronics took the largest dollar cut, $102.6 billion in 2028. Its growth rates went up anyway: 8.9% to 10.0% in 2026, 7.0% to 8.7% in 2027 and 4.8% to 6.1% in 2028. A lower starting base, growing faster.
Services took the deepest percentage cut. The 2028 services forecast fell 37.6%, from $80.5 billion to $50.2 billion, with growth rates lowered 11 to 16 points in every year from 2025 through 2028.
Application software, infrastructure software and services all lost growth in the revision. Gartner says enterprise spending on software, security and services “is expected to develop more cautiously as organizations become more selective in scaling and expanding IoT environments.”
Security is the exception on dollars. Its 2028 forecast rose $665 million, or 37.3%, and Gartner lifted its 2028 growth rate from 6.7% to 8.6%.
Total 2028 growth moved up slightly, from 6.2% to 6.4%. The level is lower; the slope is about the same.
Automotive is the largest IoT sector at $322.1 billion in 2030. Manufacturing and natural resources follows at $198.9 billion. Together they account for 54.6% of the 2030 market.
Manufacturing is the growth story among the large sectors. It grows from $119.6 billion in 2025 to $198.9 billion in 2030, a 10.7% CAGR, adding $79.3 billion. Gartner expects it to grow 13.4% in 2026 and 15.0% in 2027.
Transportation reaches $109.8 billion at a 10.0% CAGR, with 16.0% growth in 2026 and 14.0% in 2027. Smart buildings, the fourth-largest sector at $107.2 billion, grows just 2.8% a year.
Inside manufacturing, software and services matter more than in the market overall. Application and infrastructure software reach $33.4 billion in the sector by 2030, 16.8% of its spending, compared with 6.0% for IoT overall. Services add another $32.3 billion.
Consumer connected cars remain the single largest use case, reaching $219.8 billion in 2030 and adding $58.3 billion. Manufacturing process automation adds $34.9 billion and air transport adds $28.8 billion.
Gartner names EV charging, manufacturing execution and management and connected products as the fastest-growing use cases from 2028 to 2030, at 18.6%, 12.0% and 11.3% CAGRs. The dataset also shows retail customer communication growing 12.9% over the same window, on a much larger $20.4 billion base.
Manufacturing execution and management is the standout among large use cases. It more than doubles, from $15.7 billion in 2025 to $32.8 billion in 2030, a 15.8% CAGR. Gartner attributes the growth to real-time control and optimization requirements on the factory floor.
Four use cases shrink. Connected lighting falls from $15.6 billion in 2025 to $7.5 billion in 2030. Automotive insurance declines from $6.4 billion to $4.3 billion, outdoor surveillance from $7.4 billion to $6.9 billion, and commercial automotive aftermarket from $2.1 billion to $1.5 billion.
Communication services is the slowest-growing segment at 3.2% a year, but the mix inside it changes fast.
IoT 5G connectivity grows from $2.2 billion in 2025 to $10.1 billion in 2030, a 36.2% CAGR. Satellite grows from $7.8 billion to $13.2 billion at 11.0%. Cellular 4G and below, still the largest connectivity line, falls from $43.0 billion to $38.5 billion.
Gartner links connectivity to digital thread solutions that connect IT, OT and product life cycle data across the industrial value chain, the data foundation digital twins need.
Gartner’s IoT security segment grows from $1.9 billion in 2025 to $2.9 billion in 2030. That is 0.3% of the 2030 market, against $769.2 billion in endpoints.
Security software, which Gartner counts inside infrastructure software, is the second-fastest-growing software subsegment at 21.2% a year, reaching $7.4 billion. Add it to the security segment and IoT security reaches $10.3 billion by 2030, still 1.1% of the market.
Analytic platforms lead software growth at 24.5%, reaching $9.6 billion. Database management systems grow 19.2% to $10.0 billion. IoT platforms, the middleware layer Gartner credits with connecting devices to enterprise systems, grow 12.5% to $14.0 billion.
For security leaders, the gap is the point. Every connected robot, vehicle, meter and controller extends the OT attack surface, and spending to secure those endpoints grows at about a penny per dollar of IoT spend, even counted broadly. For the broader security market context, see Gartner’s $247.5B security forecast makes post-quantum firewall refreshes the only upgrade through 2030.
North America is the largest region at $260.5 billion in 2030, followed by China at $229.9 billion and Europe at $224.2 billion. Together they hold 74.9% of the market.
North America grows slowest of the three, at 5.8% a year. Emerging Asia Pacific grows fastest, at 14.7%, reaching $53.0 billion. Sub-Saharan Africa grows 12.9% and Latin America 11.9%, both from small bases.
Gartner’s report also flags the war in the Middle East. It expects disruptions to the Strait of Hormuz to continue into 2027, with energy prices more than 50% above pre-war levels. Gartner expects the main near-term impact on IT spending to be a rebalancing of sourcing, vendor relationships and regional exposure rather than a material spending reduction.
The growth-rate columns in Gartner’s Table 2 are labeled 2025 GR, 2027 GR, 2028 GR and 2029 & 2030 GR. The values line up with 2025, 2026, 2027 and 2028.
The endpoint electronics changes of 1.1, 1.7 and 1.3 points match the revisions Gartner describes in its text for 2026, 2027 and 2028. I read the table that way throughout this analysis.
Gartner’s text also says the highest growth by 2030 comes from communications, media and services and transportation. In the dataset, communications, media and services is a $1.8 billion sector growing 11.0% a year, and transportation’s 10.0% CAGR trails manufacturing’s 10.7%.
How big is the IoT market according to Gartner? Gartner forecasts worldwide IoT market opportunity of $736.6 billion in 2026 and $953.3 billion in 2030, a 7.2% CAGR from 2025.
Which IoT segment is largest? Endpoint electronics, at $769.2 billion in 2030, or 80.7% of the market.
Which IoT segment grows fastest? Application software, at a 20.4% CAGR from 2025 to 2030, reaching $17.5 billion.
Did Gartner lower its IoT forecast? Yes. The 2028 forecast fell from $990.5 billion in the June 2024 edition to $850.3 billion, a $140.2 billion reduction, while 2028 growth edged up from 6.2% to 6.4%.
How fast is IoT 5G growing? IoT 5G connectivity grows at a 36.2% CAGR, from $2.2 billion in 2025 to $10.1 billion in 2030.
All market sizes are Gartner IoT market opportunity in current U.S. dollars from the detailed dataset behind G00858825, which reconciles to Gartner’s Table 1 totals. Growth rates for years and segments match Gartner’s published figures.
CAGRs for sectors, regions, subsegments and use cases, dollar additions, shares and the combined IoT security figure are my calculations. June 2024 edition values are derived by subtracting Gartner’s Table 2 dollar changes from the new forecast.
Earlier analysis in this series:
This post is my personal analysis of Gartner’s IoT research and does not represent my employer.
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.”
I built this analysis from Gartner’s research note (G00859901) and paired it with category data from Gartner’s 3Q26 information security forecast (G00862059), which sizes the markets security teams will buy from as they shift to exposure management.
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.
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:
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.
Gartner’s replacement is a shift from volume-based patching service-level agreements to exposure-based ones.
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.
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.
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 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).
Threat intelligence, the data CTEM uses to judge real-world exploitability, nearly doubles by 2030. Managed security operations adds $7.0 billion, the largest dollar gain among security services. I covered the full forecast in Gartner’s $247.5B security forecast makes post-quantum firewall refreshes the only upgrade through 2030.
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.
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.
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.
Gartner’s Figure 1 gives CISOs three talking points for boards worried about Mythos, Daybreak and frontier AI risk:
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?”
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.
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.
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.
Related analysis on this site:
This post is my personal analysis of Gartner’s research and does not represent my employer.
Enterprise application software spending reaches $496.3 billion in 2026 and $812.6 billion by 2030, according to the latest Gartner application software forecast. That is a 12.8% compound annual growth rate in constant currency, revised up from 12.7% last quarter.
The headline growth rate hides a sharper story. CRM alone captures $119.2 billion, or 38%, of the $316.2 billion the market adds between 2026 and 2030. In the same report, Gartner says cross-functional agentic AI will cannibalize $116 billion from traditional application software spending by 2030.
Those two numbers are close in size, and they point to the same conclusion. Most of the new money in application software goes to the markets where agentic AI is proving value first. Legacy suites that do not embed agents compete for a shrinking slice.
I built this analysis from Gartner’s Forecast: Enterprise Application Software, Worldwide, 2024-2030, 3Q26 (G00862072), published September 22, 2026. All market, subsegment and regional figures come from the 7,567-row dataset Gartner publishes with the report. The shares, dollars added and comparisons are my calculations.
Gartner says cumulative spending between 2026 and 2030 will exceed $3.2 trillion, “fueled by the transition from Generative AI to Agentic AI.” The dataset totals $3,227 billion over those five years.
Gartner expects business leaders to favor applications with embedded agentic capabilities, and vendors to compete on how much functionality they deliver through agents. It warns that “legacy offerings risk rapid obsolescence.”
Early value is already showing up in three segments, according to Gartner: CRM, analytics and human capital management (HCM). Adoption starts inside functional silos such as marketing, sales and customer service, where use cases are maturing. Cross-functional integration follows once use cases prove out, the technology matures and enterprises build trust.
That second phase is where the $116 billion comes from. Gartner covers it in a separate report, Spending on Cross-Functional Agentic AI Will Cannibalize $116 Billion of Spending From Application Software Markets by 2030.
CRM grows from $170.5 billion in 2026 to $289.8 billion in 2030 at a 13.8% CAGR. Its share of the total market rises from 34.4% to 35.7%.
Analytic platforms post the fastest market-level growth at 14.5%, reaching $73.8 billion. Email and authoring grows 13.6% to $77.2 billion, and supply chain management grows 13.2% to $71.5 billion. All three beat the market average.
ERP, other application software, content services and project and portfolio management all grow below 12%. Together they still add $106.5 billion, but each loses share.
| Market | 2025 | 2026 | 2030 | CAGR 2025-2030 | Added 2026-2030 | Share of new spending |
|---|---|---|---|---|---|---|
| CRM | $149.1B | $170.5B | $289.8B | 13.8% | +$119.2B | 37.7% |
| ERP | $73.5B | $83.0B | $130.9B | 11.6% | +$47.9B | 15.1% |
| Other application software | $74.6B | $83.5B | $128.6B | 10.9% | +$45.1B | 14.3% |
| Analytic platforms | $36.7B | $42.3B | $73.8B | 14.5% | +$31.5B | 9.9% |
| Email and authoring | $40.1B | $47.0B | $77.2B | 13.6% | +$30.3B | 9.6% |
| Supply chain management | $37.6B | $42.8B | $71.5B | 13.2% | +$28.7B | 9.1% |
| Content services | $18.9B | $21.3B | $31.9B | 10.5% | +$10.6B | 3.4% |
| Project and portfolio management | $5.3B | $5.9B | $8.8B | 10.2% | +$2.9B | 0.9% |
| Total | $435.8B | $496.3B | $812.6B | 12.8% | +$316.2B | 100% |
Spending in current U.S. dollars. CAGRs in constant currency. Dollars added and shares calculated by Software Strategies Blog from Gartner’s 3Q26 dataset (G00862072).
Decision intelligence platforms grow fastest, at 20.8%, and more than double from $2.7 billion in 2026 to $5.7 billion in 2030. The subsegment is small, but it sits closest to the agentic pattern Gartner describes: software that recommends or takes decisions rather than reporting on them.
Cross-CRM is the more important signal. It grows 18.9% a year and doubles from $27.5 billion to $55.7 billion. That is $28.1 billion of new spending, or 24% of CRM’s total gain. Cross-CRM is the closest thing in this dataset to the cross-functional integration Gartner expects agentic AI to drive.
Customer service and support remains the largest CRM subsegment, reaching $89.7 billion at 13.1%. Marketing reaches $68.1 billion at 12.8%. Sales grows slowest inside CRM, at 11.8%, to $50.2 billion.
Analytics and BI platforms grow 15.0% to $49.4 billion. Within supply chain management, orchestration platforms (14.3%) and procurement (14.2%) lead.
ERP is the market where the subsegment split matters most. HCM grows 13.5% and reaches $78.5 billion by 2030, 60% of all ERP spending. It accounts for $31.7 billion, or 66%, of ERP’s $47.9 billion gain.
The rest of ERP grows slowly. Financial management systems components grow 9.7% to $41.8 billion. Enterprise asset management grows 8.0% to $4.6 billion. Core manufacturing and operations management grows 6.7% to $6.0 billion, the slowest of all 23 subsegments.
That fits Gartner’s list of where early agentic value is showing up. HCM made the list. Finance, asset management and manufacturing operations did not.
North America reaches $461.9 billion in 2030, 56.8% of worldwide spending, and grows 13.1% a year. It captures $180.9 billion, or 57.2%, of the market’s new spending.
Europe grows 10.2%, the slowest of any region, and its share drops from 23.3% in 2026 to 22.0% in 2030.
The fastest growth is in Asia. Emerging Asia/Pacific grows 19.2% to $25.9 billion, and China grows 17.1% to $37.3 billion. Together they add $30.7 billion and lift their combined share from 6.6% to 7.8%.
Gartner revised growth for only two markets. Email and authoring rose 0.5 to 0.6 percentage points a year. Content services rose 0.2 to 2.0 points a year, including 1.4 points in 2026. Gartner says growth trajectories for every other market are unchanged.
In U.S. dollars, the total forecast is $657 million lower for 2026 and $2.5 billion lower for 2027 than in 2Q26, then $3.3 billion higher by 2030. The 2030 gains are concentrated in content services (+$1.73 billion) and email and authoring (+$1.72 billion). Exchange rates explain the remaining dollar movement in markets where growth rates did not change.
Gartner also repeats a note on the war in the Middle East. It expects disruption to the Strait of Hormuz to continue into 2027 and energy prices to stay more than 50% above pre-war levels. Gartner expects the main near-term IT spending impact to be a rebalancing of sourcing strategies, vendor relationships and regional exposure, not a material reduction in spending.
Gartner reports growth in constant currency, using 2024 exchange rates as the base. Market sizes are in current U.S. dollars, so 2026 spending rises 13.9% in dollars but 12.7% in constant currency. I use constant-currency CAGRs throughout and dollar values for sizes, dollars added and shares.
The $116 billion cannibalization figure comes from a separate Gartner report cited in this forecast. I compare it with CRM’s dollar gain to show scale, not to suggest that one offsets the other.
How large is the enterprise application software market in 2026? Gartner forecasts $496.3 billion in end-user spending in 2026, up 12.7% in constant currency.
How large will it be in 2030? Gartner forecasts $812.6 billion in 2030, a 12.8% CAGR in constant currency from 2025 to 2030.
Which market is largest? CRM, at $289.8 billion in 2030, or 35.7% of the total.
Which segment grows fastest? Decision intelligence platforms, at a 20.8% CAGR. Among the eight markets, analytic platforms grow fastest at 14.5%.
How will agentic AI affect application software spending? Gartner says agentic AI drives growth, with early value in CRM, analytics and HCM. It also says cross-functional agentic AI will cannibalize $116 billion from traditional application software spending by 2030.
Market totals, growth revisions and quotes come from Gartner’s 3Q26 enterprise application software forecast (G00862072). Subsegment and regional figures come from the dataset Gartner publishes with the report, which covers eight markets, 23 subsegments, nine regions and 2024 to 2030. I calculated constant-currency CAGRs from 2025 to 2030, dollars added from 2026 to 2030, and market and regional shares. Charts are my own work from that data.
Earlier analysis in this series:
This post is my personal analysis of Gartner’s research and does not represent my employer.
Oct 5
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).
For the 2Q26 update that first counted securing AI inside the forecast, see Gartner’s $248.2B security forecast makes securing AI the only segment accelerating through 2030.
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 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.
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.
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.
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.
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.
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%.
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.
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.
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.
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.
Endpoint protection platforms (enterprise). +$11.7 billion, from $21.3 billion to $32.9 billion.
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.
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.
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.
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.
I covered the full AI-amplified forecast in Gartner’s AI security forecast exposes 162x services growth that still trails software 2 to 1 in new spending.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
Earlier analysis in this series:
For each month’s AI agent attacks, exploited CVEs and breaches with primary sources, see my monthly AI security news briefing.
This post is my personal analysis of Gartner’s information security research and does not represent my employer.
Sep 21
Agentic workflows will drive 50% of generative AI model revenue by 2030, up from 5% in 2025. Gartner published that projection on September 17, 2026, in its forecast analysis of the generative AI models market (G00861842). The number changes how every enterprise buyer should read the firm’s $239 billion AI platforms and models forecast.
Multistep reasoning, tool integration, and repeated validation steps multiply the inference events behind every completed business process. Gartner puts the impact at $38 billion in additional spending by 2030 from scaling agentic workflows alone.
Falling inference prices won’t offset it. Cheaper units unlock deeper automation, and deeper automation drives up token volume per task faster than prices fall. Gartner calls this a structural tailwind for GenAI model spending.
That consumption flywheel sits inside a market growing from $39 billion in 2025 to $239 billion by 2030 at a 42.8% compound rate, per Gartner’s June 25 forecast (G00855897). I built this analysis from both Gartner reports and Gartner’s country-level dataset, which covers 1,316 rows across 9 regions and 7 years. For the agentic spending crossover that sets up this post, see Gartner’s $5.95 trillion AI forecast puts the chatbot era on a 2027 deadline (August 5, 2026).
Dollar figures are current U.S. dollars. Gartner reports growth in constant currency, so its rates won’t always match growth calculated from the dollar totals. The regional CAGRs here are my calculations from Gartner’s dollar data.
Gartner splits the market into two halves. AI platforms grow from $26.3 billion in 2025 to $100 billion by 2030, a 30.0% CAGR. GenAI models grow from $13 billion to $139.2 billion, a 59.9% CAGR.
GenAI models overtake AI platforms in 2027. By 2030, models command 58% of total spending.
Gartner maps all four segments by 2030 market size and CAGR. Foundation GenAI models reach $105.4 billion at a 55.2% CAGR. DSLMs reach $33.9 billion at 83.4%, the fastest growth rate in the forecast.
Data science and ML platforms carry roughly three times the spending of app development platforms. The ratio rises from about 2.8 to 1 in 2025 to 3.3 to 1 in 2030.
Domain-specific language models and specialized GenAI models grow at an 83.4% CAGR from 2025 to 2030. That outpaces foundation models at 55.2% and AI platforms at 30.0%. The segment goes from $1.6 billion in 2025 to $33.9 billion by 2030.
The share shift tells the structural story. DSLMs were 5.5% of GenAI model spending in 2024. By 2030 they will command 24.3%.
Gartner’s growth rates for DSLMs decelerate from 452.0% in 2025 to 34.5% in 2030. The dollar additions do the opposite. Each year adds more net new spending than the last, climbing from $1.3 billion to $8.6 billion.
The 2Q26 revisions confirm the direction. Gartner raised its 2030 DSLM forecast by $14.3 billion and cut its 2030 foundation model forecast by $32.1 billion. The pattern holds in every year. DSLM revisions climb from $189 million for 2025 to $1.3 billion for 2026 to $14.3 billion for 2030. Foundation model revisions run negative every year, from $2.7 billion for 2025 to $32.1 billion for 2030.
Gartner’s September analysis names agentic workflows as the single largest driver of GenAI model spending growth through 2030. The mechanism runs on volume, not price.
Agentic workflows consume more tokens per completed task than conversational AI. Each autonomous process generates multiple inference events as task complexity rises, demanding advanced reasoning, larger context windows, and repeated validation. I tracked the agentic spending crossover in Gartner forecasts agentic AI will overtake chatbot spending by 2027 (February 16, 2026). The September data shows the trajectory accelerating.
Gartner identifies three forces operating at once. Agentic workflows add $38 billion. Multimodal expansion adds $32 billion. Open-weight substitution and inference internalization remove $25 billion. The net effect grows the revenue pool while shifting where the money lands.
Gartner expects two or three suppliers to dominate the GenAI LLM marketplace in North America and Asia/Pacific by 2030. It forecasts the top two vendors will hold 85% of the foundation model revenue pool in those regions. The firm’s 2025 market share data shows Anthropic, OpenAI, and Google together accounted for 63% of enterprise spending.
The concentration thesis goes beyond model quality. Sustained investment in model development, inference capacity, reliability, security, integration, and global distribution creates a cost structure that favors vendors able to keep reinvesting at scale.
Gartner places GenAI in the Trough of Disillusionment in 2026. In that phase, enterprises lean toward frontier models delivered through their incumbent SaaS providers. That preference narrows the field for standalone frontier model companies and sets up a winner-take-all race to become the model provider software vendors choose. For how every credible forecast sizes this market, see my roundup of agentic AI forecasts and market estimates, 2026.
North America holds near 54% of worldwide spending from 2024 through 2030. Spending rises from $13.2 billion in 2024 to $130 billion in 2030, a 43.4% CAGR from a 2025 base of $21.5 billion.
The United States alone reaches $33.1 billion in 2026 and $123 billion by 2030. Gartner’s China region, which includes Hong Kong and Taiwan, grows fastest of the three at a 58.3% CAGR, from $4.1 billion in 2025 to $40.9 billion in 2030. Europe grows at 40.8% to $45.1 billion, with the United Kingdom at $4.8 billion in 2026, France at $2.2 billion, and Germany at $1.9 billion.
Gartner projects 30% of routine, high-volume enterprise GenAI inference will run on open or enterprise-controlled models by 2030, up from 5% in 2025. That substitution takes $25 billion out of the GenAI model revenue pool by 2030.
Production traffic already shows the split. Vercel’s AI Gateway routes tens of trillions of tokens a month between production applications and AI labs. In August, open-weight models processed 56% of gateway tokens but accounted for 14% of estimated spending, according to Vercel’s September production index. In December 2025, open-weight token share was 7%.
The mix is moving fast. In a post Chamath Palihapitiya amplified on September 19, Guillermo Rauch reported a snapshot of 78.4% open-weight and 21.6% closed-weight token volume.
Vercel’s September 18 daily export shows DeepSeek V4.1 Flash at 59.3% of all token volume. GLM 5.3 Flash took 7.5%, DeepSeek V4 Flash 0731 took 2.7%, and Kimi K3 took 2.5%.
Spending looks different. Anthropic accounted for 64% of estimated gateway spend in August. In July, Anthropic took 65.1% of spend on 30% of token volume, and its average price per token ran 4.4 times the average across every other lab.
The September 18 export makes the gap concrete. Claude Opus 4.8 accounted for 13.7% of estimated spend, Claude Opus 5 for 9.0%, Claude Sonnet 5 for 5.5%, and Claude Sonnet 4.6 for 4.3%. DeepSeek V4.1 Flash, with 59.3% of tokens, accounted for 5.1% of spend.
Vercel’s data covers traffic routed through its gateway, not the whole market. Its spend figures are estimates based on list prices. It shows the same pattern Gartner forecasts but doesn’t prove Gartner’s $25 billion number.
For buyers, the lesson is to budget for workload mix, not token volume alone. The models moving the most tokens aren’t the ones capturing the most spend. Route suitable workloads to lower-cost models and save premium models for work that justifies the price.
Palihapitiya went further on September 19, predicting the top three models would be open source within 12 months. He named Nebius, Iren, Baseten, Together, and Fireworks as the clouds he expects to benefit. That’s his forecast, not something the usage data establishes.
Gartner reports AI budgets are getting a harder look, and money is moving to providers that can prove their value on cost, speed, and reliability. Here are five takeaways for leaders making AI platform and model decisions over the next 12 months. For how security spending fits this picture, see Gartner’s $248.9B security forecast makes securing AI the only segment accelerating through 2030 (July 6, 2026).
Gartner’s forecast puts a number on the tension running through every enterprise AI budget. The market nearly quadruples from $64 billion in 2026 to $239 billion by 2030. Agentic workflows drive half of GenAI model revenue by the end of that window.
Open-weight models absorb a growing share of token volume while frontier providers keep the lion’s share of spend. The $38 billion agentic addition and the $25 billion revenue pool reduction pull the market in two directions at once.
Enterprises that build for model routing, budget for agentic consumption, and negotiate multiyear commitments with the surviving frontier providers will be better positioned in 2030. Enterprises that treat AI spending as a single-vendor procurement decision will not.
This post is my personal analysis of Gartner’s AI platforms, models, and generative AI research and does not represent my employer.
Apr 1
$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.
Mar 28
Palo Alto Networks spent $29 billion acquiring three companies. ServiceNow spent $11.6 billion on three more. Alphabet paid $32 billion for Wiz. The startups building agentic AI defenses raised $3.6 billion. Total MCP security funding for 17,000+ deployed servers: $40 million. Then RSAC 2026 happened.
Mar 24
Inside the $244.2 billion security market: agentic AI adoption outpaces defenses 8 to 1, cloud security grows at 28.8%, and enterprises spend 17x more on AI tools than on securing the AI itself
Gartner forecasts worldwide AI spending will reach $2.52 trillion in 2026, a 44% increase year-over-year. Worldwide IT spending will hit $6.15 trillion. Within that massive build-out, information security spending accelerates to $244.2 billion, up 13.3%.
The headline looks healthy. Look closer, and it isn’t. I’ve been tracking Gartner’s information security forecast through multiple quarterly updates, and the trajectory keeps steepening. But the spending acceleration is masking a deeper problem: enterprises are deploying AI agents into production far faster than they are securing them.
Gartner predicts 40% of enterprise applications will include task-specific AI agents by the end of 2026. Up from less than 5% in January. These are not chatbots. Gartner’s examples include autonomous cybersecurity response agents that scan network traffic, analyze system logs, and initiate responses without human intervention.
Only roughly 6% of organizations report having an advanced AI security strategy in place, according to vendor-sourced research from BigID’s 2025 AI Risk and Readiness study. Even adjusting for methodology differences between vendor and analyst research, the gap is stark. Agents are entering production at roughly 7-8x the rate organizations are building governance around them.
Gartner’s 4Q25 AI spending forecast created a dedicated agentic AI market segment for the first time. The spending lines are dramatic. Agentic AI overtakes chatbot and assistant spending by 2027. By 2029, agentic AI will reach $752.7 billion at a 119% compound annual growth rate. Chatbot spending peaks at $264.7 billion, then declines. That crossover point is where the security model breaks, because chatbots operate within human-supervised sessions. Agents don’t.
Gartner named agentic AI oversight the number-one cybersecurity trend for 2026 in its February report (my breakdown of all six trends here). A separate Gartner poll of 147 CIOs found 24% had already deployed AI agents and 50% were actively experimenting. Guardian agents, AI systems designed to monitor and govern other AI agents, are projected to capture 10-15% of the agentic AI market by 2030.
Forrester’s 2026 cybersecurity predictions go further: an agentic AI deployment will cause a publicly disclosed data breach this year, leading to employee dismissals. Senior analyst Paddy Harrington frames it as a cascade of failures, not a single point of error. That prediction landed in October 2025. Nothing since has made it less likely.
Gartner’s 4Q25 information security forecast projects global spending reaching $244.2 billion in 2026, up 13.3% year-over-year. That is acceleration, not continuation. Gartner’s forecast trajectory has been steepening for multiple quarters. It follows a year where many CISOs focused on consolidating tools rather than buying new ones.
The allocation matters more than the total (please click on the graphic to expand for easier reading):
Cloud security at 28.8% growth is the fastest subsegment by a wide margin. CSPM alone carries a 31.3% CAGR. These represent organizations reacting to attack surfaces that expanded when workloads moved to the cloud faster than security controls followed.
Managed security services at 11.1% tells a workforce story the spending headline misses. The ISC2 documented a global cybersecurity workforce gap of 4.8 million professionals in October 2024. That gap grew 19% year-over-year while the active workforce flatlined at 5.5 million. A quarter of organizations reported cybersecurity layoffs. So they’re buying SOC capacity from managed providers instead. The spending growth in managed services is a staffing problem wearing a procurement mask.
Gartner’s 4Q25 AI spending forecast splits the AI cybersecurity market into two sub-segments for the first time. AI-amplified security, using AI to defend the enterprise, reached $49 billion in 2025. Securing AI itself, protecting the models, training data, inference pipelines, agent workflows, and decision outputs, stood at $2.8 billion. That is 5.5% of the AI cybersecurity market.
Enterprises are investing 17 times more in AI-powered security tools than in securing the AI on which those tools run. Gartner projects over 75% of enterprises will use AI-amplified cybersecurity products by 2028, up from less than 25% in 2025. The tools are getting funded. What the tools actually depend on to function is not.
Forrester predicts quantum security spending will exceed 5% of overall IT security budgets in 2026. Five percent sounds modest until you consider what it represents: the shift from research line items to actual procurement.
That means consulting engagements for quantum migration planning. Cryptographic discovery tools to figure out which systems need replacing first. Post-quantum algorithm testing across live production environments. Gartner calls post-quantum cryptography a force that demands organizations identify, manage, and replace traditional encryption methods now. Not eventually. The encryption market is growing at 2.0x according to the 4Q25 forecast, and the planning horizon is 2030. Starting migration in 2028 means compounding rip-and-replace costs every quarter of delay.
Forrester also predicts the EU will establish its own known exploited vulnerability database in 2026. Regulatory fragmentation adds cost. For enterprises operating across jurisdictions, quantum migration planning cannot be separated from compliance architecture.
A smaller Gartner survey of 175 employees conducted between May and November 2025 found that 57% use personal GenAI accounts for work. A third admitted to uploading sensitive information to tools their organizations have not sanctioned.
I keep coming back to this stat because it reframes the entire agentic AI security conversation. The firewalls most enterprises rely on were built for human-to-application communication. Protocols like MCP now enable agent-to-agent interaction at a scale and speed those tools were never designed to see. Machine identities outnumber human employees by more than 80 to 1 in most enterprises, according to CyberArk. Traditional IAM was not built for nonhuman actors operating autonomously.
Gartner’s cybersecurity trends report identifies IAM adaptation for AI agents as a top-six trend for 2026, specifically calling out identity registration, credential automation, and policy-driven authorization for machine actors. Failure to address these issues will lead to greater access-related cybersecurity incidents as autonomous agents become more prevalent.
Gartner places AI in the Trough of Disillusionment throughout 2026. AI will most often be sold by incumbent software providers rather than bought as part of new moonshot projects. ROI predictability has to improve before enterprises scale their deployments.
Forrester’s 2026 predictions reinforce this: enterprises will defer 25% of planned AI spending into 2027 as financial rigor slows production deployments and kills proofs of concept. Fewer than one-third of decision-makers can tie AI value to their organization’s financial growth.
Yet Gartner’s IT spending forecast shows server spending accelerating at 36.9% year-over-year and data center spending surging 31.7% past $650 billion. GenAI model spending grows at 80.8%. The infrastructure build-out is not slowing even as enterprise application adoption pauses.
Infrastructure spending runs hot. Application-layer AI spending cools. Security spending accelerates into the gap between adoption speed and governance readiness. The $244.2 billion flowing into information security is the cost of operating in an environment where AI agents are proliferating faster than the controls designed to govern them.
For two decades, enterprise security assumed a human on the other end of every session, every credential request, every decision. That assumption is collapsing. The autonomous agent accessing your production database at 3 AM doesn’t authenticate the way your SOC analyst does, doesn’t respect the same governance boundaries, and operates at speeds no human reviewer can match.
What makes this moment different from previous security inflection points is the speed asymmetry. When cloud migration created new attack surfaces, enterprises had years to adapt. The shift from on-prem to cloud took a decade. The shift from human-operated to agent-operated environments is measured in quarters. Gartner didn’t even have a dedicated agentic AI spending segment until this forecast cycle. By the next one, the crossover will have already happened.
The practical question for 2026 is not whether to invest in AI security. That decision has been made by the spending trajectory. It is whether to govern AI agents proactively, before the first publicly disclosed agentic breach forces a reactive scramble, or to wait and pay the premium that every late mover in cybersecurity history has paid. Forrester has already predicted which outcome is more likely this year. The 17:1 ratio suggests most enterprises are betting on the wrong side of that question.
Gartner Forecast: Information Security, Worldwide, 2023–2029, 4Q25 (December 18, 2025)
Gartner Forecast Analysis: Information Security, Worldwide, 2026 (February 5, 2026)
Gartner Forecast: AI Spending, Worldwide, 2024–2029, 4Q25 (December 2025)
Gartner, Top Trends in Cybersecurity for 2026 (February 5, 2026)
Gartner, Worldwide AI Spending Will Total $2.52 Trillion in 2026 (January 15, 2026)
Gartner, Worldwide IT Spending to Grow 10.8% in 2026 (March 2026)
Gartner, 40% of Enterprise Apps Will Feature AI Agents by 2026 (August 26, 2025)
Gartner, Guardian Agents Will Capture 10-15% of Agentic AI Market by 2030 (June 11, 2025)
Forrester Predictions 2026: Cybersecurity and Risk (October 28, 2025)
Forrester, Global Tech Spend Will Grow 7.8% in 2026 (February 2, 2026)
Forrester, 2026 Technology & Security Predictions (October 28, 2025)
ISC2, 2024 Cybersecurity Workforce Study (October 2024)
CyberArk, Machine Identities Report (April 2025)
BigID, AI Risk & Readiness in the Enterprise (2025)
Feb 26
Agentic AI spending is projected to reach $201.9 billion in 2026 (Gartner), overtaking chatbot spending by 2027.  Four independent firms size the standalone market at $7–8 billion with 40%+ CAGRs. But adoption lags the money: only 23% of organizations have scaled agent deployments (McKinsey), and 40% of projects face cancellation by 2027 (Gartner).
Fortune Business Insights projects $7.29 billion in 2025, reaching $139.19 billion by 2034 at 40.5% CAGR. Precedence Research sizes it at $7.55 billion in 2025, growing to $199.05 billion by 2034 at 43.84% CAGR. MarketsandMarkets puts the figure at $7.06 billion in 2025, reaching $93.20 billion by 2032 at 44.6% CAGR. Deloitte’s TMT Predictions 2025 estimates $8.5 billion in 2026, growing to $35 to $45 billion by 2030.
Every major forecast agrees on direction. None agrees on scale. The standalone agentic AI market lands between $7 billion and $8.5 billion. Gartner’s broader view, counting agentic capabilities embedded across enterprise software, reaches $201.9 billion in 2026. That 25x gap is not a contradiction. It is a measurement problem, and the takeaways below reflect both realities. The following are the key takeaways from agentic AI forecasts published in 2026 so far:
Worldwide AI spending will reach $2.52 trillion in 2026, growing 44% year-over-year. That number jumped roughly $500 billion from the September forecast, which had pegged the market just above $2 trillion. Infrastructure takes $1.37 trillion, 54% of total spend. AI software follows at $452.5 billion, up 60%. AI services add $588.6 billion. AI-optimized servers alone account for $421.6 billion, growing to 49%. Gartner expects spending to grow by another 30% in 2027 and surpass $3 trillion. I have tracked these forecasts through multiple iterations. The revisions keep going in one direction. Source: Gartner press release, January 15, 2026
Gartner projects $4.71 trillion in global AI spending by 2029. The fastest growth isn’t in infrastructure. Synthetic data generation leads all categories at 178% CAGR, followed by the broader AI Data market at 155%. Agentic AI compounds at 119%, expanding from $15 billion to $753 billion by 2029. AI Infrastructure, the largest category by dollars, grows at just 29%. The money is following the bottlenecks. Source:Â Gartner 4Q25: $4.71T AI Market Proves Agentic AI and Data Readiness Are the Only Race That Matters, Software Strategies Blog, January 22, 2026 Link: https://softwarestrategiesblog.com/2026/01/22/gartner-4q25-agentic-ai-data-readiness-4-71t-market/
The AI cybersecurity market is predicted to hit $51.3 billion in 2026, nearly doubling from $25.9 billion in 2025. But the category masks a structural imbalance. AI-amplified security, where AI defends the enterprise, captures 94.5% of spending at $48.5 billion. Securing AI, where the enterprise defends its own AI systems, gets $2.8 billion. Enterprises are investing 17x more in using AI as a security tool than in protecting the AI itself. Both sub-segments grow at similar CAGRs (74% vs. 72%), which means the dollar gap widens every year. By 2029, AI-amplified security reaches $160.4 billion, while securing AI hits just $11.6 billion. One is a tool. The other is the thing that needs protecting. Source: Gartner Forecasts Agentic AI Will Overtake Chatbot Spending by 2027, Software Strategies Blog, February 16, 2026 Link: https://softwarestrategiesblog.com/2026/02/16/gartner-forecasts-agentic-ai-overtakes-chatbot-spending-2027/
AI Data sits alone in the upper-right quadrant of Gartner’s spending map, compounding at 155% CAGR with 277% growth in 2026. AI Cybersecurity and AI Models cluster above 67% CAGR. AI Infrastructure anchors the chart as the largest bubble, but grows at just 29%. Global AI spending reaches $1.8 trillion in 2025 and $4.7 trillion by 2029. The acceleration is not in compute. It is in data readiness, security architecture, and agentic capabilities. By 2028, software with agentic capabilities crosses 50% of total application software spend, up from 2% in 2024. Non-agentic software spending starts declining in 2027. Source:Data Readiness and Security Are Driving AI’s $4.7 Trillion Run, Software Strategies Blog, December 22, 2025 Link: https://softwarestrategiesblog.com/2025/12/22/data-readiness-security-driving-ai-4-7-trillion/
Gartner’s AI spending forecast reaches $2.53 trillion in 2026 and $4.71 trillion by 2029. Eight markets. One pattern. AI Infrastructure dominates absolute dollars at $1.37 trillion in 2026 but grows at just 29% CAGR. AI Data, the smallest segment at $3.1 billion, compounds at 155%. AI Cybersecurity nearly doubles to $51.3 billion. AI Software hits $452.5 billion, growing 60% year-over-year as agentic capabilities reshape the category. The growth rates tell you where the bottlenecks are breaking. Source: Data Readiness and Security Are Driving AI’s $4.7 Trillion Run, Software Strategies Blog, December 22, 2025 Link: https://softwarestrategiesblog.com/2025/12/22/data-readiness-security-driving-ai-4-7-trillion/
Nearly nine in ten organizations now use AI in at least one business function, up from 78% a year ago, but nearly two-thirds have not begun scaling it across the enterprise. Only 6% qualify as high performers where AI contributes more than 5% to EBIT. Sixty-two percent of organizations are at least experimenting with AI agents, yet in no individual business function are more than 10% scaling them. High performers are three times more likely than peers to fundamentally redesign workflows and three times more likely to have senior leaders demonstrating ownership of AI initiatives. More than one-third of high performers commit over 20% of their digital budgets to AI, and about three-quarters have reached the scaling phase, versus one-third of other organizations. Source: McKinsey / QuantumBlack, The state of AI in 2025: Agents, innovation, and transformation, November 2025
Valued at $638.23 billion in 2024, the global AI market is projected to reach $3,680.47 billion by 2034, expanding to a CAGR of 19.20%. North America holds 31.80% market share. The software segment dominates at 51.40%, while machine learning leads by technology at 36.70%. Healthcare is expected to record the highest CAGR of 36.50% across end-use segments. Among regions, Asia-Pacific is expected to grow at 19.8% CAGR from 2025 to 2034, with AI projected to add up to $3 trillion to the region’s GDP by 2030, driven by national AI strategies in China, India, and Japan. Source: Precedence Research, AI Market Size, Growth & Trends, September 2025
Nearly $7 trillion. That’s the capital outlay data centers will require by 2030 to keep pace with demand for compute power. Of that, $5.2 trillion goes toward AI-ready facilities and $1.5 trillion toward traditional IT workloads. Global demand for data center capacity could almost triple by 2030, with about 70% of new demand coming from AI workloads. Three investment scenarios range from $3.7 trillion (constrained demand) to $7.9 trillion (accelerated demand, adding 205 incremental GW). The 60% majority of investment—$3.1 trillion—flows to technology developers and designers producing chips and computing hardware. Source: McKinsey, The cost of compute: A $7 trillion race to scale data centers, April 2025
Inference already consumed half of all AI compute in 2025. That number will grow to two-thirds in 2026 and reach 75% of all AI compute needs by 2030. Global data center capacity is projected to nearly double from 103 gigawatts to 200 GW by 2030, yet U.S. data centers already face a capacity shortfall exceeding 11 GW, with the cumulative gap expected to exceed 40 GW by 2028. North American data center capacity alone will increase eightfold, from 5.6 GW in 2024 to 44 GW by 2030. Operators are increasingly deploying edge facilities closer to end users to reduce latency as inference-dominated workloads drive a fundamental redesign of data center architectures. Source: Avid Solutions, 13 Data Center Growth Projections, January 2026
Generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually to the global economy, increasing the projected impact of all AI by 15 to 40%. About 75% of the value falls across four areas: customer operations, marketing and sales, software engineering, and R&D. Half of today’s work activities could be automated between 2030 and 2060, with a midpoint in 2045—roughly a decade earlier than previously estimated. When embedding effects in existing software are included, the total economic benefit rises to $6.1 trillion to $7.9 trillion annually. Source: McKinsey, The economic potential of generative AI, June 2023
The global AI market hit $294.16 billion in 2025 and is projected to grow to $2,480.05 billion by 2034, at a CAGR of 26.60%. The Banking, financial services and insurance (BFSI) segment holds 18.90% market share, while healthcare is expected to record the highest CAGR of 36.50%. In the U.S. alone, the AI market was estimated at $146.09 billion in 2024 and is predicted to reach $851.46 billion by 2034. The number of AI companies funded globally in 2024 totaled 2,049, with U.S.-funded companies accounting for 1,143, signaling strong investor confidence in the sector’s expansion potential. Source: Fortune Business Insights, AI Market Size, Growth & Trends by 2034
Big Tech’s AI capex hit $405 billion in 2025, up from a $250 billion estimate at the start of the year. Sell-side analysts have underestimated AI spending every quarter for two years running. A decade ago, Big Tech’s trailing-twelve-month capex was $24 billion—15x less than today. AI data center costs are projected at $3 trillion to $8 trillion, with gigawatt capacity expected to grow 3.5x by 2030. Source: IO Fund, Big Tech’s $405B Bet, November 2025
The global AI market was valued at $371.71 billion in 2025 and is projected to reach $2,407.02 billion by 2032, growing at a CAGR of 30.6%. Hyperscalers accounted for 53% of chip purchases in 2023, spurring 156% market growth from 2023 to 2024. While demand from hyperscalers is expected to moderate, growth of 41% is still forecast from 2025 to 2026. Enterprises are moving from cloud reliance to in-house AI infrastructure investments, particularly for cost-effective inference solutions, as edge AI gains traction through AI-enabled PCs and mobile devices. Source: Markets and Markets, AI Market Report 2025-2032
At $602 billion projected for 2026, hyperscaler capex has entered uncharted territory. Amazon, Microsoft, Google, and Meta will each exceed $100 billion individually, pushing capital intensity to 45-57% of revenue. Total hyperscaler capex from 2025-2027 is projected at $1.15 trillion, more than double the $477 billion spent from 2022-2024. Morgan Stanley and JP Morgan suggest the technology sector may need to issue $1.5 trillion in new debt over the next few years to finance AI infrastructure construction. The sheer scale of debt issuance mirrors patterns seen during the fiber-optic buildout of the late 1990s. Source: Multiple sources compiled by Introl, January 2026
The number of software companies using consumption-based pricing more than doubled between 2015 and 2024, as AI introduces new variable costs that make traditional perpetual licenses obsolete. SaaS remains dominant, but the next wave is outcome-aligned pricing that scales with actual AI usage. Software businesses that successfully adopt consumption-based pricing aligned with usage and outcomes may be better positioned to capture AI-driven value and differentiate themselves in a rapidly evolving market where the cost of each AI inference adds a new variable to the P&L. Source: McKinsey, AI adjusts the software bill, January 27, 2026
Data center capacity needs for AI and non-AI workloads could almost triple by 2030, with AI capacity increasing 3.5 times and making up roughly 70% of the total. Under a continued-momentum scenario, total capacity demand rises from 82 GW in 2025 to 219 GW by 2030, with incremental AI capacity ranging from 13 GW in 2025 to 31 GW in 2030, totaling 124 GW of new AI capacity. Non-AI workloads grow from 38 GW to 64 GW over the same period. Average power densities in AI-ready data centers have more than doubled in just two years and are expected to rise nearly four times by 2027. Source: McKinsey, Data center demands (Week in Charts), May 2025
U.S. data-center spending exceeded half a trillion dollars in 2025. The U.S. and China drove a massive expansion in AI-related computing capacity through 2024, with the U.S. pulling further ahead in the first half of 2025. AI-related trade accounted for nearly half of all merchandise trade growth in that period, despite representing only 15% of total trade volume. The infrastructure boom is reshaping international commerce, with surging demand for servers, graphics cards, and related components essential to AI training and inference now a dominant force in global supply chains. Source: Federal Reserve Board, FEDS Notes: The Global Trade Effects of the AI Infrastructure Boom, February 2026
The generative AI market is expanding from $71.36 billion in 2025 to $890.59 billion by 2032, at a CAGR of 43.4%. North America accounted for 43.05% of global revenue in 2025. Text remains the dominant data modality due to its foundational role in enterprise workflows, while the services segment is gaining traction for scalability and cost-effectiveness. Foundation model delivery platforms verticalized adoption across industries, and the rapid scaling of AI-native infrastructure are the three key forces driving the market as of 2025. The 43.4% CAGR makes this one of the fastest-expanding technology subsegments in history. Source: MarketsandMarkets, Generative AI Market Report, Global Forecast to 2032
The generative AI market reached $37.89 billion in 2025 and is projected to hit $1.2 trillion by 2035, a 37% compound annual growth rate. Transformer architectures account for more than 42% of technology revenue, driven by text-to-image and text-to-video applications. Software captures over 65% of total revenue. North America holds 41% of the market. Asia-Pacific is the fastest-growing region at a 27.6% CAGR through 2035. Financial services is expected to lead sector growth at 36.4%, fueled by fraud detection, risk management, and regulatory compliance demands. Source: Precedence Research, Generative AI Market Size, January 2026
GPUs captured 89% of AI processor revenue in 2025, but FPGA and ASIC alternatives are growing at a 17% CAGR through 2031. Hardware accounted for 68% of all AI infrastructure spending last year. North America held 40% of the market, backed by $52.7 billion in CHIPS Act grants and hyperscalers operating roughly 60% of global AI compute capacity. Liquid cooling reached 18% of AI server racks as power densities crossed 100 kilowatts per rack, the threshold where air cooling fails. Asia-Pacific is projected to grow fastest at 16.4% CAGR through 2031, driven by China’s $50 billion semiconductor fund and $15 billion in hyperscaler commitments across India. Source: Mordor Intelligence, AI Infrastructure Market Size, Trends & Growth Drivers 2031
Nearly one in four Americans has already made a purchase through AI. Morgan Stanley Research estimates agentic shoppers will drive $190 billion to $385 billion in U.S. e-commerce spending by 2030, capturing 10% to 20% of market share. Grocery and consumer packaged goods lead adoption, with 49% of AI-assisted buyers transacting in those categories. AI shopping agent users are projected to reach 126 million by 2030, up from near zero today, while traditional e-commerce users decline from 264 million to 149 million over the same period. Source: Morgan Stanley Research, Agentic Commerce Market Impact Outlook, December 2025 Link: https://www.morganstanley.com/insights/articles/agentic-commerce-market-impact-outlook
