Where is AI Spending Going in 2026? (27 Data to Understand)

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AI spending is hitting levels nobody predicted just 12 months ago.

Total global investment will hit $2 trillion in 2026.

We analyzed 27 data points to see where the money is going. Here's our market report about AI Wrappers.

In our 200+-page report on AI wrappers, we'll show you the real user pain points that don't yet have good solutions, so you can build what people want.

Where AI Spending Is Going in 2026

• 1. AI captures 63% of all venture capital investments

  The Data:

  AI startups got 63% of all venture capital in the 12 months through Q3 2025. That's up from 40% in 2024 and 23% in 2020. AI startups are now worth $2.30 trillion combined. That jumped from $1.69 trillion in 2024 and just $469 billion in 2020. Big funding rounds of $100 million or more made up 69% of AI funding in 2024. 32 new AI companies hit $1 billion valuations, which was nearly half of all new unicorns created.

  What This Means:

  Almost two-thirds of all VC money now goes to AI. This creates a cycle where top talent and resources all move toward AI companies. The $2.3 trillion valuation is huge (similar to a major country's economy). This tells you AI isn't a trend. It's become the main focus of the entire startup world.

  Sources: Bain

• 2. Corporate AI investments doubled to $129 billion in H1 2025

  The Data:

  Big companies invested in 2,474 AI startup funding rounds in the first half of 2025. Total money doubled to over $129 billion compared to the same period in 2024. That's 25% more deals and double the cash. Tech giants like Google and Microsoft are leading this. Chipmakers like Nvidia and Qualcomm are doing the same.

  What This Means:

  Large companies see AI startups as strategic, not just financial bets. They're investing to lock in customers and secure new AI tech before competitors do. The $129 billion in six months means the full year could hit $250 billion. These corporate partnerships give startups resources and distribution. They speed up AI innovation across the board.

  Source: Global Venturing

• 3. Hyperscalers accelerate capex beyond $400 billion baseline

  The Data:

  The four biggest US cloud companies (Google, Meta, Microsoft, Amazon) are increasing spending big in 2026. They already spent $400-450 billion in 2025. Google's CFO said they'll spend significantly more than 2025's $91-93 billion. Meta will spend notably more than 2025's $70-72 billion. Microsoft increased Q1 spending by 74% to $34.9 billion. Amazon will spend around $125 billion in 2025, mostly on AI.

  What This Means:

  These companies plan infrastructure years ahead. When they all announce bigger spending at once, it means AI demand is real and lasting. They're not just building for today. They're confident AI will make them serious money. Their AI demand is bigger than their current capacity. This creates steady demand for chips, servers, and datacenter equipment through 2026 and beyond.

  Source: CNBC

• 4. 88% of executives plan to increase AI budgets

  The Data:

  88% of executives will increase their AI budgets in the next 12 months. Over 26% will increase budgets by 26% or more. This comes from a PwC survey of 308 US senior executives. 79% say AI agents are already being used in their companies. 66% see real value through higher productivity.

  What This Means:

  Almost 9 out of 10 executives are spending more on AI. This isn't just tech companies. It's across all industries and company sizes. More than 1 in 4 are increasing budgets by over 25%. That's huge growth, not small tweaks. This means 2026 will see faster AI adoption, not a slowdown. Companies need infrastructure, software, and talent. That demand stays strong all year.

  Source: PwC


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• 5. Global AI spending reaches $2.022 trillion in 2026

  The Data:

  Worldwide AI spending will hit $2.022 trillion in 2026. That's up from $1.478 trillion in 2025 (37% growth). This includes everything AI: datacenter hardware, software, services, generative AI models, chips, and AI devices. Gartner raised this forecast during 2025. The 2026 numbers they're predicting now were originally forecasted for 2028.

  What This Means:

  AI spending is now over one-third of all global IT spending. The fact that forecasts got pushed forward by two years means demand is beating expectations. Companies might spend even more in 2026 as they race to stay competitive. This $2 trillion covers the entire stack, from chips to consumer apps. It shows AI investment isn't just one area. It's spreading everywhere.

  Source: Gartner

• 6. AI infrastructure software spending hits $230 billion

  The Data:

  AI infrastructure software spending will reach $230 billion in 2026. That's almost 4x growth from $60 billion in 2024. This includes tools for AI development: app platforms, databases, security tools, container systems, MLOps platforms, and model management systems.

  What This Means:

  Companies aren't just buying GPUs. They need software to manage AI systems. The jump from $60 billion to $230 billion shows this clearly. Running AI requires full software stacks for data, model control, security, and coordination. This creates big opportunities for enterprise software companies building AI workflow tools. If you're considering building infrastructure tools for AI workflows, our report to build a profitable AI Wrapper breaks down which tool categories are seeing the most demand.

  Source: CIO Dive

• 7. AI application software triples to $270 billion

  The Data:

  AI application software spending will reach $270 billion in 2026. That's more than triple the 2024 level. This covers business apps with AI built in: CRM systems with predictions, ERP platforms with automation, productivity tools with AI help (like Microsoft Copilot), and industry-specific AI apps. In 2026, companies will spend more on software with AI than software without it.

  What This Means:

  AI software spending tripled in two years. This shows companies are moving from infrastructure to actual applications. They're buying AI versions of every tool, from sales to finance. Software without AI is becoming obsolete. Buyers expect AI features as standard now. Companies adding AI to their products can charge more and keep customers longer.

  Source: CIO Dive

• 8. Enterprises allocate 36% of digital budgets to AI

  The Data:

  Companies spend 36% of their digital budgets on AI on average. For a company with $13 billion in revenue, that's about $700 million. This comes from Deloitte's survey of 548 business and tech leaders. Average company revenue was $13.4 billion. Digital budgets grew a lot too, from 7.5% of revenue in 2024 to 13.7% in 2025.

  What This Means:

  More than one-third of digital money goes to AI. That makes AI the main focus of tech strategy, not an experiment. For big companies, this means hundreds of millions per year on AI. The percentage keeps rising as AI proves it works. By 2026, it might hit 40% or more. AI is becoming the biggest category in IT spending.

  Source: Deloitte

• 9. Inference spending surpasses training at $20.6 billion

  The Data:

  AI cloud infrastructure will hit $37.5 billion in 2026. 55% of that ($20.6 billion) goes to inference (running AI models). That's more than training for the first time. Total spending grew 105% from 2025's $18.3 billion. Inference spending jumped from $9.2 billion in 2025 to $20.6 billion in 2026.

  What This Means:

  Inference beating training is a big deal. It means companies are done experimenting. They're running AI in production at scale now. This shift favors chips built for inference, not just training. It's reshaping what semiconductor companies build. Companies making inference tools and infrastructure will see growing demand as AI moves from labs to real use.

  Source: Gartner


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• 10. 40% of enterprise apps will feature AI agents by late 2026

  The Data:

  40% of enterprise apps will have AI agents by end of 2026. That's up from less than 5% in 2025. It's an 8x jump in one year. Gartner says agentic AI could drive 30% of enterprise software revenue by 2035 (over $450 billion).

  What This Means:

  Going from 5% to 40% in one year is one of the fastest adoption curves ever in business software. AI agents can run workflows, make decisions, and work with other systems on their own. This changes how work gets done. It automates complex processes that used to need humans. Companies without AI agents in their apps will fall behind fast.

  Source: Gartner

• 11. AI semiconductors market reaches $268 billion

  The Data:

  AI chip spending will hit $268 billion in 2026. That's up 28% from $209 billion in 2025. This covers chips made for AI work: GPUs from Nvidia and AMD, custom accelerators (like Google's TPUs and Amazon's Trainium), and specialized inference chips.

  What This Means:

  AI chips are the foundation of everything. The $268 billion (13% of total AI spending) shows compute is still the main bottleneck. The 28% growth reflects chip shortages and premium pricing. Leading GPUs cost a lot because demand is intense. As models get bigger and inference scales up, chip spending stays high. This helps chip designers, manufacturers, and the whole supply chain.

  Source: IEEE ComSoc Technology Blog

• 12. AI-optimized servers hit $329.5 billion

  The Data:

  AI server spending will reach $330 billion in 2026. That's up 23% from $268 billion in 2025. This includes complete server systems with AI chips plus high-bandwidth memory, special networking (InfiniBand, RoCE), power systems, and cooling.

  What This Means:

  Servers cost $62 billion more than the chips inside them. That shows supporting infrastructure is expensive. Building systems that can train large models and run inference at scale is complex. Cloud providers and companies are treating these as strategic assets. This creates opportunities for networking gear, memory, cooling, and power tech.

  Source: IEEE ComSoc Technology Blog

• 13. Datacenter systems spending reaches $582.5 billion

  The Data:

  Datacenter systems will hit $583 billion in 2026 (19% growth). This includes all datacenter gear: AI and regular servers, storage, networking switches, routers, and support infrastructure. Gartner raised this forecast big in 2025. The 2026 numbers now exceed what they predicted for 2028.

  What This Means:

  Near $600 billion shows AI is reshaping all IT infrastructure spending. Even traditional datacenter parts see higher demand. Companies upgrade entire facilities to handle AI's power, cooling, and networking needs. This creates opportunities beyond just AI chips: storage, switches, power units, and cooling systems. Forecasts got pushed forward two years, which means the buildout is happening faster than expected.

  Source: The Next Platform

• 14. Financial services lead industry spending at $73 billion

  The Data:

  Financial services will spend about $73 billion on AI in 2026. That's over 20% of total global AI spending. IDC shows this growing from $35 billion in 2023 to $97 billion in 2027 (29% annual growth). Banks lead the spending. Key uses: fraud detection, trading algorithms, credit risk, customer service bots, compliance, and anti-money laundering.

  What This Means:

  Financial services is the single biggest industry investor in AI. Taking 20%+ of global spending makes banks and insurers AI leaders. Their success creates templates that other industries copy. The high spending shows proven returns in finance and regulatory needs driving adoption. We analyze the financial services AI opportunity in depth in our market research report about AI Wrappers, including which specific use cases are seeing the most investment.

  Source: Statista

• 15. Healthcare AI investment exceeds $45 billion

  The Data:

  Healthcare AI will top $45 billion in 2026. Robot-assisted surgery alone is $40 billion of that. Healthcare AI jumped from $5 billion in 2020 to over $45 billion by 2026. McKinsey says AI could boost healthcare productivity by 1.8-3.2% yearly ($150-260 billion per year in the US alone). Key areas: medical imaging, drug discovery, clinical docs, treatment planning, and robot surgery.

  What This Means:

  Healthcare's $45 billion+ shows AI can tackle the sector's big problems: rising costs, burnout, access gaps, and slow drug development. AI can cut drug discovery from 4-5 years to 1-2 years. That's massive savings and faster treatments. The $40 billion robot surgery market shows willingness to buy expensive AI systems when outcomes justify it. Healthcare AI has life-or-death stakes. That speeds up testing and adoption.

  Source: OffCall


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• 16. Manufacturing AI spending hits $16.7 billion with 57% annual growth

  The Data:

  Manufacturing AI will reach $16.7 billion by 2026. It's growing at 57% yearly from $1.1 billion in 2020. This covers AI across manufacturing: predictive maintenance (cuts downtime by 30-50%), quality control, supply chain optimization, autonomous production, and generative AI for product design. But 56% of manufacturers still only run AI pilots.

  What This Means:

  Manufacturing's 57% annual growth is almost double the overall AI market. Industrial companies are catching up to tech companies fast. The shift from pilots to full production in 2026 will drive the next spending wave. AI helps manufacturing compete with low-cost labor markets through automation. Most manufacturers are still testing. That means huge upside when they go all-in.

  Source: World Economic Forum

• 17. Retail AI market reaches $17.8 billion

  The Data:

  Retail AI will hit $17.8 billion in 2026, up from $14.4 billion in 2025. It's heading to $124 billion by 2035 (24% annual growth). Retail AI includes demand forecasting (AI cuts forecast errors by 50%), inventory optimization, personalized recommendations, dynamic pricing, chatbots, and checkout-free stores. McKinsey says generative AI alone could unlock $240-390 billion for retailers.

  What This Means:

  Retail AI directly changes customer experiences. Everyone sees it. That sets expectations across all industries. The 50% improvement in forecasting means massive savings on inventory and better revenue. Early adopters will likely control 73% of the $164 billion retail AI market by 2030. That's first-mover advantage through better data and refined algorithms. Retailers without AI by 2026 risk permanent disadvantage.

  Source: Research Nester

• 18. US maintains dominance with $300 billion market

  The Data:

  US AI market will hit $300 billion in 2026 (40% annual growth). That's 30-40% of global AI spending. The US stays the largest AI market globally. It's driven by top tech companies, strong venture capital, advanced research, and early enterprise adoption. The US leads in foundation models, AI chip design, and commercial deployment.

  What This Means:

  US dominance reinforces American tech leadership. The $300 billion market attracts global talent and money. This creates network effects that strengthen everything. But the US share is dropping from over 50% to 30-40%. China and Europe are catching up. This sets up geopolitical competition for AI supremacy. It might split the global AI market into regional systems.

  Source: Keywords Everywhere

• 19. China's AI investment reaches $27 billion with hardware focus

  The Data:

  China will spend nearly $27 billion on AI in 2026 (8.9% of global spending). Hardware is over $15 billion (56% of China's total). IDC shows China more than doubling AI investment from before, growing at 27% yearly from 2021-2026. Top uses: customer service agents, public safety, emergency response, and biometric systems.

  What This Means:

  China's $27 billion shows the government treating AI as strategic for economy and military. The 56% hardware focus means China is building its own AI infrastructure. They want less dependence on Western tech amid chip restrictions. By 2026, China is the second-largest national AI market. This intensifies US-China tech competition. Government, finance, and telecom together exceed 60% of Chinese AI spending. That reflects government priorities, not just market forces.

  Source: AI Business


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• 20. European AI spending exceeds $70 billion

  The Data:

  Europe will spend over $70 billion on AI in 2026. That's more than double the current $33 billion (25.5% annual growth). IDC says Europe hits $133 billion by 2028 (30.3% annual growth). Financial services (especially banking) leads with 23% of European AI spending. Software is 58% of European spending, unlike China's hardware focus. Generative AI is growing at 55% yearly in Europe.

  What This Means:

  Europe's $70 billion+ makes it the second-largest regional market (about 25% of global spending). Europe's software focus and emphasis on ethical AI positions European companies to lead in trustworthy AI and regulated industries like healthcare and finance. The 55% generative AI growth shows Europe isn't falling behind despite stricter regulations. Security is big: fraud analysis (8.7%) and threat intelligence (8.5%) are major investments. That reflects Europe's focus on data protection and compliance.

  Source: Skadden

• 21. Asia-Pacific shows fastest growth at 45.7% annually

  The Data:

  Asia-Pacific AI market was $77 billion in 2024. It'll hit $735 billion by 2030 (45.7% annual growth). That makes it the fastest-growing region globally. Asia-Pacific was 27.5% of global AI revenue in 2024. China holds 36.1% of the Asia-Pacific market. South Korea is growing fastest. Software is 35% of spending. Services grow fastest at 57.3% yearly.

  What This Means:

  Asia-Pacific's 45.7% growth rate beats North America (28-32%) and Europe (30%) by a lot. The region will grab more global AI spending each year. By 2026, Asia-Pacific might match or beat Europe. This creates three-way competition: US, China/Asia-Pacific, and Europe. AI innovation is shifting east. This creates opportunities for regional cloud providers and AI companies. Growth comes from fast digitalization, expanding internet access, government support, and strong manufacturing adopting AI.

  Source: Grand View Research

• 22. Generative AI funding nearly doubled to $45 billion in 2024

  The Data:

  Generative AI VC funding hit about $45 billion in 2024. That nearly doubled from $24 billion in 2023. Late-stage deal sizes jumped from $48 million to $327 million. Bloomberg says the generative AI industry will grow from $40 billion in 2022 to $1.3 trillion over ten years. First half of 2025 funding already beat all of 2024.

  What This Means:

  Funding doubling in one year and staying strong through 2025 shows investors believe generative AI is a fundamental shift, not hype. The 7x jump in late-stage deals shows companies scaling fast. They need massive capital for compute, talent, and growth. This money ensures generative AI keeps improving fast through 2026. Companies invest in bigger models, better data, and specialized apps. The distribution tactics that work for generative AI companies are covered extensively in our report covering the AI Wrapper market, with specific examples you can adapt.

  Source: Mintz

• 23. Computer vision market reaches $34 billion

  The Data:

  Computer vision will hit $34.24 billion in 2026. This is AI-powered image and video analysis. Uses include autonomous vehicles, medical imaging, factory quality checks, checkout-free stores, security systems, and farm monitoring. It includes smart cameras, PC-based systems, and cloud image recognition.

  What This Means:

  Computer vision's $34 billion makes it AI's most mature commercial application outside language. Unlike language models needing huge datacenter compute, computer vision runs on edge devices. This enables real-time uses in manufacturing, security, and consumer devices without network delays. The tech automates visual inspection across industries. That drives steady investment. Some projections show $48.6 billion by 2026. That suggests upside as adoption speeds up.

  Source: Market.us

• 24. AI-as-a-Service market grows to $49.5 billion

  The Data:

  AI-as-a-Service will hit about $49.5 billion in 2026. That's up from $24.73 billion in 2024 (40% annual growth). This includes cloud AI platforms from AWS, Google Cloud, Microsoft Azure, and IBM Watson. They provide Machine Learning, Natural Language Processing, Computer Vision, and Generative AI APIs.

  What This Means:

  Doubling in two years shows companies prefer buying AI as a service over building it themselves. The $49.5 billion shows cloud providers making money from AI beyond basic infrastructure. This makes AI accessible to smaller companies without resources for custom development. As platforms improve and prices drop through competition, adoption speeds up. This makes AI available to all company sizes. It drives the next digital transformation wave.

  Source: Next Move Strategy Consulting

• 25. US Pentagon allocates $13.4 billion for AI and autonomy

  The Data:

  US Defense budget for 2026 includes $13.4 billion just for AI and autonomy. This is the first year with a separate AI budget line. Breakdown: $9.4 billion for unmanned aerial vehicles, $1.7 billion for maritime autonomous systems, $734 million for underwater capabilities, $210 million for autonomous ground vehicles, $1.2 billion for software and integration, and $200 million for AI and automation tech.

  What This Means:

  A dedicated budget line means Defense treats AI as fundamental capability, not experiment. The $13.4 billion (bigger than many countries' entire defense budgets) will drive AI in autonomous systems, decision support, and intelligence analysis. Military AI often creates dual-use tech that spreads to commercial markets. This spending signals to allies and rivals that the US prioritizes AI for military advantage.

  Source: MeriTalk


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• 26. European Union mobilizes €200 billion through InvestAI

  The Data:

  EU's InvestAI targets €200 billion total AI investment (€50 billion public, €150 billion private) over five years. There's a €20 billion fund for AI "gigafactories." European Commission President announced this in February 2025 in Paris. Investment includes infrastructure for gigafactories that can train very large AI models. Access goes to researchers, companies, startups, and SMEs across Europe. The EU will also deploy 9 new AI supercomputers in 2025-2026.

  What This Means:

  Europe's €200 billion shows the EU determined to compete with US and China despite lagging in commercial AI and venture capital. The "gigafactories" focus shows concerns about depending on American cloud providers and Chinese manufacturing. By 2026, these investments start yielding European AI capabilities in compute, foundation models, and apps. This could create a third major AI ecosystem alongside US and China with its own standards and regulations.

  Source: European Commission

• 27. Alternative projection shows $480 billion in AI capex

  The Data:

  Global AI spending projected at $480 billion in 2026 (33% growth from $360 billion in 2025). This UBS forecast tracks AI capital spending: infrastructure, compute, high-bandwidth memory, networking, and industrial capex (cooling, power, physical infrastructure). Spending is spreading beyond the "Big 4" hyperscalers (Microsoft, Amazon, Alphabet, Meta). China AI companies, neocloud providers like CoreWeave and Lambda, and enterprise/sovereign clouds will hit 48% of total in 2026, up from 42% in 2025.

  What This Means:

  AI infrastructure spending spreading beyond tech giants shows a maturing market. Compute access isn't monopolized anymore. This creates opportunities for specialized AI cloud providers serving specific industries. It shows companies building their own infrastructure instead of relying only on hyperscaler clouds. This signals long-term AI commitment and willingness to invest big for strategic control. Spreading beyond Big 4 also reduces concentration risk. It creates a more resilient global AI infrastructure.

  Source: UBS

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