How 100 Enterprise CIOs Are Building and Buying Gen AI in 2025

By Sarah Wang , Shangda Xu , Justin Kahl , and Tugce Erten

Just over a year ago, we highlighted 16 changes to the way enterprises approached building and buying gen AI. Since then, the landscape has continued to evolve quickly—so we revisited our conversations with over two dozen enterprise buyers and surveyed 100 CIOs across 15 industries to help founders understand how these leaders are using, buying, and budgeting for gen AI in 2025 and beyond.

Even in a field where the only constant is change, the gen AI market structure has evolved significantly beyond our expectations since we ran our last survey over a year ago. 

• Enterprise AI budgets grew beyond already high forecasts and graduated from pilot programs and innovation funds to recurring line-items in core IT and business unit budgets. 
• Organizations are much more sophisticated at mixing and matching multiple models to optimize across both performance and cost. OpenAI, Google, and Anthropic took dominant overall market share in our survey while Meta and Mistral were popular among open source options. 
• Procurement now mirrors traditional software buying—with more rigorous evaluations, hosting considerations, and benchmark scrutiny—while increasingly complex AI workflows are driving higher switching costs. 
• Meanwhile, the AI app landscape has matured: off-the-shelf solutions are eclipsing custom builds and rewarding AI-native third party applications.

Read the full report here

More from the a16z Growth Compendium

16 Changes to the Way Enterprises Are Building and Buying Generative AI in 2024

By Sarah Wang and Shangda Xu

Generative AI took the consumer landscape by storm in 2023, reaching over a billion dollars of consumer spend in record time. In 2024, we believe the revenue opportunity will be multiples larger in the enterprise.

Last year, while consumers spent hours chatting with new AI companions or making images and videos with diffusion models, most enterprise engagement with gen AI seemed limited to a handful of obvious use cases and shipping “GPT-wrapper” products as new SKUs. Some naysayers doubted that gen AI could scale into the enterprise at all. Aren’t we stuck with the same 3 use cases? Can these startups actually make any money? Isn’t this all hype?

Over the past couple months, we’ve spoken with dozens of Fortune 500 and top enterprise leaders, and surveyed 70 more, to understand how they’re using, buying, and budgeting for generative AI. We were shocked by how significantly the resourcing and attitudes toward gen AI had changed over the last 6 months.

Though these leaders still have some reservations about deploying generative AI, they’re also nearly tripling their budgets, expanding the number of use cases that are deployed on smaller open-source models, and transitioning more workloads from early experimentation into production. 

This is a massive opportunity for founders. We believe that AI startups who 1) build for enterprises’ AI-centric strategic initiatives while anticipating their pain points, and 2) move from a services-heavy approach to building scalable products will capture this new wave of investment and carve out significant market share.

Read here

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