VCs predict enterprises will spend more on AI in 2026 — through fewer vendors

Companies have been testing and testing various AI tools in recent years to figure out what their adoption strategy will look like. Investors think the period of experimentation is coming to an end.

TechCrunch recently surveyed 24 enterprise-focused venture capital firms and an overwhelming majority predicted that companies will increase their budgets for AI by 2026 – but not for everything. Most investors said this budget increase will be concentrated and many companies will spend more money on fewer contracts.

Andrew Ferguson, vice president at Databricks Ventures, predicted that 2026 will be the year that companies start consolidating their investments and picking winners.

“Today, companies are testing multiple single-use tools, and there is an explosion of startups targeting certain buying centers such as [go-to-market]where it is extremely difficult to distinguish differentiation, even during [proof of concepts]“When companies see real proof points of AI, they will cut some of the experimentation budget, rationalize overlapping tools and deploy those savings into the AI ​​technologies that delivered.”

Rob Biederman, managing partner at Assymetric Capital Partners, agrees. He predicts that large companies will not only concentrate their individual spending, but that the broader enterprise landscape will limit overall AI spending to just a handful of vendors across the industry.

“Budgets will rise for a limited number of AI products that clearly deliver results, and will fall sharply for everything else,” Biederman said. “We expect a split where a small number of vendors account for a disproportionate share of enterprise AI budgets, while many others see revenues level off or shrink.”

Targeted investments

Scott Beechuk, partner at Norwest Venture Partners, thinks companies will increase their spending on the tools that can make AI safe for business.

“Enterprises now recognize that the real investment is in the security and oversight layers that make AI trustworthy,” Beechuk said. “As these capabilities mature and risks reduce, organizations will feel confident moving from pilots to large-scale deployments, and budgets will increase.”

Harsha Kapre, director at Snowflake Ventures, predicted that by 2026, companies will spend on AI in three different areas: strengthening the data base, optimizing models after training, and consolidating tools.

“[Chief investment officers] are actively reducing [software-as-a-service] sprawl and evolve towards unified, intelligent systems that reduce integration costs and deliver measurable results [return on investment]Kapre said. “AI-based solutions will likely see the greatest benefit from this shift.”

A shift from experimentation to concentration will have consequences for startups. What is not clear is how.

It’s possible that AI startups will reach the same point of reckoning that SaaS startups did a few years ago.

Those companies that operate products that are difficult to replicate, such as vertical solutions or solutions based on proprietary data, will likely still be able to grow. Startups with products similar to those of major enterprise vendors, such as AWS or Salesforce, could see trials and funding dry up.

Investors also see this opportunity. When asked how they know an AI startup has a moat, multiple venture capital firms said that companies with proprietary data and products that can’t be easily replicated by a tech giant or large language model company are the most defensible.

If investor predictions come true and companies focus their AI spending next year, 2026 could be the year corporate budgets rise, but many AI startups don’t see a bigger slice of the pie.