Venture capital firms expect companies to spend more on AI in 2026, through fewer suppliers.

Companies have been experimenting and testing different AI tools over the past few years to see what their adoption strategy will look like. Investors believe that the trial period is coming to an end.

TechCrunch recently surveyed 24 enterprise-focused venture capital funds, and the overwhelming majority of organizations expected to increase their AI budgets in 2026 — but not for everything. Most investors said this budget increase would be concentrated and that many companies would spend more money on fewer contracts.

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

“Today, companies are testing multiple tools for a single use case, and there are a large number of startups focusing on specific buying centers e.g [go-to-market]as it is very difficult to discern the differentiation even during this [proof of concepts]“When companies see real proof points from AI, they will cut back some of the experimentation budget, rationalize overlapping tools, and spread those savings into AI technologies that deliver results,” Ferguson said.

Rob Biederman, managing partner at Ametric Capital Partners, agrees. He predicts that not only will enterprise companies focus their individual spending, but the broader enterprise landscape will also narrow their overall AI spending to just a few vendors across the entire industry.

“Budgets will increase for the limited set of AI products that deliver clear results, and decrease sharply for everything else,” Biederman said. “We expect a fragmentation as a small number of vendors capture a disproportionate share of enterprise AI budgets while many others see revenues plateau or shrink.”

Focused investments

Scott Peychuk, a partner at Norwest Venture Partners, believes companies will spend more on tools that make AI safe for businesses to use.

“Companies now realize that the real investment lies in the safeguards and layers of oversight that make AI reliable,” Peychuk said. “As these capabilities mature and risks are reduced, organizations will feel confident in shifting from pilots to large-scale deployments, and budgets will increase.”

Harsha Kapri, director of Snowflake Ventures, expects companies to spend on AI in three distinct areas in 2026: strengthening data foundations, improving models after training, and standardizing tools.

“[Chief investment officers] It is actively reduced [software-as-a-service] Extending and moving towards unified, intelligent systems that reduce integration costs and provide measurable services [return on investment]“AI-powered solutions are likely to see the greatest benefit from this shift,” Capri said.

The shift away from experimentation and toward focus will impact startups. What is not clear is how.

AI startups will likely reach the same reckoning point that SaaS startups did a few years ago.

Companies that operate products that are difficult to replicate, such as vertical solutions or those built on proprietary data, are more likely to still be able to grow. Startups with products similar to those offered by large enterprise vendors, such as AWS or Salesforce, may start to see pilot projects and funding dry up.

Investors see this possibility as well. When asked how they know an AI startup has a moat, many VCs said companies with proprietary data and products that can’t be easily replicated by a tech giant or a large language model company are more defensible.

If investor expectations are correct and companies start focusing their spending on AI next year, 2026 could be the year that enterprise budgets increase, but many AI startups do not see a bigger slice of the pie.