Businesses have been piloting and testing various AI tools over the past few years to understand what their adoption strategies will look like. Investors believe the experimental period is nearing its end.
TechCrunch recently surveyed 24 enterprise-focused VC firms and predicted that the vast majority will increase their AI budgets in 2026, but not all. Most investors said the budget increases would be concentrated and many companies would spend more money on fewer contracts.
Andrew Ferguson, vice president at Databricks Ventures, predicted that 2026 will be the year companies start consolidating investments and picking winners.
“Today, companies are testing multiple tools for a single purpose, and there has been an explosion of startups focused on specific buying centers, such as: [go-to-market]it is very difficult to identify differentiation among them. [proof of concepts]”As companies realize the real proof points with AI, they will cut some of their experimentation budgets, streamline duplicative tools, and deploy those savings to the AI technology provided,” Ferguson said.
Rob Biederman, managing partner at Asymmetric Capital Partners, agreed. He predicts that not only will large enterprises concentrate individual spending, but the broader enterprise environment will limit overall AI spending to just a handful of vendors across industries.
“Budgets will increase for a limited number of AI products that clearly deliver results, but for others they will decline precipitously,” Biedermann said. “We anticipate a tipping point where a small number of vendors will capture a disproportionate share of enterprise AI budgets, while many others will see flat or declining revenues.”
concentrated investment
Scott Beechuk, a partner at Norwest Venture Partners, believes spending on tools that allow companies to use AI securely will increase.
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“Companies are now realizing that the real investment is in the safeguards and oversight layers that make AI trustworthy,” says Beechak. “As these capabilities mature and risks are reduced, organizations will be able to move from pilot deployments to large-scale deployments with confidence and increased budgets.”
Harsha Kapre, director at Snowflake Ventures, predicted that companies will invest in AI in three different areas in 2026: strengthening data foundations, optimizing post-training models, and integrating tools.
“[Chief investment officers] We are actively reducing [software-as-a-service] Move to integrated, intelligent systems that reduce sprawl, reduce integration costs, and deliver measurable outcomes. [return on investment]“AI-enabled solutions will be the biggest beneficiaries of this change,” Capre said.
The shift from experimentation to focus will impact startups. What isn’t obvious is how.
AI startups may reach the same reckoning point that SaaS startups reached a few years ago.
Companies with products that are difficult to replicate, such as vertical solutions or products built on proprietary data, have the potential to continue to grow. Startups offering products similar to those offered by large enterprise suppliers such as AWS and Salesforce may begin to run out of pilot projects and funding.
Investors are also paying attention to this possibility. When asked how to know if an AI startup has a moat, venture capitalists said the most defensible companies are those with proprietary data and products that cannot be easily replicated by big tech or large language modeling companies.
If investor predictions come true and companies start focusing on AI spending next year, 2026 could be the year that corporate budgets increase, but many AI startups aren’t expecting a bigger piece of the pie.
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