Harsha Kapre, director at Snowflake Ventures, has forecasted that enterprises will significantly increase their investments in artificial intelligence (AI) by 2026. Kapre outlines three primary areas where this spending will take place: strengthening data foundations, optimizing model post-training, and consolidating the tools utilized. Many organizations have let the last several years go by just piloting AI tools. They’re looking to figure out which technologies will maximize value across their operational requirements.
The upcoming TechCrunch event in San Francisco, scheduled for October 13-15, 2026, will serve as a platform for industry experts and venture capitalists to share insights on these trends. Becca, a senior writer at TechCrunch who covers venture capital trends and startups, is expected to report extensively on the event and its implications for the tech landscape.
Andrew Ferguson, vice president at Databricks Ventures, echoes his agreement with some of Kapre’s predictions. He agrees that 2026 will be a watershed year for businesses as they fold their investments together. He emphasizes that organizations have been testing multiple AI tools for various use cases, leading to a competitive environment where differentiation among startups is challenging.
“Today, enterprises are testing multiple tools for a single-use case, and there’s an explosion of startups focused on certain buying centers like [go-to-market], where it’s extremely hard to discern differentiation even during [proof of concepts],” – Andrew Ferguson
Rob Biederman, managing partner at Asymmetric Capital Partners, agrees with all the hype about AI spending. He thinks enterprises will start to be more targeted in their approach and their dollars.
“Budgets will increase for a narrow set of AI products that clearly deliver results and will decline sharply for everything else,” – Rob Biederman
Scott Beechuk, a partner at Norwest Venture Partners, goes so far as to say, “companies will spend significantly more on tools.” These tools will make the deployment and operation of AI technologies more safe and reliable. Asserting their moral and ethical responsibility to keep the technology in check, he argues that everyone—from technologists to advocates—carries an obligation to help shape its course.
“Enterprises now recognize that the real investment lies in the safeguards and oversight layers that make AI dependable,” – Scott Beechuk
Beechuk points out that AI capabilities have matured and corresponding risks have diminished. In doing so, businesses will begin transitioning from the pilot program stage to widescale implementations. Giving in to this shift would surely mean bigger budgets for even more successful AI implementations.
“As these capabilities mature and reduce risk, organizations will feel confident shifting from pilots to scaled deployments, and budgets will increase,” – Scott Beechuk
The consensus among these industry leaders is clear: as enterprises refine their approach to AI investments, the focus will shift toward fewer vendors with proven results. This trend dovetails with what’s happening at software-as-a-service (SaaS) startups, and a similar reckoning point might be upon us there, too.