VCs Expect Enterprises to Spend More on AI in 2026 with Fewer Vendors
Investors believe enterprises will boost AI spending in 2026, focusing on fewer vendors and consolidating budgets for impactful technologies
According to a recent TechCrunch survey of 24 VCs focused on the enterprise sector, there’s a powerful prediction on the horizon. Enterprises, they’re saying, will ramp up their AI budgets but in a much more targeted manner. Instead of scattering funds across numerous vendors, companies are likely to hone in on a select group, going deeper rather than wider.
Andrew Ferguson, who holds a vice president position at Databricks Ventures, elucidates this trend. He envisions 2026 as the year enterprises cease their broad experimentation phase. “Right now, companies are juggling multiple tools for single-use cases, amidst a flurry of startups,” Ferguson noted. “As the evidence of AI effectiveness mounts, enterprises will trim their experimentation budgets and bet on technologies that deliver real results.”
Scott Beechuk at Norwest Venture Partners supports this notion, emphasizing that the safe deployment of AI tools will echo through increased spending. “Enterprises are realizing that the key investment is in the robust safeguards that make AI reliable,” Beechuk said, anticipating a shift from pilot projects to full-scale implementations, leading to budget increases.
Rob Biederman from Asymmetric Capital Partners outlined a similar perspective, emphasizing a forthcoming narrowing in the enterprise AI landscape. “We’ll see budgets swell for a select few AI products that demonstrate clear results, while spending for others takes a hit,” Biederman asserted. “A small cluster of vendors will dominate, capturing a significant share of enterprise AI funding.”
Harsha Kapre, a director at Snowflake Ventures, highlights three critical areas enterprises will prioritize in 2026: bolstering data foundations, optimizing model post-training, and streamlining tools. “CIOs are moving towards smart, integrated systems and away from SaaS sprawl, allowing organizations to optimize returns,” Kapre explained.
However, as enterprises redirect their focus, how will startups fare? The path ahead seems uncertain. Some startups, especially those offering unique vertical solutions or reliant on proprietary data, may continue to flourish. But those mimicking large enterprise products, like AWS and Salesforce, might see their funding dwindle as pilot projects shrink.
Investors share this view. When asked about the qualities that indicate a defensible AI startup, many pointed to proprietary data and the uniqueness of products that large tech companies cannot easily replicate.
If these investor forecasts hold true, 2026 could usher in not just an uptick in enterprise AI budgets, but also a challenging reality for many startups that fail to carve out a distinctive niche in a crowded field.