Venture capitalists anticipate a surge in enterprise AI spending by 2026, but predict that this investment will be channeled through a smaller number of vendors. A recent TechCrunch survey of 24 venture capital firms focused on enterprise technology revealed that a significant majority expect companies to increase their AI budgets in the coming years, while simultaneously consolidating their vendor relationships.

The shift reflects a move away from the experimental phase of AI adoption, according to investors. For the past several years, enterprises have been actively piloting various AI tools to determine optimal implementation strategies. Andrew Ferguson, a vice president at Databricks Ventures, believes 2026 will mark a turning point as enterprises begin to consolidate their investments and select preferred AI platforms. "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," Ferguson said.

This current landscape involves companies often testing numerous AI solutions for similar applications, leading to a fragmented market with numerous startups vying for attention. However, as enterprises gather tangible evidence of AI's effectiveness, they are expected to streamline their approach. Ferguson explained that companies will likely reduce their experimentation budgets, eliminate redundant tools, and reinvest those savings into AI technologies that have demonstrated proven results.

Rob Biederman, a managing partner at Asymmetric Capital Partners, echoed this sentiment. The anticipated consolidation suggests that enterprises are seeking to maximize the return on their AI investments by focusing on solutions that offer clear and measurable benefits.

The increased spending and vendor consolidation are expected to have a significant impact on the AI industry. Startups that can demonstrate clear differentiation and deliver tangible value are more likely to secure long-term contracts with enterprise clients. Conversely, companies offering overlapping or unproven solutions may face challenges in a more competitive market. The trend also highlights the growing importance of robust AI platforms that can address a wide range of enterprise needs, potentially favoring larger, more established players in the AI space.