In a recent Townhall convened by Creative Strategies, industry experts made some pretty bullish predictions on AI spend. They’re betting that by 2026, enterprises will exponentially increase their spending and concentrate it on a dozen or so vendors. A panel with some of the biggest names in venture capital at the helm ignited this prophecy. That conversation was held at the TechCrunch Disrupt programming happening October 13-15, 2026, in San Francisco.
Becca is a former senior writer at TechCrunch. Venture capital trends and startups are her jam, and she walked through the highlights shared by these experts. Norwest Venture Partners’ Scott Beechuk stood out among the panelists. She said that the tools that AI entrepreneurs should be comfortable building are those that reinforce responsible and safe value creation across the board. Specifically, he noted that organizations are maturing their AI capabilities. As they address related risks, they will make the shift from pilot projects to widespread deployments.
“Enterprises now recognize that the real investment lies in the safeguards and oversight layers that make AI dependable,” – Scott Beechuk
Rob Biederman, managing partner at Asymmetric Capital Partners, agreed with Beechuk. He believes that a change in spending priorities is coming. Very soon, budgets will reward only a few AI products that produce verifiable outcomes. Biederman observed that budgets will increase for the AI products that deliver their expected results. At the same time, funding will fall off a cliff for every other option.
Andrew Ferguson, vice president at Databricks Ventures, thinks that 2026 will be an inflection point for enterprises. At some point, companies will begin to get more serious about consolidating their investments and selecting the best solutions. He stressed that most of the enterprises he’s spoken with are testing different tools with multiple use cases. This trend has only resulted in an overwhelming onslaught of startups jostling for attention in targeted spaces, such as go-to-market strategies.
“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
Harsha Kapre, director at Snowflake Ventures, outlined three distinct areas where enterprises are expected to allocate their AI budgets in 2026. These include enhancing data readiness, improving models after they’re trained, and integrating multiple tools. Kapre’s recommendations indicate that entities will focus investments that improve their general data capabilities and simplify their AI toolsets.
The panel’s predictions come on the heels of several years during which enterprises have been piloting and testing various AI solutions. All of this experimentation has produced a much better idea of what works best in practical application.
As the TechCrunch event approaches, experts are keen to explore how these trends will shape the future landscape of AI in enterprise settings. The reality is, many organizations would love to move beyond the pilot project phase. Now they’re moving toward identifying proven vendors that can provide solutions that have worked in well-tested pilots for production, full-scale implementations.
