For the past few years, enterprises have been piloting and testing various AI tools to shape their adoption strategies. According to investors, this period of experimentation is now drawing to a close. A recent survey of 24 enterprise-focused venture capitalists revealed an overwhelming majority predict enterprises will increase their AI budgets in 2026, though not across the board. Most investors believe this budget rise will be concentrated, with many companies spending more funds on fewer contracts.
Andrew Ferguson, a vice president at Databricks Ventures, forecasts that 2026 will be the year enterprises begin consolidating their investments and choosing winners. He notes that currently, companies are testing multiple tools for single use cases amidst an explosion of startups, making differentiation difficult. As enterprises witness genuine proof points from AI, they will cut experimentation budgets, rationalize overlapping tools, and redirect those savings into technologies that have proven their value.
Rob Biederman, a managing partner at Asymmetric Capital Partners, agrees. He predicts enterprise companies will not only concentrate their individual spending, but the broader industry will narrow its overall AI spending to just a handful of vendors. Budgets will increase for a narrow set of AI products that clearly deliver results and decline sharply for all others. He expects a bifurcation where a small number of vendors capture a disproportionate share of enterprise AI budgets, while many others see revenue flatten or contract.
Scott Beechuk, a partner at Norwest Venture Partners, believes enterprises will increase spending on tools that make AI safe for enterprise use. He states that organizations now recognize the real investment lies in the safeguards and oversight layers that make AI dependable. As these capabilities mature and reduce risk, companies will feel confident shifting from pilots to scaled deployments, and budgets will increase accordingly.
Harsha Kapre, a director at Snowflake Ventures, predicts enterprises will focus their 2026 AI spending in three distinct areas: strengthening data foundations, model post-training optimization, and the consolidation of tools. He observes that chief investment officers are actively reducing software-as-a-service sprawl and moving toward unified, intelligent systems that lower integration costs and deliver measurable return on investment. AI-enabled solutions are likely to see the biggest benefit from this shift.
This move away from experimentation and toward concentration will inevitably affect startups, though the exact impact remains unclear. It is possible AI startups will reach a reckoning point similar to what SaaS startups faced a few years ago. Companies with hard-to-replicate products, such as vertical solutions or those built on proprietary data, will likely continue to grow. However, startups with products similar to those offered by large suppliers like AWS or Salesforce may see pilot projects and funding dry up.
Investors recognize this possibility as well. When asked how to identify an AI startup with a defensible moat, multiple venture capitalists pointed to companies possessing proprietary data and products that cannot be easily replicated by a tech giant or a large language model company.
If investor predictions hold true and enterprises do begin to concentrate their AI spending next year, 2026 could be a year where overall enterprise AI budgets increase, but many AI startups do not see a bigger slice of the pie.