For several years, businesses have been trialing and evaluating various AI tools to determine their adoption approach. Investors now believe this phase of experimentation is nearing its conclusion.
A recent TechCrunch survey of 24 venture capitalists specializing in enterprise technology revealed that most anticipate companies will boost their AI budgets in 2026, though selectively. The majority of investors indicated this budgetary growth would be focused, with many businesses allocating greater resources to fewer agreements.
Andrew Ferguson, a vice president at Databricks Ventures, foresees 2026 as the year when businesses will begin to consolidate their investments and identify top-performing solutions.
“Currently, organizations are evaluating numerous tools for individual applications, and there’s a proliferation of startups targeting specific purchasing departments such as [go-to-market], making it incredibly difficult to distinguish unique advantages even during [proof of concepts],” Ferguson stated. “Once businesses observe tangible results from AI, they will reduce experimental spending, streamline redundant tools, and reinvest those savings into AI technologies that have demonstrated effectiveness.”
Rob Biederman, a managing partner at Asymmetric Capital Partners, concurred. He anticipates that not only will individual enterprise firms focus their expenditures, but the wider business sector will also restrict its total AI spending to a select group of vendors across the industry.
“Funding will rise for a limited range of AI products that demonstrably yield outcomes, while significantly decreasing for all other solutions,” Biederman remarked. “We foresee a split where a small number of providers secure a disproportionately large portion of enterprise AI budgets, while many others experience stagnant or decreasing revenue.”
Targeted Allocations
Scott Beechuk, a partner at Norwest Venture Partners, believes businesses will allocate more funds to tools that ensure AI’s secure deployment within organizations.
“Organizations are now aware that the true investment resides in the protective measures and supervisory frameworks that ensure AI reliability,” Beechuk stated. “As these features advance and mitigate risks, companies will confidently transition from pilot programs to extensive implementations, leading to increased budgets.”
Harsha Kapre, a director at Snowflake Ventures, forecasted that enterprises would direct their AI expenditures in 2026 towards three specific domains: fortifying data infrastructure, optimizing models post-training, and integrating various tools.
“[Chief investment officers] are actively curtailing the proliferation of [software-as-a-service] and transitioning to cohesive, smart systems that decrease integration expenses and provide quantifiable [return on investment],” Kapre explained. “AI-powered solutions are expected to gain the most from this transformation.”
This transition from broad experimentation to focused investment is set to impact startups, though the exact nature of this impact remains uncertain.
It’s conceivable that AI startups will encounter a similar turning point experienced by SaaS startups some years prior.
Firms offering difficult-to-duplicate products, such as specialized vertical solutions or those based on unique proprietary data, are expected to continue thriving. Conversely, startups with offerings resembling those from major enterprise providers like AWS or Salesforce might experience a decline in pilot programs and available funding.
Investors also acknowledge this potential outcome. Inquiring about how they identify an AI startup’s competitive advantage, several VCs cited companies possessing proprietary data and products not readily replicable by a technology giant or large language model firm as having the strongest defenses.
Should investor forecasts prove accurate and businesses indeed begin to consolidate their AI spending next year, 2026 might see an increase in enterprise budgets, yet many AI startups may not secure a larger portion of the market.