Enterprises have spent the past few years experimenting with AI tools, testing various platforms and vendors to determine their long-term adoption strategies. Now, venture capitalists believe that phase is coming to a close. A recent TechCrunch survey of 24 enterprise-focused VCs found that the majority expect companies to significantly increase their AI budgets in 2026—but not across the board. Instead, spending will become more concentrated, with enterprises choosing fewer vendors and investing more deeply in those that deliver measurable results. Andrew Ferguson, vice president at Databricks Ventures, sees 2026 as the turning point when enterprises begin consolidating their AI investments. “Today, companies are testing multiple tools for the same use case,” he said. “In areas like go-to-market, differentiation is often blurred—even during proof-of-concepts. As enterprises see real-world outcomes from AI, they’ll cut back on experimentation, eliminate redundant tools, and redirect savings toward the technologies that prove effective.” Rob Biederman, managing partner at Asymmetric Capital Partners, echoed this sentiment, predicting a broader industry consolidation. “Budgets will rise sharply for a select few AI products that clearly demonstrate value,” he said. “Meanwhile, spending on everything else will decline. We’re heading toward a bifurcated market where a small number of vendors capture the majority of enterprise AI spend, while many others face stagnant or shrinking revenue.” The shift toward focused investment is already shaping up. Scott Beechuk, partner at Norwest Venture Partners, emphasized that enterprises are increasingly prioritizing AI safety and governance. “Organizations now understand that the real value lies in the safeguards and oversight layers that make AI reliable and trustworthy,” he said. “As these capabilities mature and reduce risk, companies will gain confidence to scale deployments—and budgets will follow.” Harsha Kapre, director at Snowflake Ventures, outlined three key areas where enterprises will likely increase spending in 2026: strengthening data foundations, optimizing models after training, and consolidating fragmented toolsets. “CIOs are actively reducing SaaS sprawl,” Kapre explained. “They’re moving toward unified, intelligent systems that lower integration costs and deliver clear ROI. AI-enabled solutions stand to benefit the most from this trend.” This consolidation will have significant implications for startups. The AI startup landscape may soon face a reckoning similar to what SaaS companies experienced a few years ago. Companies with unique, hard-to-replicate offerings—such as vertical-specific solutions or those built on proprietary data—will remain resilient. In contrast, startups offering generic AI tools that resemble capabilities already provided by major cloud providers like AWS or Salesforce may struggle to secure new pilots or funding. Multiple VCs stressed that defensibility comes down to moats. “The startups with proprietary data or products that can’t be easily replicated by tech giants or large language model providers are the ones most likely to succeed,” one investor noted. If enterprise predictions hold true, 2026 could mark a pivotal moment: AI budgets rise, but the gains won’t be evenly distributed. A few dominant players will capture the lion’s share of spending, while many others may find themselves left behind.