Over the past few years, businesses have been actively experimenting with various AI tools to shape their adoption strategies. Investors now believe this phase of exploration is nearing its end. Many anticipate that budget increases will become more focused, with companies directing greater funds toward a smaller number of contracts.

Andrew Ferguson, a vice president at Databricks Ventures, expects 2026 to be the year when enterprises begin consolidating their investments and selecting clear winners. “Right now, companies are testing multiple tools for the same use case, and there’s an explosion of startups targeting specific areas like go-to-market, where differentiation is hard to spot even during proof of concepts,” Ferguson explained. “As businesses see tangible results from AI, they’ll reduce experimental spending, streamline overlapping tools, and reinvest those savings into the technologies that have proven effective.”

Rob Biederman, a managing partner at Asymmetric Capital Partners, shares this view. He predicts that not only will individual companies concentrate their spending, but the broader enterprise market will also narrow its overall AI investment to just a handful of vendors. “Budgets will grow for a select group of AI products that clearly deliver outcomes and will drop sharply for everything else,” Biederman said. “We foresee a split where a small number of vendors capture a large share of enterprise AI budgets, while many others see their revenues stagnate or decline.”

**Focused Investments**

Scott Beechuk, a partner at Norwest Venture Partners, believes companies will increase spending on tools that make AI safer and more reliable for enterprise use. “Enterprises now understand that the real investment is in the safeguards and oversight layers that ensure AI can be trusted,” Beechuk noted. “As these capabilities mature and reduce risk, organizations will gain the confidence to move from pilot programs to full-scale deployments, leading to budget growth.”

Harsha Kapre, a director at Snowflake Ventures, forecasts that in 2026 enterprises will allocate AI spending across three key areas: strengthening data foundations, optimizing models after training, and consolidating tools. “Chief investment officers are actively reducing SaaS sprawl and moving toward unified, intelligent systems that cut integration costs and deliver clear ROI,” Kapre said. “AI-enabled solutions are likely to benefit the most from this shift.”

This move away from experimentation and toward concentration will inevitably impact startups, though the exact effects remain uncertain. AI startups may reach a turning point similar to what SaaS companies faced several years ago. Startups offering hard-to-replicate products, such as vertical solutions or those built on proprietary data, will likely continue to grow. However, those with products similar to offerings from major suppliers like AWS or Salesforce may begin to see pilot projects and funding diminish.

Investors are also mindful of this possibility. When asked what gives an AI startup a defensible advantage, several venture capitalists pointed to companies with proprietary data and products that aren’t easily replicated by tech giants or large language model firms.

If investor predictions hold true and enterprises do start to concentrate their AI spending next year, 2026 could indeed be a year where overall enterprise budgets grow—but many AI startups may not see a larger share of the investment.