At a Glance
> At a Glance
> – VCs predict a sharp focus on AI budgets in 2026.
> – Enterprises will cut experimentation and favor a few high-performing vendors.
> – Safety tools and data foundations will drive the bulk of new spend.
> – Why it matters: Companies will shift resources toward proven AI solutions, reshaping the startup landscape.
Enterprises have been testing a variety of AI tools for years, but venture capitalists say that the era of broad experimentation is ending. A recent survey of 24 enterprise-focused VCs indicates that 2026 will bring tighter budgets and a more selective approach to AI purchases.
Investor Outlook on 2026 AI Spending
The survey found that most investors expect overall AI spending to narrow, concentrating on a handful of vendors while reducing overlap.
- Andrew Ferguson (Databricks Ventures) said enterprises will consolidate investments.
> Andrew Ferguson stated:
>
> > “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.”
> >
> > “As enterprises see real proof points from AI, they’ll cut out some of the experimentation budget, rationalize overlapping tools and deploy that savings into the AI technologies that have delivered.”
- Rob Biederman (Asymmetric Capital Partners) predicted a bifurcation in spending.
> Rob Biederman said:
>
> > “Budgets will increase for a narrow set of AI products that clearly deliver results and will decline sharply for everything else.”
> >
> > “We expect a bifurcation where a small number of vendors capture a disproportionate share of enterprise AI budgets while many others see revenue flatten or contract.”
Focus on Safety and Oversight
Enterprises are also prioritizing safeguards that make AI dependable.
- Scott Beechuk (Norwest Venture Partners) highlighted the shift toward safety tools.
> Scott Beechuk noted:
>
> > “Enterprises now recognize that the real investment lies in the safeguards and oversight layers that make AI dependable.”
> >
> > “As these capabilities mature and reduce risk, organizations will feel confident shifting from pilots to scaled deployments, and budgets will increase.”
Three Pillars of Enterprise AI Investment
Harsha Kapre (Snowflake Ventures) outlined the main areas where budgets will grow in 2026:
| Area | Focus |
|---|---|
| Strengthening data foundations | Building reliable data infrastructure |
| Model post-training optimization | Improving model performance after training |
| Consolidation of tools | Reducing SaaS sprawl and unifying systems |
Kapre added that chief investment officers are moving toward unified, intelligent systems that lower integration costs and deliver measurable return on investment.
Impact on Startups
The shift away from experimentation will pressure many AI startups, especially those offering solutions similar to large enterprise vendors.
- Startups with hard-to-replicate vertical solutions or proprietary data are likely to continue growing.
- Startups whose products mirror offerings from AWS or Salesforce may see pilot projects and funding dry up.
- Investors emphasize that a moat is most defensible when a startup owns proprietary data or a product that cannot be easily replicated by a tech giant or large-language-model company.
Key Takeaways
- 2026 will see tighter AI budgets with a focus on a few high-performing vendors.
- Safety and data foundation tools will command the majority of new spending.
- Startups offering niche or proprietary solutions may thrive, while those competing with large vendors could face reduced funding.
The coming year will likely reshape how enterprises invest in AI and which startups survive the tightening of capital.
