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Business Insiderabout 2 hours ago
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This new research challenges nearly every big AI narrative of 2026

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RBC survey of CIOs shows enterprise AI adoption is accelerating, with OpenAI dominating and token budgets manageable.

This new research challenges nearly every big AI narrative of 2026

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The Big Picture
RBC Capital Markets surveyed over 100 CIOs and tech leaders, revealing that enterprise AI spending is robust and growing. Contrary to fears of token budget blowouts, nearly 90% of respondents find token costs manageable, and most plan to increase spending. OpenAI leads the market with 57% usage share, far ahead of Anthropic's 12%. The survey also shows that AI has moved from pilot to production for over half of respondents, and hybrid pricing models are rapidly gaining adoption. Notably, 100% of respondents allocate budget to AI, with 91% creating new budgets rather than reallocating existing funds, indicating sustained investment momentum.
Why It Matters
This survey debunks fears of an AI cost crisis and a SaaS slowdown, showing that enterprises are not only increasing AI budgets but creating entirely new ones. OpenAI's commanding lead over Anthropic in enterprise adoption signals a winner-take-most dynamic that could shape the IPO prospects of both companies. The rapid shift to hybrid pricing models also indicates that AI is becoming a permanent, growing line item in corporate IT, not a speculative experiment.

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Sarah Friar speaks during a conference in New York
Sarah Friar speaks during a conference in New York
OpenAI CFO Sarah Friar leads one of the most popular AI companies among chief information officers, said RBC.

Mike Segar/Reuters

  • A new RBC survey of chief information officers and tech leaders shows no freakout over AI token budgets.
  • The research found that OpenAI is the most popular among companies, outperforming Anthropic.
  • Corporate customers are spending more on software while rapidly adopting hybrid AI pricing models.

New research from RBC Capital Markets turned up a string of unexpected findings that challenge many of the biggest AI narratives.

Every six months or so, Rishi Jaluria and other RBC tech analysts survey more than 100 chief information officers and other tech leaders to gauge spending on corporate IT. These annual budgets represent many billions of dollars.

And Jaluria is no AI cheerleader. He's urged caution when it comes to AI adoption by businesses. So I pay attention when he publishes.

This time, the message is clear: Companies are spending a lot on AI and are willing to spend even more.

"We came away encouraged by broad-based enterprise spending momentum into 2H 2026, with AI adoption beginning to transition from pilot to production," Jaluria wrote.

Surprise No. 1

For months, investors have worried that ballooning token bills would become AI's biggest headache. RBC's survey found the opposite.

Nearly nine in 10 respondents said token budgets are manageable, even though almost half have already exceeded their original spending plans.

A chart from a CIO survey by RBC
A chart from a CIO survey by RBC
A chart from a chief information officer survey by RBC.

RBC Capital Markets

Instead of scrambling to cut AI costs, most companies plan to spend even more on AI tokens in the future. (Token prices are likely to plunge, making returns on AI spending more attractive, so this makes sense).

A chart from a CIO survey by RBC
A chart from a CIO survey by RBC
A chart from a CIO survey by RBC.

RBC Capital Markets

OpenAI is way ahead

This result really caught my eye: OpenAI isn't just ahead — it's lapping the field.

Fifty-seven percent of respondents said ChatGPT is the AI model-based service they use most, compared with just 12% for Anthropic's Claude.

A CIO chart from RBC
A CIO chart from RBC
A chart from a CIO survey by RBC

RBC Capital Markets

OpenAI also comfortably leads on performance, with 44% naming it the highest-performing model provider versus 24% for Anthropic.

A chart from a CIO survey by RBC
A chart from a CIO survey by RBC
A chart from a CIO survey by RBC.

RBC Capital Markets

Sustained, and very large, business adoption of AI is required for successful IPOs by OpenAI and Anthropic.

SaaSwhat-alypse?

The long-predicted "SaaSpocalypse" has failed to show up so far, according to this survey.

The vast majority of respondents expect to spend more on software, and not a single respondent expects to spend less. Even companies spending more on AI largely aren't paying for it by gutting the rest of their software stack.

A chart from a CIO survey by RBC
A chart from a CIO survey by RBC
A chart from a CIO survey by RBC

RBC Capital Markets

From pilot to production

The survey also suggests enterprise AI has graduated from experimentation. Late last year, a similar survey from RBC raised concerns about enterprise AI adoption.

This time, more than half of respondents said AI is already in production, while another 35% expect to reach production within six months.

A chart from a CIO survey by RBC
A chart from a CIO survey by RBC
A chart from a CIO survey by RBC

RBC Capital Markets

New pricing catches on quick

Meanwhile, hybrid pricing models that combine seat licenses with usage-based pricing have quickly become the preferred way enterprises want to buy AI.

That's a remarkably fast shift for a market that typically adopts new technology at glacial speed.

A chart from a CIO survey by RBC
A chart from a CIO survey by RBC
A chart from a CIO survey by RBC

RBC Capital Markets

The 100% chart

Perhaps the most striking chart in the report is also the simplest: a solid blue circle showing 100% of respondents are allocating budget to AI and large language model projects.

A chart from a CIO survey by RBC
A chart from a CIO survey by RBC
A chart from a CIO survey by RBC

RBC Capital Markets

Of those, 91% said they're creating entirely new AI budgets rather than simply reshuffling existing spending — another sign that, for corporate America, the AI investment cycle is accelerating.

Sign up for BI's Tech Memo newsletter here. Reach out to me via email at abarr@businessinsider.com.

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This new research challenges nearly every big AI narrative of 2026 | TechCulture