Enterprise AI spending increases, OpenAI leads, RBC reveals

A new study from RBC Capital Markets reveals a series of unexpected findings that call into question many of the biggest stories about AI.

Rishi Jallia and other RBC technology analysts survey more than 100 chief information officers and other technology leaders approximately every six months to measure their companies’ IT spending. Their annual budgets amount to billions of dollars.

And Jallia is not an AI cheerleader. He urged caution when it comes to the introduction of AI by companies. So I’ll be careful when he publishes.

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

“AI deployments have begun to move from pilots to production, driven by widespread corporate spending momentum heading into the second half of 2026,” Jaluria wrote.

Surprise 1

Investors have been worried for months that rising token claims could be AI’s biggest problem. RBC’s investigation found the opposite.

Nearly 9 in 10 said their token budget was manageable, even though almost half of respondents had already exceeded their original spending plan.

Rather than rushing to reduce AI costs, most companies plan to spend more on AI tokens in the future. (This makes sense, as the price of the token is likely to fall, making the return on spending on AI more attractive).

OpenAI is far ahead

This result really caught my eye. OpenAI isn’t just ahead of the curve, it’s chasing the field.

57% of respondents said ChatGPT is the AI ​​model-based service they use the most, compared to just 12% for Anthropic’s Claude.

OpenAI also has a comfortable lead in performance, with 44% naming it as the best performing model provider compared to 24% for Anthropic.

A successful IPO by OpenAI and Anthropic will require continued and large-scale business adoption of AI.

Now, what kind of apocalypse?

According to this study, the long-predicted “SaaSpocalypse” has not appeared so far.

The majority of respondents expected their spending on software to increase, and none expected their spending to decrease. Even companies that invest more in AI are not paying for it by scrapping the rest of their software stack.

From pilot to production

The study also suggests that enterprise AI has graduated from experimentation. Late last year, a similar survey by RBC raised concerns about companies’ adoption of AI.

This time, more than half of respondents say AI is already in production, and an additional 35% expect it to be in production within six months.

New pricing becomes popular quickly

Meanwhile, hybrid pricing models that combine seat licenses and usage-based pricing have quickly become the preferred method for enterprises to purchase AI.

This is a surprisingly fast change for a market that often introduces new technologies at glacial speed.

100% chart

Perhaps the most impressive graph in the report is also the simplest. The solid blue circle indicates that 100% of respondents are allocating budget to AI and large-scale language model projects.

Of those, 91% said they are creating entirely new AI budgets rather than simply reshuffling existing spending. This is another sign that the AI ​​investment cycle is accelerating for American companies.

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