AI vendor dependence could be a bigger risk, Cohere exec warns

“When I go back to my do-it-yourself option for the home reno, it’s really easy in that example to think, well, get a professional,” Pelosi said. “But now imagine you could never do it yourself. You were always beholden, not to a professional, but to three or four professionals globally who tell you how the house is going to be built, how it’s going to be done and when it’s going to be done.”

Choice becomes the new currency in enterprise AI

Pelosi argued that most companies are still earlier in their AI deployment than the headlines suggest.

“We are not really using AI yet,” he said. “Large enterprises, governments, small and medium enterprises, they are just scratching the surface.”

Personal use of tools like ChatGPT is high, Pelosi said, but heavy production workloads, the kind that touch real operational data, are only beginning to scale. That scale-up is already showing up in headcount data: new research on AI spending and hiring growth found that companies investing heavily in AI are growing their workforces faster than companies that aren’t. That matters for HR because the more a company depends on a single AI provider, the harder it gets hit if that provider goes down, and Pelosi’s own answer to that risk is not to rely on just one type of model. Cohere, he said, deliberately uses both open and closed models rather than picking one.

“We have closed source models where certain teams don’t want to have to think about the indemnity issues, and open source models,” he said. “We encourage collaboration, we encourage experimentation, and we let folks use those as well to fine-tune to the way they need them to work.”