Does enterprise artificial intelligence (AI) save teams money, or cost companies cash? It’s a question with a potentially category-defining answer, and it’s one that depends on whom you ask.

Complete the form to unlock this article and enjoy unlimited free access to all PYMNTS content — no additional logins required.

News broke this week, for example, that Apple is reportedly putting its employees’ AI usage on a tighter leash. The bigger question for corporate finance departments, though, is how limiting AI spending can save them real money without sacrificing growth.

The Cupertino technology and hardware giant is cutting the AI budget for certain internal teams by as much as a third, and other tech sector companies have also set limits on employees’ AI spending. Tesla has a $200 weekly limit, Uber has a $1,500 monthly limit and Meta has encouraged employees to use the company’s own tools, as PYMNTS covered.

The restrictions reflect a new reality for enterprise AI as its solutions scale and the models mature. Every additional prompt, automated workflow and software development task can generate another charge. Unlike traditional software licenses, usage-based AI costs can rise as employees become more dependent on the technology.

That creates an uncomfortable equation for CFOs. Cutting AI consumption can improve a technology budget while increasing labor costs, slowing development or reducing the quality of financial decisions.

PYMNTS Intelligence has been targeting that dilemma with months of original research. Findings from 2026’s data studies suggest the real challenge is no longer how much AI enterprises can afford but determining which AI expenses have become integral to the business.

Source link