Meta executive Adam Mosseri believes the next phase of enterprise AI adoption will involve more disciplined budgeting. As AI tools become embedded in engineering work, companies may begin treating token usage similarly to payroll, cloud computing, or other recurring operating expenses.
That is a sign of AI’s growing importance in the workplace. Rather than being viewed as a novelty, AI assistance is increasingly becoming a core productivity layer for developers, designers, and product teams.
Why this matters
Token caps could help organizations manage costs while still giving employees access to powerful AI systems. With clearer budgets, companies can better understand which AI workflows deliver the most value and where optimization is needed.
- More sustainable adoption: Teams can scale AI use without runaway spending.
- Better measurement: Leaders can compare AI costs against productivity gains.
- Smarter workflows: Engineers may learn to use AI tools more efficiently and strategically.
While the idea of limits may sound restrictive, it also shows that AI has become valuable enough to require serious operational planning. For businesses, this is another marker that AI is moving from experimentation into everyday infrastructure.