NEA’s Tiffany Luck says enterprises are still figuring out their AI ROI
The business move
Earlier this year, many tech companies pushed employees to adopt AI tools aggressively, a trend dubbed “tokenmaxxing.” This meant ramping up AI usage quickly, even at a high cost. Companies like Uber exhausted their AI budgets within months, some organizations cut back on AI licenses like Claude, and Meta eliminated its internal AI usage leaderboard. Tiffany Luck from NEA highlighted that enterprises are still trying to figure out the real return on investment from these AI efforts.
Why it matters
The rush to maximize AI use ran into immediate budget pushback, showing that many companies have not yet nailed how to measure or manage AI ROI. This tension exposes how costly AI adoption can be when unchecked and how quickly enthusiasm hits financial and operational limits. Enterprises face pressure to balance AI experimentation with stricter cost controls, making AI investments harder to justify without clear value metrics. This caution may slow down wide-scale AI adoption or push firms toward more targeted, efficient use cases.
Who gains and who gets squeezed
AI vendors may face demand swings as clients rethink broad AI license rollouts or internal usage incentives. Buyers will push providers for more flexible pricing and clearer metrics tied to business outcomes. Internal teams that champion AI tools risk losing funding if they cannot prove concrete results fast. At the same time, enterprises who figure out tighter ROI tracking and smarter AI deployment will gain competitive edges by optimizing costs while still extracting value from AI technologies.
What to watch next
Track whether companies develop better AI cost management tools and ROI measurement frameworks. Watch for shifts in vendor contracts toward usage-based pricing. Keep an eye on whether enterprises pull back on wide-ranging AI programs or redirect resources to proven use cases. Also, see if internal AI advocacy shifts from maximizing use to maximizing business impact, redefining success metrics across industries.
AI Quick Briefs Editorial Desk
