NEA’s Tiffany Luck says enterprises are still figuring out their AI ROI
TL;DR
TechCrunch's Equity podcast frames the post-tokenmaxxing hangover: after months of pushing AI usage hard, companies are scrutinizing cost, budgets and measurable value. The examples are concrete: Uber reportedly burned through its annual AI budget in a few months, some firms cut Claude licenses for parts of their orgs, and Meta shut down an internal usage leaderboard. NEA partner Tiffany Luck says this is the central enterprise AI question now: adoption is broad, but reliable ROI measurement is still messy.
Nauti's Take
Tokenmaxxing was a useful stress test, but as a management strategy it was blunt. Counting how much AI people use is not the same as proving that the work got better, faster or cheaper.
Tiffany Luck's view is clearly shaped by venture capital, but the core point holds: the next enterprise cycle will be less about demo magic and more about evidence by team, workflow and budget line. AI is still hot, but the CFO has entered the room.
Briefingshow
The issue is not that enterprise AI is failing, but that the first adoption wave often ran ahead of disciplined cost accounting. Once licenses, tokens and internal infrastructure show up in budgets, enthusiasm is not enough. The winners will be tools tied to workflows, savings or revenue impact, not just usage minutes.
Sources