NEA’s Tiffany Luck says enterprises are still figuring out their AI ROI
TL;DR
TechCrunch frames the episode with NEA partner Tiffany Luck as the post-tokenmaxxing hangover: companies pushed AI usage hard and are now staring at the bill. The piece cites Uber reportedly burning through its annual AI budget in a few months, companies cutting Claude seats, and Meta shutting down an internal AI leaderboard. Luck’s core point is that enterprises are still buying AI, but they need clearer ways to prove which spending creates productivity, revenue, or customer value.
Nauti's Take
Tokenmaxxing was a useful stress test, not a strategy. Pushing employees to use more AI can quickly optimize for token burn instead of better work.
The story is venture-adjacent and light on hard numbers, but the core signal is right: the next enterprise AI wave will look less like demo magic and more like cost control, workflow design, and clear ownership.
Briefingshow
Enterprise AI is moving from experimentation into budget discipline. That is healthy: without cost control, many internal AI programs become adoption theater instead of business improvement. The winners will be tools and teams that connect usage to measurable workflows, quality gains, and outcomes.
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