NEA investor: companies still don't know if AI will bring them returns

NEA venture capital fund partner Tiffany Luck believes companies are still struggling to measure the return on their artificial intelligence investments. The "tokenmaxxing" trend that gained popularity in early 2024, where companies were encouraged to maximize AI tool usage, has resulted in unexpected costs, Uber spent its annual AI budget within months, Meta shut down its internal leaderboard. Luck nevertheless sees significant potential in both personal AI agents and consumer applications.

During the artificial intelligence boom, the so-called "tokenmaxxing" trend that swept Silicon Valley, where executives pushed employees to use AI tools as intensively as possible, has begun to present companies with the bill. Tiffany Luck, partner at NEA venture capital fund, acknowledges that a large portion of companies cannot yet clearly measure whether and how much artificial intelligence actually contributes to their results.

Failed calculations

Concrete examples are telling: according to Uber, the company managed to spend its annual AI budget within just a few months. Meta ended its internal AI usage leaderboard, and several organizations have restricted Claude language model licenses in certain departments. This illustrates how enthusiasm is colliding with reality.

Luck, who began her career promoting e-commerce potential, now sees artificial intelligence as an opportunity of a new era, particularly in the consumer market, where she speaks of "magical moments" that intelligent AI can create in user experience.

Agents and IPOs

In TechCrunch's Equity podcast, Luck also discussed the future of personal AI agents and AI sector IPOs expected this year. In her view, startups are the ones stepping in to help large enterprises better track and prove the return on AI spending.

From a venture capital perspective, the question of which AI investments will pay off has become increasingly pressing. Luck believes solutions will come not only from large technology giants, but precisely from agile startups that can quickly adapt to companies' real needs.