Инвестор NEA Тиффани Лак: корпорации до сих пор не разобрались с ROI от ИИ

In early 2025, "tokenmaxxing" — an unofficial race by corporations to maximize AI consumption — became the dominant trend in Silicon Valley. Several months later, the bills arrived.

What is tokenmaxxing

The term tokenmaxxing emerged in corporate environments: CEOs directly urged teams to use AI tools without limits and "pump up" token consumption to the maximum. The logic was clear — whoever uses AI more adapts faster and outpaces competitors. The race intensified at all levels: from individual teams to entire corporations, from startups to tech giants. Companies massively adopted corporate subscriptions to ChatGPT, Claude, Gemini, and other tools, essentially competing in consumption scale. Internal AI usage leaderboards turned into elements of corporate culture.

When the bill came

Reality proved harsher. Uber, according to open sources, spent its entire annual AI budget in just a few months. Several major companies cut their corporate Claude licenses — in some cases for entire divisions that couldn't show measurable results. Meta went even further: the company shut down its internal leaderboard for employee AI usage. This doesn't signal rejection of the technology. But the first phase of reckless testing is coming to an end. What takes its place is the question that should have been asked first: what exactly did we get for this money?

NEA investor's perspective

Tiffany Luk, a partner at NEA venture fund specializing in technology investments, frames the problem directly: the corporate AI tools market is only beginning to understand real return on investment.

"Enterprises are still figuring out their actual AI return," —

Tiffany Luk, NEA.

By her observations, most companies entered the AI race under competitive pressure and fear of missing the trend — without a clear methodology for measuring effectiveness. Success metrics were either not defined initially or proved unworkable in practice. As a result, companies spend significant sums but cannot answer the basic question: is it worth it?

What's next

The corporate AI market is entering a normalization phase. Companies are beginning to seek specific use cases with measurable returns:

• Process automation with clear KPI
• Reducing operational costs through partial replacement of manual labor
• Accelerating development — from idea to release
• Improving customer service through AI agents
• Intelligent search and analysis of company internal data

Companies that first learn to accurately measure AI returns will gain not only a technological advantage but also a more sustainable economic model in the next round of the race.

What this means

Corporate AI enthusiasm from the first wave collided with accounting reality. The coming year will show who managed to turn AI experiments into measurable value — and who simply burned budget on tokens.

*Meta is recognized as an extremist organization and banned in the Russian Federation.