NEA’s Tiffany Luck says enterprises are still figuring out their AI ROI

2026-06-17 · Source: AI News & Artificial Intelligence | TechCrunch · Field: Business & Management — Artificial Intelligence & Machine Learning, Corporate Strategy & Leadership, Entrepreneurship & Start-ups · Depth: Fundamental Awareness, quick

Summary

NEA partner Tiffany Luck highlights the ongoing challenge for enterprises in determining their return on investment (ROI) for artificial intelligence initiatives. This comes after an earlier "tokenmaxxing" trend in Silicon Valley, where companies pushed AI usage to its limits, resulting in significant cost overruns. For instance, Uber reportedly exhausted its annual AI budget in a few months, some organizations reduced Claude licenses, and Meta discontinued its internal AI leaderboard. Luck, who previously championed e-commerce adoption, now focuses on AI's potential, particularly for "magic moments" in consumer businesses. On TechCrunch's Equity podcast, she discussed the future of personal agents, her views on this year's AI IPOs, and how startups are developing solutions to help companies monitor their AI expenditures.

Key takeaway

For Directors of AI/ML evaluating new deployments, you must prioritize robust ROI tracking and cost management from the outset. The "tokenmaxxing" trend demonstrates that unchecked AI usage quickly exhausts budgets, as seen with Uber and Meta. Focus on integrating solutions that provide clear visibility into AI expenditures and their direct business impact. This proactive approach will ensure your AI initiatives deliver measurable value and avoid unexpected financial burdens.

Key insights

Enterprises struggle to quantify AI ROI amidst escalating costs, shifting focus from usage to measurable value.

Principles

• Unchecked AI usage leads to significant cost overruns.
• Measuring AI ROI is critical for sustainable enterprise adoption.

In practice

• Evaluate AI spend against tangible business outcomes.
• Explore startup solutions for AI cost tracking.

Topics

• AI ROI
• Enterprise AI
• AI Cost Management
• Tokenmaxxing
• Personal Agents
• Venture Capital

Best for: CTO, VP of Engineering/Data, Executive, Investor, Consultant, Director of AI/ML

Related on AIssential

• Drilling Into AI’s Financial Sustainability — Uncontrolled AI adoption driven by usage incentives led to unsustainable costs and a pivot towards cost-conscious, value-driven implementation.
• Exploring AI’s Value and Profitability — AI ROI is about augmenting human work and fostering innovation, not just incremental productivity.
• The Pulse: ‘Tokenmaxxing’ as a weird new trend — Developers are inflating AI token usage to meet internal metrics, while companies face challenges managing AI budgets.
• Companies evaluate aggressive AI spending as costs pile up — Aggressive AI spending is straining corporate margins without clear ROI, prompting re-evaluation despite continued investment.
• The token bill comes due: Inside the industry scramble to manage AI’s runaway costs — AI's escalating token costs necessitate new financial management standards and tools to ensure ROI amidst surging consumption.
• Breaking: bad news for three of the biggest IPOs in history — Excessive GenAI usage without clear ROI is unsustainable, leading to significant financial losses for major tech companies.

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI News & Artificial Intelligence | TechCrunch.