AI's Jevons Paradox: Why Cheaper Tokens Are Costing You More

Token prices have fallen sharply over the past two years, yet enterprise AI bills keep climbing. Bain & Company calls it a simple behavioral fact: "everyone stays on frontier," so the moment a cheaper model ships, teams upgrade to the next expensive one instead of banking the savings. Goldman Sachs projects global token consumption will rise 24x by 2030, as autonomous agents turn a single request into dozens of planning steps, tool calls, and self-corrections. It's a textbook Jevons Paradox, the efficiency gain that was supposed to shrink your bill is instead expanding total consumption. 

And it's compounding with a second, harder problem: recent research shows token usage can be inflated over 1,000% without detection, and 2026 has already produced a real, confirmed multimillion-dollar AI billing error, a new class of AI-bill auditing startups, and public backlash over opaque credit meters in revenue tech are all surfacing the same structural problem: consumption-based AI pricing puts buyers in a position of pure trust, with zero visibility into the number behind the invoice. Meanwhile, the way AI agents access enterprise tools is being standardized by new industry alliances, quietly expanding where and how token costs show up, even outside a vendor's own pricing page.

Join Reddy Mallidi and Maxim Tarasevich for a candid conversation on why "unauditable by design" pricing is becoming untenable, and what leaders should demand instead: predictable, outcome-anchored AI economics.

Key Takeaways:

1. Understand the paradox, not just the price tag: Why falling per-token prices are coinciding with rising total AI spend, and what that means for next year's budget.

2. Know what you can't verify: The structural reasons AI bills resist independent audit, and what recent real-world billing disputes reveal about the risk.

3. See who's building the moat: How the platforms that control enterprise data are shaping the standards that determine where your AI spend goes.

4. Move to spend you can actually predict: What outcome-based, hard-capped pricing looks like in practice, and how to evaluate a vendor against it.