AI Token Costs Fall While Enterprise AI Spending Climbs
Techstrong.ai, Wednesday, September 30th, 2026
ABBYY's Jon Knisley explains why cheaper tokens don't shrink AI bills as agents multiply model calls.
On a Techstrong AI video, ABBYY's Jon Knisley tells Mike Vizard that falling token prices don't guarantee smaller AI bills, a version of Jevons Paradox, as agents make repeated model calls, invoke tools and add reasoning steps.
Knisley recommends routing tasks to the right model, using frontier models only for demanding reasoning and cheaper or domain-specific models for routine work, and notes that restructuring documents can cut token counts.
In a lease-extraction project, combining traditional ML with generative AI beat an LLM alone, showing the need to measure accuracy and outcomes, not just token costs.