Shift Technology Targets 10x Staff Output By Tiering AI Model Costs

The Common Question

How can insurtech companies control rising AI token costs before they spiral?

The Lesson in This Case

Shift Technology is targeting a tenfold increase in output per employee, aiming to produce the equivalent of 7,000 full-time workers from a staff of 700, by routing AI tasks to models matched to their complexity and cost. The company benchmarks models weekly, assigning simple tasks to cheaper models and the most demanding work to premium ones, treating inference tiering as an ongoing operational discipline. Senior leaders building AI into claims or fraud workflows should treat model cost benchmarking as a standing function, because token consumption is rising faster than prices are falling and unmanaged usage has already cost some enterprise teams tens of thousands of dollars in a single month.

Originally reported by Insurance Business. Read the full story here.