Deploying an AI Agent that uses an outcome-based pricing model means you only pay for value you receive, but this can make forecasting spend difficult. In the latest edition of the Blueprint newsletter, Senior Data Scientist at Fin, Eoin Gilligan Martyn, shares practical advice about how to build a baseline forecast you can present to your CFO and address any concerns they might have about runaway AI spend.
Intercom's look at deploying an AI agent that uses an existing knowledge base is practical. Where do you draw the line between agent answers and a human handoff?
Mary Austin
1w
Outcome-based pricing aligns incentives with results, but it does make budgeting less predictable. Clear usage assumptions and spending guardrails can help balance value with forecastability.
SYSVIT
1w
Good read for anyone rolling out AI agents. Paying only for results is appealing, but a CFO will want a forecast first, so putting a baseline together early makes sense.
A baseline forecast for outcome based AI agent spend that a CFO will accept is rare and useful. Teaching beats pitching, and keeping the cost story simple is how rollouts survive. What unit are you forecasting on, resolutions or conversations?