Real-World AI Evaluation: How FRAME Generates Systematic Evidence to Resolve the Decision-Maker's Dilemma

FRAME (Forum for Real World AI Measurement and Evaluation) addresses the challenge organizational leaders face in governing AI systems without systematic evidence of real-world performance. The framework combines large-scale AI trials with structured observation of contextual use and outcomes, utilizing a Testing Sandbox and Metrics Hub to provide actionable insights.

• →FRAME bridges the gap between scalable abstract AI evaluations and small-scale contextual testing.
• →The framework traces AI system outputs through practical use to downstream effects for comprehensive measurement.
• →A Testing Sandbox captures AI use under real workflows at scale for systematic evaluation.
• →A Metrics Hub translates usage traces into actionable indicators for decision-makers.
• →The approach turns real-world AI heterogeneity into measurable signals rather than evaluation trade-offs.