Proof Over Promises: Validating AI-Enabled Performance

Define success criteria and validation methods for AI-enabled building performance use cases.

Distinguish useful AI-supported analysis from false confidence, weak assumptions, or unverified claims.

Identify data quality, commissioning, O&M, and monitoring practices needed to support trustworthy performance insights.

Apply a minimum viable proof plan: data source, metric, human review point, validation cadence, and decision threshold.