AI Evals For Leadership

Apply consistent evaluation criteria to AI proposals, pilots, and vendor solutions before approval.

Enable leaders to justify AI decisions confidently to boards, auditors, and regulators.

Reduce ad-hoc or politically driven AI decisions through structured, repeatable assessment.

Ensure AI initiatives directly support organizational strategy or public service objectives.

Prioritize AI funding based on measurable value, not technical novelty.

Strengthen accountability for AI spend by linking outcomes to mission and mandate.

Identify bias, fairness, and explainability risks early in data and model design.

Reduce exposure to regulatory, legal, and public trust failures.

Equip leaders to intervene before AI issues escalate into crises.

Define decision rights, approval authorities, and escalation paths for AI systems.

Clarify leadership ownership across business, technology, and compliance teams.

Ensure AI remains under executive and board control, not vendor or technical drift.

Track AI performance, drift, and risk after deployment—not just at launch.

Enable timely decisions to pause, modify, or retire AI systems when needed.

Maintain long-term trust, reliability, and value through continuous oversight.