AI Adoption in the Enterprise: Risks, Wins, and Guardrails

Start with high-value, low-risk pilots and instrument them for learning. Governance should combine technical review, human oversight, and clear escalation paths. Invest in model monitoring, lineage, and explainability for critical applications. Successful programs connect AI to measurable KPIs and embed cross-functional ownership.

Start with high-value, low-risk pilots and instrument them for learning. Governance should combine technical review, human oversight, and clear escalation paths. Invest in model monitoring, lineage, and explainability for critical applications. Successful programs connect AI to measurable KPIs and embed cross-functional ownership.

Start with high-value, low-risk pilots and instrument them for learning. Governance should combine technical review, human oversight, and clear escalation paths. Invest in model monitoring, lineage, and explainability for critical applications. Successful programs connect AI to measurable KPIs and embed cross-functional ownership.

Start with high-value, low-risk pilots and instrument them for learning. Governance should combine technical review, human oversight, and clear escalation paths. Invest in model monitoring, lineage, and explainability for critical applications. Successful programs connect AI to measurable KPIs and embed cross-functional ownership.

Start with high-value, low-risk pilots and instrument them for learning. Governance should combine technical review, human oversight, and clear escalation paths. Invest in model monitoring, lineage, and explainability for critical applications. Successful programs connect AI to measurable KPIs and embed cross-functional ownership.