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AI Governance Checklist: How to Manage Risk & Ethics (Executive AI Strategy) | Decode AI with Niraj

The future of AI success isn't just about ROI—it’s about Governance. In this essential executive masterclass, Niraj reveals the AI Governance Checklist every C-suite leader needs to manage risk, ensure AI Ethics, and build a defensible AI strategy. Learn the non-negotiable steps to protect your enterprise from costly compliance breaches and 'black box' liabilities.

We move beyond legal jargon to establish a predictable, ethical, and scalable foundation for all your AI initiatives.

🔑 KEY TAKEAWAYS:

Accountability Layer: Define the Business Process Owner (P&L impacted) who must be accountable for every model's output, eliminating black box risk.

Drift Tolerance: Set mandatory thresholds for model retraining and human intervention when real-world data causes accuracy to degrade.

Regulatory Scrubber: Implement audit processes to scrub biased historical data and ensure compliance with global data privacy laws (GDPR, CCPA).

AI Review Board: Structure a multi-functional committee (Legal, Risk, Tech) to vet all high-risk deployments before they launch.

The Trust Mandate: Understand how governance is the ultimate lever for building trust with customers, regulators, and leadership.

⏱️ TIMESTAMPS:

0:00 - The C-Suite Mandate: Risk vs. ROI
0:40 - Checklist 1: Establish the Accountability Layer
1:20 - Checklist 2: Define Drift Tolerance (Managing Model Decay)
1:50 - Checklist 3: Implement the Regulatory Scrubber (Bias & Compliance)
2:30 - Checklist 4: Create the AI Review Board
3:10 - The Ultimate Goal: Building Trust
3:50 - Conclusion & What’s Next

➡️ NEXT STEPS:

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