This whitepaper focuses on why AI governance is foundational to achieving sustainable AI success. It describes how organizations face mounting pressure from regulators, customers, and internal stakeholders to prove AI systems are ethical, explainable, and compliant. The paper outlines governance principles covering data sourcing, model transparency, accountability, and lifecycle management. It stresses the need for cross-functional collaboration between data, legal, risk, and business teams. The paper concludes that embedding governance early enables organizations to reduce risk, improve trust, and scale AI initiatives faster without sacrificing control.

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