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Section 1: AI Strategy and Risk Landscape in the Indian Context

Strategic AI Integration and Corporate Responsibility

Taxonomy of AI Risks: From Bias to Hallucinations

Regulatory Horizon: Global Standards vs. Indian Laws

Section 2: The DPDP Act 2023 and AI Compliance

Interpreting DPDP Definitions for AI Ecosystems

Consent, Legitimate Use, and Data Principal Rights

Penalties, Adjudication, and Cross-Border Transfers

Section 3: AI in HR: Managing Workforce Risks

Algorithmic Bias in Recruitment and Talent Acquisition

Workplace Surveillance and Employee Privacy

Automated Decision-Making in Performance Management

Section 4: Establishing AI Governance and Oversight

Structuring the AI Governance Committee

Third-Party Risk Management and Vendor Assessment

Creating and Maintaining an AI Risk Register

Section 5: Policy Drafting and Incident Response

Drafting the Acceptable AI Usage Policy

AI Incident Response and Crisis Management

🎮 Pixel Quest: Corporate AI Governance Challenge

Quiz

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Survey

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AI is now central to competitive advantage in Corporate India—but it comes with material legal, ethical, and operational risks. AI Governance Risk and DPDP Compliance for Corporate India is a practical, board-ready program that translates complex regulation and fast-evolving AI capabilities into actionable controls for Indian enterprises. You’ll learn how to align AI strategy with corporate responsibility, distinguish governance needs for Predictive vs. Generative AI, and build safeguards against bias, hallucinations, IP exposure, and Shadow AI. Grounded in the Indian context, the course compares global frameworks such as the EU AI Act with India’s emerging AI regime, and connects existing statutes like the IT Act and Copyright Act to real-world AI deployments. A dedicated module on the Digital Personal Data Protection (DPDP) Act 2023 helps you operationalize consent, legitimate use, data rights, cross-border transfers, and penalty exposure. You’ll also address high-impact workforce scenarios—from recruitment bias and employee monitoring to automated performance decisions—while building enterprise-wide governance: committees, vendor due diligence, risk registers, policies, and incident response. Through play-based learning in Pixel Quest and a rigorous final quiz, you’ll leave with templates, checklists, and a governance blueprint that reduces risk, accelerates compliance, and enables trustworthy AI at scale.

AI Governance Risk and DPDP Compliance for Corporate India

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            <p>The rapid integration of Artificial Intelligence within the Indian corporate sector has transitioned from a competitive advantage to a strategic imperative. However, this technological leap necessitates a robust framework for governance that aligns with the evolving legal landscape, most notably the Digital Personal Data Protection (DPDP) Act 2023. For Board Members and CXOs, understanding the intersection of AI innovation and fiduciary responsibility is critical to mitigating reputational, legal, and operational risks. This course provides a comprehensive analysis of the AI risk landscape, differentiating between predictive and generative models, while mapping these technologies against the specific compliance requirements of the Indian regulatory environment and global standards.</p>

<p>Beyond high-level strategy, the curriculum delves into the operational complexities of AI deployment, particularly within Human Resources and enterprise data management. Participants will explore the nuances of algorithmic bias, the legalities of automated decision-making, and the stringent transparency obligations mandated for Data Fiduciaries under the DPDP Act. By examining the practicalities of establishing cross-functional AI Governance Committees and drafting enforceable usage policies, leadership teams will be equipped to manage third-party vendor risks and respond effectively to AI-related incidents. This program serves as a definitive guide for Compliance, Legal, and IT leaders to synthesize a roadmap that ensures technological advancement does not compromise ethical standards or statutory obligations.</p>
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