Compliance for Artificial Intelligence in Business - Legal and Ethical Perspective

Artificial Intelligence (AI) is becoming a cornerstone of digital transformation in Indian businesses. From predictive analytics in retail to credit scoring in finance, chatbots in customer service, and automation in logistics, AI is reshaping operational models and strategic priorities. However, this rapid adoption has outpaced the development of adequate legal and ethical governance frameworks, both within companies and across jurisdictions.
India is in the midst of a regulatory transition aimed at establishing robust governance frameworks for AI, data protection, and algorithmic accountability. The enactment of the Digital Personal Data Protection Act, 2023 (DPDP Act) marks a watershed moment in India’s approach to data privacy, mandating businesses to implement lawful data processing, obtain valid consent, and ensure data fiduciary accountability. Furthermore, the Indian government has released a series of discussion papers and strategy documents (e.g., NITI Aayog’s Responsible AI Guidelines, Ministry of Electronics and IT's India AI strategy) signaling its commitment to developing a comprehensive regulatory and ethical framework for AI. Sector-specific regulators like RBI, SEBI, and IRDAI are also increasingly scrutinizing algorithmic decision-making, particularly in finance and fintech.
At the same time, Indian companies must remain aware of cross-border legal obligations; such as the EU GDPR, the EU AI Act, and evolving US regulations, especially if they operate in international markets, process offshore data, or engage with global supply chains.
However, strategic importance of AI governance is no longer confined to legal risk mitigation. It is becoming a cornerstone of corporate responsibility, brand trust, and long-term business viability in the digital economy. Businesses must also contend with rising ethical expectations from customers, employees, investors, and civil society. Ethical failures in AI systems; such as algorithmic bias, opaque decision-making, and unintended discriminatory outcomes, can result in reputational damage, regulatory investigations, loss of consumer trust, and even legal liability. Several high-profile international cases have underscored the risks of ignoring ethical responsibilities in AI deployment
• Amazon had to shut down an AI recruitment tool after it was found to systematically discriminate against female candidates by penalizing resumes that included the word "women."
• Facebook (Meta) faced backlash and regulatory scrutiny over its content recommendation algorithms that amplified misinformation and polarization—raising ethical questions about autonomy, manipulation, and social harm.
• Apple and Goldman Sachs were criticized for offering AI-driven credit limits through the Apple Card that allegedly offered significantly lower credit limits to women compared to men, even when their financial profiles were comparable.
• In India, growing use of automated surveillance tools and facial recognition systems by businesses and government agencies has triggered debates about privacy, consent, and the disproportionate impact on marginalized communities.

These examples reveal a common thread: AI systems can unintentionally encode and amplify societal biases if not carefully designed, governed, and tested for fairness, transparency, and accountability. In a business context, these risks can affect hiring, lending, pricing, customer segmentation, insurance underwriting, and more. In today's climate, organizations cannot afford to treat AI ethics as an afterthought or merely a compliance checkbox. Instead, embedding ethical safeguards into AI lifecycle management, from design and data collection to deployment and monitoring, has become a business imperative
For business leaders in India, this makes it imperative to develop a deep understanding of:
• how AI compliance intersects with emerging Indian and global legislation;
• how to operationalize responsible AI principles in global business context; and
• how to prepare organizations for regulatory oversight and ethical scrutiny.

The Program Instructor, Parul Gupta, has been teaching at MDI Gurgaon and has written and published extensively on Legal and ethical aspects of AI and technology in business. Not only is Professor Gupta a leading academician and trainer, but she also utilizes a case-study approach to explaining the topic, which creates a unique, practical and enriching training experience.