India is charting a different course on AI regulation, combining advisory frameworks with targeted data protection policies rather than rushing into strict legislation like the European Union. This flexible approach, sometimes called "smart experimentation," allows the country to observe how global regulatory models evolve while protecting citizens and fostering innovation. The strategy reflects a broader recognition that one-size-fits-all AI governance may not work for countries with vastly different economic structures and technological maturity levels .

What Makes India's AI Governance Model Different?

Rather than implementing comprehensive AI legislation immediately, India has adopted a layered approach that combines multiple policy tools. The country has introduced the Digital Personal Data Protection Act, which addresses privacy concerns without imposing the kind of strict compliance requirements found in the European Union's AI Act. This strategy allows India to test different governance mechanisms in real-world conditions before committing to permanent regulatory frameworks .

The flexibility of India's approach stems from recognizing that emerging economies face unique challenges that developed nations may not encounter. Large portions of India's population operate outside formal economic systems, meaning that AI policies designed for traditional employment structures may miss critical vulnerabilities. By maintaining adaptive governance frameworks, India can adjust its policies as new risks emerge and as global best practices become clearer .

How Can Countries Implement Inclusive AI Governance?

• Linguistic Diversity Investment: Prioritize developing sovereign AI models capable of supporting local languages and cultural contexts, ensuring that AI systems serve populations beyond English-speaking users and major global languages.
• Practical AI Literacy Programs: Launch initiatives targeting farmers and informal workers with real-world AI applications such as crop monitoring, weather prediction, and multilingual chatbot support to bridge digital divides.
• Flexible Regulatory Frameworks: Combine advisory guidelines with targeted data protection policies rather than implementing rigid legislation, allowing governments to observe global regulatory evolution and adjust policies accordingly.
• Global South Representation: Ensure that governance discussions include voices and perspectives from emerging economies, preventing policies designed solely around developed-world concerns from overlooking unique vulnerabilities in other regions.

Why Does AI's Impact on the Global South Matter for Regulation?

AI's uneven impact across different regions creates urgent governance challenges that policymakers cannot ignore. In emerging economies, artificial intelligence threatens to deepen existing inequalities through job displacement in informal sectors, the spread of deepfakes, and widening digital divides for communities without access to digital tools. These risks are particularly acute in countries where large portions of the population operate outside formal economic systems, making traditional employment-focused AI policies inadequate .

The challenge extends beyond economic disruption. Linguistic diversity represents a critical governance gap that most global AI discussions overlook. Most AI systems today are optimized for English and a handful of major languages, leaving billions of people in non-English-speaking regions with limited access to AI tools that understand their languages and cultural contexts. This technological gap can perpetuate economic disadvantages and limit opportunities for communities already facing digital exclusion .

"Understanding how technologies can be misused provides valuable insight when designing safer and more ethical AI systems," explained Maya Sherman, an AI policy researcher and technology diplomat associated with the Oxford Internet Institute.

Maya Sherman, AI Policy Researcher and Technology Diplomat, Oxford Internet Institute

Sherman's background in monitoring darknet spaces and tracking cybercrime shaped her conviction that cybersecurity and AI ethics must go hand in hand in modern governance frameworks. This perspective is particularly relevant for emerging economies, where cybersecurity infrastructure may be less developed and where malicious uses of AI could cause outsized harm .

What Role Does AI Play in Supporting Rural Communities?

India's governance approach includes practical initiatives demonstrating how AI can benefit populations often left behind by technology. Through programs linked with the Global Partnership on AI, farmers have been introduced to practical AI applications that address real agricultural challenges. These include crop monitoring systems that track plant health, weather prediction tools that help farmers plan planting and harvesting, and multilingual chatbot support that breaks down language barriers to accessing agricultural information .

In a country with extraordinary linguistic diversity, where hundreds of languages are spoken across different regions, AI-powered translation tools could become a powerful enabler of digital inclusion. Rather than requiring farmers to learn English or major regional languages to access AI tools, locally optimized systems could deliver information in the languages farmers actually speak. This approach transforms AI from a tool that primarily benefits educated, English-speaking populations into a resource that serves entire communities .

The philosophical challenge of AI governance, as Sherman noted, lies in navigating the paradoxes inherent in the technology itself. Artificial intelligence was originally designed to increase efficiency and productivity, yet it now raises complex ethical questions about fairness, bias, and social impact. For policymakers in emerging economies, the challenge of AI governance involves embracing these "gray areas" where technology intersects with society, rather than seeking simple regulatory solutions .

India's flexible governance model offers a template for other emerging economies facing similar challenges. By combining advisory frameworks with targeted protections, investing in linguistic diversity, and ensuring that policy discussions include voices from the Global South, countries can develop AI regulations that protect citizens without stifling innovation. As global AI governance continues to evolve, the lessons from India's approach may prove as valuable as the regulatory frameworks emerging from more developed nations.