India Needs Its Own 'Small AI', Never Mind ChatGPT

Such models could strengthen pharmaceutical manufacturing, improve production quality, ensure regulatory compliance across multiple jurisdictions, and generate high-value employment.

“India's opportunity lies in 'Small AI', purpose-built, enterprise AI that solves industry-specific problems and gives the country a significant competitive advantage,” said Dr. Amit Sheth, Founder, Indian AI Research Organisation (IAIRO), and Professor, Computer Science & Engineering, University of South Carolina. He was speaking at the Pharma Conclave 2026 organised by The Secretariat in Ahmedabad on Wednesday.

Stressing the need for reliability in enterprise applications, he noted that while consumer AI can tolerate minor inaccuracies, industrial AI demands a far higher degree of precision to support mission-critical operations in the pharmaceutical sector.  

The conclave threw light not only on the evolution of the sector in India but also on the challenges that need to be addressed. "We must build sovereign AI innovation that creates original technology and delivers real-world impact," said Sheth.

AI has transformed the pharmaceutical industry in India, which is the third largest in the world. But the country needs trustworthy, purpose-built models that improve drug discovery, ensure regulatory compliance, and strengthen production quality. It has significantly reduced lab timelines by up to 60% by simulating how molecular structures behave. Further, medical writing and submission preparation times have been reduced by over 50%.

But with greater scalability comes greater responsibility. For India's healthcare system, adherence to global safety standards is non-negotiable. 

We must build sovereign AI innovation that creates original technology and delivers real-world impact

Challenges Of AI In Pharma

Speaking at the conclave, Sheth said, "The future of AI in pharma lies in building trustworthy, purpose-built models that improve drug discovery, ensure regulatory compliance and strengthen production quality."

Sheth stressed that India should focus on developing enterprise-grade AI solutions tailored to the pharmaceutical sector rather than relying solely on generic AI models. 

He said AI must strengthen regulatory compliance, production quality control and drug discovery through knowledge-driven systems capable of improving manufacturing efficiency, reducing wastage and supporting global regulatory requirements. 

Sheth also stated that India must focus on developing enterprise-grade AI systems tailored to pharmaceutical applications rather than relying solely on generic large language models. Stressing that AI for industry demands a much higher degree of reliability than consumer applications, he said.

Sheth is a globally recognised computer scientist, educator, and entrepreneur, who is leading IAIRO at GIFT City in Gujarat. He returned to India after decades of pioneering AI research and innovation in the US to strengthen national AI capability. IAIRO aims to bridge research, industry, startups, and government to turn AI prototypes into deployable products.

Practical Applications

Explaining the practical applications of such systems, Sheth said AI-powered knowledge graphs could accelerate drug discovery, strengthen production quality control and help pharmaceutical companies comply with diverse regulatory frameworks, including those of India, the US, the UK and Europe. 

He also highlighted AI's potential to reduce manufacturing waste, improve documentation, identify production anomalies in real time and shorten the early stages of drug research through data-driven target identification. 

According to Sheth, building original AI intellectual property and application-specific models would not only enhance the global competitiveness of India's pharmaceutical sector but also create a foundation for innovation-led growth.