As artificial intelligence rapidly reshapes global economies, nations are racing to build sovereign capabilities, scalable infrastructure, and future-ready talent. Amid this accelerating competition, India stands at a critical inflection point, balancing opportunity, ambition, and execution. In an exclusive conversation with Tech Achieve Media at the India AI Impact Summit 2026, Dhrubabrata Ghosh, Managing Director – Data Analytics and Digital Transformation at Protiviti, offers a sharp and grounded perspective on where India truly stands in the global AI race, why enterprise adoption remains uneven, and what strategic steps can transform India into a global AI powerhouse. From sovereign AI models and digital public infrastructure to talent readiness and infrastructure investment, he outlines the road ahead for India’s AI-led future.
Also read: Telecom Will Power India’s AI Future: COAI at India AI Impact Summit 2026
TAM: There’s a lot of debate on whether AI is still a buzzword or has actually moved into real-world business impact. What’s your view?
Dhrubabrata Ghosh: AI has definitely moved beyond being a buzzword. If you look at recent advancements, across software models and even hardware, it’s clear that AI is fundamentally changing how businesses operate. Take software development, for instance. A large portion of coding and development will now be done using advanced AI models, completely altering how services are delivered. This is no longer hype; it is a real shift that is transforming business models, service delivery, and operational efficiency.
Also read: Embracing the AI Revolution: Sachin Tayal, MD, Protiviti
TAM: We often hear that AI pilots are successful, yet very few move into large-scale implementation. Why does this gap exist?
Dhrubabrata Ghosh: There are three major bottlenecks. First, data quality. AI is only as good as the data it consumes. While we have strong digital infrastructure, the quality, consistency, and readiness of enterprise data are still major challenges. Second, human resistance and fear. People worry about fully autonomous systems replacing them. Adoption improves significantly when organizations move toward semi-autonomous systems with humans in the loop, where decision-making remains human-led. Third, lack of a clear business case. Earlier, companies adopted AI simply because it was trendy, without evaluating whether it actually delivered measurable business value. If a task takes only a few hours a month, it may not require AI. Today, enterprises are becoming more mature and outcome-driven, which is improving adoption.
TAM: There is widespread discussion about India lagging in foundational AI models. Has that changed?
Dhrubabrata Ghosh: Yes, significantly. India has already begun building sovereign AI models. Initiatives like Param 2, Sarvam AI, and Bhashini are strong examples of LLMs being developed specifically for Indian languages and contexts. Many organizations are actively contributing to this ecosystem. Infrastructure is a key enabler here, and the government is investing heavily. Over the next 6–12 months, we will see a sharp rise in Indian-language models, which will be critical for financial services, governance, healthcare, and public services.
TAM: Should India also focus on foundational layers like chips and GPUs, similar to how Nvidia built dominance?
Dhrubabrata Ghosh: In semiconductors, India is several years behind, so it’s a long-term catch-up game. However, when it comes to sovereign AI models, India is very much in the race and on time. Foreign LLMs struggle in Indian contexts due to language complexity, cultural nuance, and inherent bias. Indian enterprises, banks, and government bodies require India-trained models. That’s why sovereign AI development is essential and transformative for our ecosystem.
TAM: India’s DPI success, Aadhaar, UPI, CoWIN, is globally admired. Why hasn’t it been replicated worldwide at the same scale?
Dhrubabrata Ghosh: India excels at application development layered on strong infrastructure. UPI is a perfect example, and it is an application built over a robust digital backbone. Once we establish our foundational AI models, India will rapidly create a massive ecosystem of AI-driven applications. Just as India mastered digital payments and quick commerce, we will see similar innovation in AI. These applications will not only scale domestically but will also become global exports, positioning India as a leader in applied AI.
TAM: Do you see India achieving the same global dominance in AI that it achieved in IT services?
Dhrubabrata Ghosh: Absolutely. While Indian IT firms may have entered the AI race slightly later, they are adapting very quickly. India’s deep services mindset, engineering talent, and application-first approach will help drive large-scale AI deployment.
AI will become a major growth driver for India, powered by both global service firms and a vibrant domestic innovation ecosystem.
TAM: In your view, what are the three most important steps India must take?
Dhrubabrata Ghosh: Here’s what would help India do that:
- Infrastructure: Massive investments in data centers and compute capacity.
- Skills: Large-scale upskilling, reskilling, and training of talent in AI technologies.
- Sovereign AI Models: Building our own foundational LLMs tailored for Indian languages, data, and use cases.
These three pillars will define India’s journey from being a strong technology adopter to becoming a true global AI superpower.
