Are Indian Industries Chasing the Wrong Kind of Intelligence?
As the industry celebrates the rapid rise of large language models (LLMs), voice assistants, and generative AI tools, some experts caution against mistaking fluency for understanding, or prediction for reasoning.
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In an era where artificial intelligence is making headlines every day, a crucial question is emerging: Are we chasing the wrong kind of intelligence? As the industry celebrates the rapid rise of large language models (LLMs), voice assistants, and generative AI tools, some experts caution against mistaking fluency for understanding, or prediction for reasoning.
In an exclusive conversation with MIT SMR India, V. Ramgopal Rao, Vice Chancellor of the BITS Pilani group of institutions and former Director of IIT Delhi, said much of what is celebrated as “AI” today lacks the essence of real intelligence.
“Today’s AI systems, especially the large language models, are remarkable in many ways, but they are essentially very advanced autocomplete engines. They predict well, but they don’t understand,” Rao said. To him, real intelligence is about learning with limited examples, adapting across situations, and making sense of the world in a contextual and meaningful way.
This divergence between technological capability and true understanding is not just philosophical. Rao said that the overemphasis on comput-intensive models, driven by investor hype and short-term commercial success, may skew research priorities and infrastructure investments. “We are at a point where the ability to sound intelligent is being mistaken for actual intelligence. That’s a serious risk, especially when decisions in healthcare, education, or law are involved,” he said.
According to him, academia should be the conscience keeper of AI. It must ask the uncomfortable questions, protect long-term thinking, and keep the field anchored in ethics and societal needs. Universities can create space for interdisciplinary conversations, incorporating philosophy, law, and the social sciences, to ensure AI development remains humane and inclusive.
Rao’s call for a course correction in AI research is timely, especially as regions like Karnataka begin laying the groundwork for more inclusive, sustainable, and globally relevant digital innovation.
Karnataka’s Pivot Toward Deeper Innovation
While tech investors and companies globally continue to double down on generative AI, Karnataka’s digital strategy, as outlined by Sanjeev Kumar Gupta, CEO of the Karnataka Digital Economy Mission (KDEM), looks at a broader and potentially more grounded approach.
Through initiatives like the India Digital Innovation Conclave (IDIC), the state is seeking to brand its innovation ecosystem on the global stage, not just through Bengaluru, but by energizing tier-II and tier-III cities like Mangaluru, Hubbali, and Mysuru. “Our next frontier is to strengthen, deepen, and energize these ecosystems further,” Gupta told MIT SMR India.
To do that, KDEM is investing in foundational ecosystem services like seed funding, mentorship, accelerator networks, and industry linkages, especially in Beyond Bengaluru clusters. These efforts are not just about creating more startups, but about fostering better innovation.
“We’ve launched a Cluster Seed Fund dedicated to startups from those specific regions. We’ve also created the Karnataka Accelerator Network, which links accelerators in Beyond Bengaluru with those in Bengaluru, facilitating knowledge sharing and growth,” Gupta said.
One notable example is the state’s Global Innovation Alliance (GIA), which has helped connect Karnataka’s startups with markets and government partners across about 30 countries. A cybersecurity startup from Karnataka gaining traction in the Netherlands through this program is just one of many quiet wins in this global outreach.
According to Rao, India needs more focus on areas that combine learning with reasoning and perception with action. Edge AI, neuromorphic computing, AI for social impact, and tools that enable human-AI collaboration all deserve more investment, he said.
“Startups working on trust, interpretability, and transparency are often ignored because they don’t fit neatly into current business models. But these are the very things that will ensure AI is sustainable and safe in the long run,” he said.
A Convergence of Perspectives
What emerges from these two conversations, one academic and the other policy-driven, is a subtle yet significant convergence. Rao said that real intelligence in AI demands reasoning, ethics, and interdisciplinary inquiry. Meanwhile, Gupta’s KDEM is building a digital economy that privileges decentralization, global collaboration, and long-term ecosystem building.
Both point to the same truth: chasing superficial intelligence may offer immediate returns, but building meaningful, sustainable intelligence, real intelligence, requires patience, perspective, and a different kind of investment.
As Karnataka positions itself not only as India’s tech hub but also as a thoughtful global player in digital innovation, it may be asking the right questions and quietly steering the AI narrative in a more grounded direction.
