Fixing India’s AI Skills Gap: Why the “Missing Middle” Matters

India seems to be riding high on AI optimism. What do you think of the current landscape?

India is in the midst of an AI revolution. We have government-backed models like Sarvam and BharatGPT, a wave of generative AI startups, and ambitious policy roadmaps. There is no shortage of excitement, but beneath all this optimism lies a weakness—our ecosystem is heavily skewed toward research and broad digital literacy, while we are thin on deployment expertise.

You’ve spoken about a “missing middle” in India’s AI talent. What exactly does this mean?
The “missing middle” refers to applied AI professionals—people who may not be researchers, but who can bridge AI research with real-world applications. These include AI product managers, ML engineers, data translators, operations specialists, prompt engineers, ethics advisors, and domain experts. They don’t necessarily build models from scratch, but they know how to build with them, making AI usable at scale.

How is the absence of this applied layer impacting startups and enterprises?
Startups are feeling the pain first. They need lean, agile teams who can integrate AI into workflows quickly, but such talent is scarce. As a result, AI often becomes a buzzword—pilots fail, demos impress investors but don’t scale, and founders themselves end up stitching AI into products. Larger enterprises and even public services face the same challenge: without this middle, the vision of “AI for All” struggles to move from ambition to execution.

Globally, how has this “middle” evolved compared to India?
In the US and Europe, this layer matured alongside AI research. As new models were developed, skills in deployment, integration, and scaling grew in parallel. India, however, has focused on building world-class researchers and boosting basic digital literacy, while neglecting this middle ground. The imbalance is already evident in how slowly AI is operationalised here.

What should India do to strengthen this missing layer?
We don’t need more PhDs; we need more job-ready professionals. The answer lies in vocationalising AI—bootcamps, certification programs, and targeted upskilling for engineers, analysts, and business leaders. Government skilling missions, corporate training, and edtech companies must step in to create these pathways.

Why do you believe the “missing middle” will define India’s AI future?
Because this 30–40% of professionals will decide whether AI remains stuck in pilot projects or moves into meaningful deployment. They may not grab headlines like big models or flashy research, but without them, breakthroughs won’t leave the labs. If India wants to lead not just in AI research but also in execution, investing in this middle is non-negotiable.