Mr. Jaspreet Bindra, Co-founder of AI&Beyond, discussed India’s AI talent landscape with The Hans India, emphasizing the crucial “missing middle” of applied professionals who can effectively translate advanced research into practical applications. He outlined the necessity of this layer, the impact of its absence on AI adoption, and the measures required to fill this structural void. India is currently experiencing an AI surge, with government-supported initiatives like Sarvam and BharatGPT, a plethora of generative AI startups, and ambitious policy frameworks. Despite the excitement, there is a significant issue: the ecosystem is disproportionately focused on research and general digital literacy, lacking in deployment skills.
Bindra referred to the “missing middle” as the applied AI professionals—individuals who may not engage in research but can connect AI research with real-world applications. This group includes AI product managers, ML engineers, data translators, operations specialists, prompt engineers, ethics advisors, and domain experts. They may not create models from the ground up, but they possess the ability to leverage these models, making AI scalable and usable. The scarcity of this applied layer is particularly felt by startups, which require agile teams capable of quickly integrating AI into their operations.
This shortage has led to AI becoming merely a buzzword; many pilot projects fail, impressive demos do not scale, and founders often find themselves having to manually incorporate AI into their products. Larger enterprises and public services face similar challenges: without this “middle,” the vision of “AI for All” struggles to transition from aspiration to reality. Comparatively, in the US and Europe, this middle layer evolved alongside AI research, with deployment and integration skills developing concurrently as new models emerged. In contrast, India’s focus has been primarily on cultivating top-tier researchers and enhancing basic digital literacy while overlooking this crucial intermediary skill set. This imbalance is already apparent in the sluggish pace at which AI is operationalized in India.
To bolster this missing layer, India needs more job-ready professionals rather than an increase in PhDs. The solution lies in vocationalizing AI through bootcamps, certification programs, and targeted upskilling for engineers, analysts, and business leaders. Government skilling initiatives, corporate training programs, and edtech companies should work together to create these pathways. The importance of the “missing middle” in shaping India’s AI future cannot be overstated, as this 30–40% of professionals will determine whether AI remains trapped in pilot projects or transitions into significant deployment. While they may not garner the same attention as groundbreaking models or eye-catching research, their contributions are essential; without them, innovations will stay confined to research labs.
For India to excel not only in AI research but also in practical implementation, investing in this middle layer is imperative.