Rewire for AI first, then aim to upskill

India's shortage of AI talent could delay tech adoption unless companies rethink their skilling strategies and ensure productivity gains spread across the broader enterprise ecosystem. The demand for workers is divided into a core group of AI builders and a broader set of AI translators. The first category requires upskilling existing tech talent, while the second should benefit from the spread of AI literacy. More AI isn't always better for enterprises, which need to assess organisational benefits before expanding deployment. AI readiness will vary across industries, and a market-led approach to adoption can help prevent the skills shortage from ballooning.

Demand for AI talent will hinge on the governance structures enterprises build and the workflow processes designed to democratise technology adoption. Brands are increasingly mindful of market sensitivity to AI's ethical development, while companies require clarity on the technology's impact on the bottom line. The compute and energy costs of deploying AI solutions act as a signalling mechanism for enterprises - as these costs decrease, greater collaboration will be needed to improve the supply response to AI skilling. Typically, companies should test their AI readiness, identify skill gaps, upskill their workforce, and then enter the market for fresh AI talent. Naturally, this response will be shaped by specialised AI needs across industries.

Companies that tailor their AI adoption pathways to competitive intensity will help keep AI talent costs within limits as the supply response catches up. However, this alone won't solve India's looming talent shortage. The market will push businesses to close internal skills gaps before generating fresh demand for AI talent.