Saurajit Kanungo, president of CG Infinity, addresses the gap between AI skills and talent that’s endemic in many companies today.

The technology skills gap has long been a reality with companies looking to automate business processes, but with the maturation of artificial intelligence and machine learning, it has become particularly acute. A recent report on AI skills and talent gaps by Skillsoft found that a third of IT leaders are struggling with finding qualified AI and ML talent. 

Boards and top executives are scrambling to adopt generative AI, large language models (LLMs) and other manifestations of the technology, which has advanced dramatically in just the last year. The problem, says Kanungo, is that “there’s a very small pool of talent that everybody’s going after. Things are happening too suddenly. You can’t just invent people with AI [expertise] overnight. It’s just asking for a miracle.”

Businesses fear that if they don’t immediately embrace AI, they’ll be left behind by their competitors. But many are rushing ahead without developing pilots, proofs of concept or programs for training staff in the new technology. “You’re caught between ‘Do I show quick results, or take a step back and reskill my people, so that I can make generative AI a scalable model for my business,’” Kanungo says.

Training expertise needs to come from multiple sources: internal staff, external experts, government programs and the educational world. Kanungo says its vital to simultaneously develop internal teams while drawing on outside resources. “If you’re not doing both, you’re not reacting quickly enough to competitive needs.”

One must ask the question of whether reskilling is possible. Can an existing worker take on a whole new set of skills, or should the organization be bringing in people with existing expertise? Kanungo is a believer in reskilling, especially over the medium to long term. Outsiders don’t possess the intimate knowledge about a company that’s necessary to mount effective training programs, he says.