How AI is revolutionizing training Posted on : Apr 07 - 2021

Pressed by the need to fill skills gaps, organizations are turning to artificial intelligence to transform stagnant training approaches into continually evolving upskilling strategies.

Employee training is an issue of critical importance for enterprises. Challenged to find skilled employees, sapped by high turnover rates, mired in massive transformations, the need to upskill and cross-train employees is paramount — and almost too much for traditional approaches to training to handle.

Enter AI.

Artificial intelligence and machine learning are increasingly being leaned on to aid in companies’ upskilling strategies, ascertaining skill sets, recommending learning paths, providing on-the-job training — even helping determine what to pay for acquired skills.

With more than 345,000 employees and an ever-present need to stay ahead of the technology curve, IBM is one such company putting AI to work in keeping its workforce sharp.

“The half-life of skills is now five years,” says Anshul Sheopuri, chief technology officer for data and AI at IBM HR. “Half of what you learn is either forgotten or becomes obsolete in five years.”

Demand for new and specialized skill sets from rapidly evolving domains such as cloud computing and AI is in large part fueling this compression of skills shelf lives. So finding a scalable way to continuously improve employee skills is “not a nice-to-have but a must-have,” he says.

Anatomy of an AI-based training strategy

The first step of any upskilling strategy is to identify what skills employees currently have. In the past, this would involve a skills self-assessment. But as Sheopuri points out, when tested, the accuracy of this method was about 75%. “It’s highly subjective and the assessments become obsolete quickly.”

Today, IBM is using AI to infer skills by scanning 220 million internal documents, including resumes, blogs, published papers, and corporate communications. The system leans on IBM’s own AI system, Watson, and it includes natural language processing, clustering, and semi-supervised learning techniques.

“We say, ‘These are the skills we think you have, give us your feedback,’ and we find the accuracy here is closer to 90%,” he says, adding that these automated skill assessments are easier to keep current. View More