How to reskill your workforce at scale in the age of AI

When we were developing the ideas that have become LearnerShape, we were highly motivated by very visible examples of large companies investing in reskilling and upskilling — AT&T and Amazon in particular.

In 2018, AT&T decided to invest $1 billion in its Future Ready program to reskill 100,000 of its 250,000 employees over a decade. AT&T’s senior executive vice president of human resources Bill Blase put it like this:

“We could go out and try to hire all these software and engineering people and probably pay through the nose to get them, but even that wouldn’t have been adequate. Or we could try to reskill our existing workforce so they could be competent in the technology and the skills required to run the business going forward.”

Then in 2019 Amazon announced that it would spend $700 million to retrain 100,000 employees in new technologies. And when Amazon does anything big, it’s worth paying attention.

A common feature of the AT&T and Amazon programs is that they were built by the companies in house. There was no vendor who could supply the resources needed for reskilling at this scale.

It’s obvious to us at LearnerShape that many other companies are facing the same challenges. This is particularly so in fast-changing sectors, or where there is other disruption from technological change. And companies that do not have the scale of Amazon or AT&T will not have the resources to do this effectively themselves. Helping companies and other organizations address this challenge is at the heart of what LearnerShape does, using advanced AI and data science to manage the complex data and computational tasks required.

For users, the process is straightforward (there is complicated data science behind it):

• Current employee skills are assessed for each employee (assessment can be handled by the company, third parties or the employees themselves, with LearnerShape tools available to help).
• The company defines target skills profiles for planned future jobs, and how many people are required for each job.
• The LearnerShape platform (a) recommends which current employees are best suited for each future position and (b) enables individualized learning pathways for each employee to attain their target future job. (These two sets of recommendations are connected, because job recommendations are based upon the length and cost of the learning pathways.)

Our current beta platform (please sign up as an individual or organization!) provides most of these functions, and the full workflow above will be launching with our advanced beta version in November. Please sign up for our newsletter or watch this site for further details.

Maury Shenk
Co-Founder & CEO, LearnerShape