The future of talent management: AI’s role in skills assessment, mapping and career development

Talent managers must demand more from next-gen AI tools.

Even before ChatGPT took the world by storm, AI was being hailed as the next big thing in hiring and talent development. Automated screening has become the status quo, and employers and tech entrepreneurs have for years been experimenting with ways AI tools could be used for more sophisticated skills-based hiring. 

And now, next-generation AI — and the investment gold rush — is leading to an explosion of new skills assessment, mapping and matching software. Both companies and policymakers are bought in. Alabama, for example, just launched a new AI-powered skills marketplace for the entire state.

For talent managers, the next few years are going to be a feast of riches. And a feast of pitches.

Before you dive in, it’s important to understand what AI tech does well and where it still has major limitations. First, talent leaders should be crystal clear about what AI cannot replace: a sustained commitment to upskilling and reskilling, with sufficient resources and structures that drive career mobility within their own workforce. Those are foundational pieces of any talent strategy.

What technology and AI can do is provide a big assist. AI is already good at parsing many known knowns — things like making sense of skills data. We know skills are critical to any job, but we just can’t make sense of all the variables. AI tech can help.

That’s great, because assessing skills, mapping requirements, and making recommendations for upskilling are all critical to opening up opportunities for more frontline workers and others who may not have a college degree. But while making sense of skills is essential, it’s also not sufficient.

Every successful career is built on more than skill — things like interests and values, a sense of what’s possible, and social and professional networks. In other words: if developing the right knowledge and skills is the core of preparing for a job, then career exploration and career readiness are the equally essential book ends.

While AI tech isn’t currently as good at helping with those things, it can be.

For example, Uplimit, an online learning company that offers a host of technical and business courses, now uses an AI bot as a teaching assistant. Its primary function is around skill development — such as answering student questions or providing feedback on code — but it also is an important engagement tool, providing a kind of “moral support,” according to a recent feature in Fast Company

In France, Bayes Impact developed a chatbot, named Bob, that provided career advice to more than 200,000 workers at the height of the pandemic. One in two workers who interacted with the bot said its coaching was a key factor in their job recovery, though other research on its impact has been mixed. AI-powered bots and text messaging have also been effective in increasing applicant and student engagement in higher education, with early signs that they could work in increasing job candidate engagement for companies as well.

Such uses of AI are promising, but pale in comparison to the energy going into AI and skills mapping and development. We need much more focus on deploying tech around career exploration and career readiness — but entrepreneurs aren’t going to develop those tools unless companies demand them. Talent managers should be leading those conversations in their organization and with their vendors.

Few employees are aware of the array of jobs in their own company out there, let alone the whole marketplace — and they can’t want the perfect job they don’t know exists. (Nor do they know the skills they might need for these roles.) When it comes to finding that “perfect” job, factors like values and interests play a significant role in match quality, and ultimately, employee engagement, productivity and retention. 

In other words, upskilling and skills matching efforts will fall short if career exploration doesn’t happen first.

Similarly, career readiness — such as practicing workplace behaviors and knowing how to grow and activate a professional network — is an essential bookend to skilling. The research is clear: opportunity gaps aren’t just about what people know, they’re also about who people know. While AI can’t build a professional network for you, it could provide feedback on networking emails or role play a conversation. It could recommend connections based not just on your work history and who you already know, but also on ideas about where you’d like to go in your career.

Talent managers should be demanding more of that from their organizations and vendors. If AI is going to make it easier to identify, grow and deploy talent, we can’t just focus it on skills matching and training. What happens before and after matters just as much.