How AI Can Help You Fill Your Team’s Skills Gaps

Artificial intelligence can do a lot more than write a newsletter, a blog post on the latest trend, or your next resume. With care, intention, and a firm grasp of facts and data, AI can help you identify, analyze, and plug skills gaps in your team or organization.

A 2025 study by Georgetown University’s McCourt School of Public Policy found that of 561 occupations surveyed in the US, 171 would face significant skills shortages through 2032. For nine of those occupations – including education, engineering and healthcare – researchers rated the shortage as “critical.”

It’s possible to conduct skills gap analysis on your own – but for three key reasons, it’s advantageous to put AI to work for you instead of trying to do all the heavy lifting yourself.

What are the advantages of AI in skills gap analysis?

1. AI analysis is faster and more comprehensive than manual analysis

Effective skills gap analysis requires a huge amount of employee data –performance, previous training, and work quality assessments – as well as insights about the future skills required by someone in a particular field and position.

Doing that on your own can be almost a full-time job. Between entering all the needed data and researching emerging trends, not only in your industry but in many others, and doing the same  for the potential employee pool, there’s a lot to keep track of.

But AI can do all that in a fraction of the time, freeing your time and energy to focus on other duties and goals.

2. AI analysis is less susceptible to bias than managerial analysis

Even the fairest manager, supervisor or HR partner is human. Humans have biases – not conscious ones, necessarily, but they’re there – and they’re not always biases against someone.

A team member we like – who works hard and always asks for more duties – might receive a more optimistic analysis, either of their skills or of their potential for acquiring more. Conversely, a high-potential employee with a blunt communication style – someone who’s skilled at identifying issues and solutions but not so diplomatic about communicating those things – might be slated for “soft skills” training when what’s really needed is developing big-picture skills for quality control management.

AI takes feelings and personalities out of the equation. It shows you what really is and what really needs to happen based on the data and needs that matter.

3. AI analysis is less susceptible to error than self-reporting

Just as managers and leaders can be susceptible to bias and error, employees aren’t always the best judges of their own skills, needs and potential.

For example, employees might grade themselves as more highly skilled than they really are in an area where high performance can be explained by some other factor. Perhaps they work alongside someone who’s more skilled and doesn’t mind helping out without taking credit. Or, maybe, they seem to perform highly in one area because they’re spending more time on it than the task should require.

On the other hand, a team member might report a skills gap in an area where the issue isn’t skill – it’s substandard equipment, or not enough time to perform a task, or even distracting micromanagement.

Again, AI bypasses that bias – whether positive or negative – to perform its analysis based upon relevant information: automated and standardized skills tracking, real-time insights and scalable planning that’s based on data, not impressions.

Use AI prompts and tools properly

Using AI to analyze skills gaps in your team or company isn’t a simple matter of plugging prompts – even carefully crafted ones – into a chatbot such as Copilot, Grok, or ChatGPT.

For one thing, the prompts you create are going to be just as influenced by your biases (or those in your employee’s self-reporting) and what you don’t know as a manual analysis. You won’t notice they’re there – it’s called “unconscious bias” for a reason – but even subtle omissions or inclusions, or the smallest blind spot about the real requirements of a current or desired omission, can skew the results.

For another, chatbots aren’t research tools. They’re tools that – if used correctly – can help you think about things you might not have, or present a way of looking at a situation that might not have occurred to you otherwise.

Chatbots are prone to what some experts call “hallucination,” or, “confabulation.” In short, this means that if they don’t know something, they might make it up. 

In a skills gap analysis, this could range from misidentifying real needs (and doing so with confidence), to picking up on your linguistic cues and unduly praising or disparaging the employee, mirroring your own feelings.

A number of AI platforms dedicated to skills gap analysis exist, with focuses from comprehensive analysis to market-driven data to providing training components to augment the analysis. 

From iMocha to JobsPikr to Eightfold AI (to name a few), the list of platforms is long. The human element comes in picking the one that’s right for your company, your workforce, and your needs.

Need help developing your AI skills? Check out ChatGPT and AI Basics for HR Professionals!