As technology continues to advance and companies look to remain competitive in meeting market demand, the skills that employees will need are also evolving. A growing number of companies are exploring how to address these skills and workforce gaps with artificial intelligence.
HR can use AI to reveal “patterns and gaps” and benchmark “current workforce skills against evolving business needs or industry trends,” said Lauren Winans, CEO and principal human resources consultant at Next Level Benefits.
What AI offers in this realm isn’t exactly new, said Will Howard, practice lead of HR trends and AI at McLean & Company. HR teams have long collected and analyzed workforce data manually, he said, but AI can make the process more “feasible and efficient” through automation.
Here, HR experts share four factors to consider when using AI to identify workforce and skills gaps:
1. Organize your data
Organizations have troves of HR data, such as job advertisements, performance reviews, and employee job histories and training, that can be mined to uncover skills gaps, said Sanmay Das, associate director of AI for Social Impact at Virginia Tech. But this data often lacks “quality and completeness,” Winans said.
Before adopting AI, organizations must embrace “good data hygiene” by ensuring the data they plan to analyze is accurate, current, and consistent, said George Denlinger, operational president of US technology talent solutions at Robert Half.
Otherwise, AI insights will be limited or inaccurate. “The phrase ‘garbage in, garbage out’ rings especially true here,” Howard said.
Companies need a clear and consistent process for collecting, maintaining, and updating workforce data, Howard said. For instance, standardize job descriptions, including specific skills, knowledge, and activities, so that AI can make accurate comparisons.
2. Analyze the insights
Large language models, like ChatGPT and Microsoft Copilot, can summarize and report on data, Das said. But, for a deeper analysis, companies often need specialized AI tools designed for HR, including workforce planning and analytics, Howard said. Workday and Disco are some examples.
Ultimately, AI tools can leverage your existing data and identify strengths and weaknesses in your workforce, Denlinger said.
For example, with data on employee performance for a specific project and sales forecasts, AI could suggest the skills or roles necessary to meet the organization’s future demands, Howard said. Examining an employee’s job and training history, AI could quantify their capacity to acquire new skills via upskilling or reskilling, Winans said.
IBM, for example, uses an AI system that analyzes its employees’ digital footprints within the company to identify their skills and predict skill proficiency levels. The company then uses that analysis to offer employees personalized educational opportunities and career coaches, helping them identify job opportunities and new career paths. In 2024, IBM reported that the approach had boosted employee engagement by 20%.
3. Understand AI’s limitations
While AI can analyze data, it may overlook nuances and the human aspects of what makes a role successful, such as small tasks not listed in a job description, soft skills, or the behind-the-scenes efforts employees put in, Das said.
Companies should also focus on data privacy, trust, and employee buy-in, Winans said. Employees may worry about how their data is being used and how it could impact them, such as changes to their roles or responsibilities. She suggested communicating transparently about what data will be used, how it will be used, and why.
Data literacy is another challenge: HR teams must know what to do with the AI results, Howard said. “Even the most advanced AI technology still requires a human to put the results into a business context and communicate and take action on the insights within the organization.”
For instance, the AI analysis on skills gaps should inform decisions about new roles the company needs to create or the training necessary for existing employees, Winans said.
4. Refine your strategy
“Skill requirements evolve rapidly,” Winans said. Using AI to uncover skills gaps should be a “continuous process, not a one-time audit,” she added.
While AI can be useful for tracking ongoing skills gaps, Denlinger said this is still an emerging use of the technology that will likely evolve.
Al also isn’t a “silver bullet that can take you from zero to best in class,” Howard said. “Organizations shouldn’t view AI as a shortcut. It still requires the foundational skills and structures that have always been there,” such as clean data and employees confident in using the technology.
Then, he said, AI “becomes the cherry on top that can take your workforce planning and data analysis to the next level.”
Read the full article here
