AI Offers New Capability in Skills Intelligence

Companies urgently require real-time, granular data to analyze trends in the demand and supply for skills, to identify skills gaps for talent strategies (buy, build, borrow talent), and to explore technology-based talent solutions (through automation or augmentation).

These data are exactly what AI tools can provide. AI-based labor market analytical tools can generate rich, actionable skills insights from labor market and macroeconomics data. AI-based skills planning platforms can combine both structured and unstructured internal workforce data to reveal both the supply and demand for skills internally. The combination of external and internal data, powered by AI, constitutes groundbreaking new capability in skills intelligence. 

AI-based tools and platforms can employ a variety of skills analysis approaches. These include:

• Skills adjacencies This approach provides insight into the changing relationships between different skills sets. A map of “stepping stone” skills (that act as bridges between different skill domains) then guides recruitment decisions about which skills to look for, skills development strategies, and learning content.
• Skills proximity assessments For sunset and sunrise skills. This analysis helps identify any transferable skills that could enable workers to transition from declining roles to in-demand roles.
• Skills inference This approach extracts evidence about employee skills from text using natural language processing (NLP). Described as unlocking an employee’s “digital footprint,” skills inference analyzes structured and unstructured data. These data include sales data, project summaries, performance evaluations, work history, and learning records.

The new opportunities AI offers will enable business to evolve strategic workforce planning to the next level, becoming more integral to skills, talent strategies, and enterprise-wise capability building. The emphasis shifts from job-based planning toward skills forecasting and the generation of skills data to guide talent and skills development strategies. The unit of the workforce plan becomes skills—not jobs, head count, and working hours. The priority switches from planning cycles linked to annual budgets to predicting skills on a continuous basis.

However, it will be essential to bring the C-suite on board if companies are to make the significant investment required to adopt AI technology for enhanced skills intelligence. According to our global 2023 C-Suite Outlook, CEOs do not place a high priority on investing in improving skills in HR data analytics or implementing AI/generative AI in optimizing human capital management efficiencies. CHROs will need to make a convincing case for the technology’s value and potential ROI. But at such an early stage in the evolution of AI-based skills platforms, wading through the often-optimistic claims of vendors and finding the case examples won’t be easy.

For more on the topic of skills, see our three-part series on Transitioning to a Skills-Based Organization: First Steps.