Turning Data Into Action: How AI Unlocks The Power Of Skills
For many organizations, the idea of transforming workforce planning around skills sounds great in theory – but quickly runs into a familiar problem: the data. How do you take thousands of job descriptions, CVs, and learning records (most of them messy, outdated, or unstructured) and turn them into something useful?
Enter AI.
Today’s AI models are quietly solving one of the hardest challenges in workforce transformation: the cold start. While your team wrestles with the complexity of organizing and updating skills data, AI is already at work behind the scenes, bringing order to chaos.
From Data Mess to Skills Intelligence
AI can take unstructured data and turn it into something powerful. By scanning sources like job descriptions, CVs, performance data, and even learning records, it infers, normalizes, and structures skills data automatically – laying the foundation for smarter workforce planning.
But AI doesn’t stop at cleaning up your data. Once systems are integrated and a common skills language is in place, it begins to surface insights that would otherwise stay hidden: identifying emerging skill gaps, flagging opportunities for workforce upskilling, and spotting patterns in employee development that humans might miss.
Smarter Profiles, Better Planning 📊
One of AI’s most powerful applications is in enriching employee profiles. Even with just a small amount of input – a job title, a LinkedIn profile, or some internal records – the system can infer likely skills, identify adjacent skills (those someone is most likely to learn next), and suggest updates.
This sets off a powerful flywheel effect:
- Initial data gives AI a starting point – past roles, projects, or training records.
- AI infers skills that are likely but unlisted, based on patterns it’s seen elsewhere.
- Employees engage with those recommendations, expanding their profiles.
- New inputs improve the model, enabling even better insights over time.
With every iteration, the system becomes more accurate. Profiles become richer. Skills gaps become clearer. And your ability to plan, develop, and move talent improves.
Embedding Ethics & Explainability 💖
Of course, AI doesn’t just need data – it needs trust. As AI becomes embedded across talent processes, organizations need to ensure that the systems they use are explainable, ethical, and auditable.
The best AI tools can show their reasoning, giving HR (and employees) confidence in every recommendation. And they’re designed not to replace human judgment, but to support it – surfacing insights that humans alone might miss, and freeing up time for more strategic decision-making.
Integration Is Everything 🖇️
AI works best when it’s built in, not bolted on. That means letting it work seamlessly across your HR tech stack – from your HCM to your LMS to your recruiting tools. When AI can pull all the right data together, you are in a position to feed it back into your single source of truth (most likely your HCM) and enhance its capabilities hugely.
As Mercer puts it: “When thoughtfully integrated, AI doesn’t just complement your tech stack – it transforms it into a smarter, more agile ecosystem.”
AI thrives on high-quality, connected data. When applied across your systems, it doesn’t just make your data more useful – it makes your entire workforce strategy more intelligent, more adaptive, and more future-ready.