Picture this: In an effort to boost internal mobility and align roles with business goals, HR invests in better data and builds detailed skills inventories. Confidence runs high—HR finally feels they understand workforce capabilities and are energized about driving real transformation.

Then… nothing happens.

The initiative stalls. Employees still don’t know which skills to build. The organization feels stuck, unsure of how to move forward.

That’s the classic “cold start” to a skills-based talent strategy—big plans, no spark.

In other words, simply knowing which skills employees have isn’t enough—true impact requires skills visibility.

Skills visibility means seeing not only what skills people possess, but also understanding how those skills are applied, where gaps exist, and what hidden or untapped abilities and potential may lie beneath.

That’s where AI-powered skills inference changes the game. Rather than just counting skills, AI interprets them, connecting the dots between roles, experiences, and capabilities to reveal practical, actionable insights.

By pairing robust skills data with powerful AI inference, HR teams can finally turn the key, ignite stalled talent initiatives, and accelerate meaningful business outcomes.

The Skills Gap Isn’t a Gap—It’s a Visibility Problem

According to Mercer’s 2024/2025 Skills Snapshot Survey Report, employers today know more about their workforce than ever. Seventy percent have identified critical skills within their departments, and nearly half have built a skills library and mapped skills to jobs. More organizations are also embedding skills into key talent practices like learning, career pathing, and succession planning.

And yet, Mercer’s 2024 Global Talent Trends Study shows that half of HR leaders still see skills shortages as a top threat to their business.

It’s striking: even after identifying critical skills, many organizations still believe they’re facing a talent shortage. But in reality, they likely have the skills—they just can’t see them.

The real issue? A lack of visibility. More specifically: AI-powered skills visibility—which is gained through AI inference.

Here’s the thing: Skills are dynamic. They evolve quickly, and their relevance shifts across roles, teams, and business contexts. That’s why having static skills data alone isn’t enough.

Enter AI inference, the process of using trained AI models to make smart, real-time predictions about what skills people have—even when those skills aren’t explicitly stated. By analyzing signals like work history, projects, performance feedback, and more, AI inference uncovers hidden strengths, emerging capabilities, and transferable skills across the workforce.

In other words, AI-powered skills visibility is more than just capturing skills, but to understand and predict them—turning raw data into actionable insights that drive smarter talent decisions.

Why AI Inference Delivers a Warm Start—With the Right Data

With more organizations moving toward skills-based talent strategies, there’s a growing need to identify skills at the individual employee level, according to Mercer’s 2024/2025 Skills Snapshot Survey. Nearly half of companies say they rely on employees to self-report their skills—a slight increase from 44% in 2023. Even more—68%—expect managers to identify employee skills, up from 65% in 2023

To encourage self-reporting, companies are trying different strategies, like using internal talent marketplaces or gamification to motivate employees to share their skills.

But here’s the catch: relying primarily on employees to self-report their skills can stall a company’s skills strategy. Even with the right incentives in place, employees may not engage—or may report outdated or incomplete information.

Censia was built with this challenge in mind.

We use AI inference to help organizations get the accurate, up-to-date skills data they need—without relying on manual self-reporting.

Censia’s AI inference analyzes skill indicators—such as work history, performance feedback, career progression, and market signals—to automatically uncover employee skills that are uniquely tied to each individual.

For example, sales managers in different industries may list the same skills, and traditional talent systems might treat those skills as interchangeable. But by analyzing indicators like career trajectory and sales cycle complexity, AI inference can identify hidden skills and capabilities within those nuances—exactly what organizations need to power a truly effective skills-based strategy.

That’s how Censia helped a Fortune 50 company go from just 5% of its workforce having a completed skills profile to 100% completion. 

And not just quantity, but quality: 80% of the inferred skills were validated as accurate.

With Censia’s powerful AI inference and high-quality dataset, organizations don’t just collect skills data—they gain the visibility and confidence to design and execute a truly effective, future-ready talent strategy.

Think of it this way: AI inference gives you a warm start, but quality dataset ensures the car is pointed in the right direction.

How HR Can Use AI to Finally Deliver on the Promise of Skills-Based Strategy

HR leaders have long recognized the need to move toward a skills-based talent strategy—but for years, they’ve lacked the tools to make that transition meaningful at scale. Most organizations begin by collecting skills data through employee self-reporting. But because skills are dynamic and ever-evolving, capturing them in isolation paints only part of the picture. Without context and continuous updates, self-reported skills data simply isn’t enough to power a true skills-based strategy.

But by layering AI inference on top of traditional data collection, organizations can enrich their skills dataset and understanding of workforce capabilities. 

That’s how skills become truly visible, solving the “cold start” problem that stalls so many talent strategies. 

With AI-powered skills intelligence, HR not only gains a clearer view of talent—they gain a strategic advantage in how the skills in the . It’s how HR earns its seat at the table to lead the charge in fixing the cold start and designing a truly AI-powered, skills-based organization.