Transforming Talent Management with AI-Powered Skills Models

For years, organizations have treated skills as a supporting element of talent management. Useful, yes, but rarely strategic. At best, they became a checklist. At worst, a static document that lived in HR and barely influenced real decisions.

At lapzo, we’ve spent a long time trying to answer a simple but difficult question: What is the right way to implement a skills model that actually works across the organization?

The Limits of Generic Skills Libraries

Our first approach was the one most companies take: build a large skills library and allow organizations to adapt it to their reality. In theory, it made sense. In practice, it didn’t.

The result often felt generic. Skills were defined at broad contribution levels — junior, mid, senior — without ever landing at the role level. And that’s where the real problem begins.

Skills are not an isolated HR exercise. They are used to:

• Recruit people

• Evaluate performance

• Identify internal talent

• Design development plans

When skills are not specific to the role, everything downstream becomes generic. Recruitment processes lack precision. Development plans look the same for everyone. Organizations end up hiring “good profiles” instead of building true experts for critical roles.

This doesn’t mean transversal skills aren’t important. They are. But role-specific skills matter more, because they are what truly differentiate performance.

Why Role-Level Skills Models Were So Hard to Build

Historically, building skills models at the role level was extremely complex.

If you wanted to do it well and customize it, the effort was massive. If you relied on a library, the output lacked depth and context. And on top of that, roles themselves were constantly evolving, making static models obsolete almost as soon as they were created.

The trade-off was always the same: depth versus scalability.

AI Changed the Equation

That trade-off no longer exists.

Today, we start from something every organization already has: job descriptions. Using AI, we translate those descriptions into role-specific skills matrices, grounded in the real operational context of each company.

These matrices don’t just list skills. They define observable behaviors tied to actual performance in that role.

Once those matrices exist, a second challenge emerges: How do you assess people accurately?

Traditionally, this meant manual, one-by-one evaluations. Now, using AI, we generate assessments that combine:

• Multiple-choice questions

• Role-based scenarios

• Real-life situations

All evaluated in real time, with context from the role and the skills matrix. The result is a much more precise view of someone’s level of mastery for a specific position.

One Model, Multiple Talent Decisions

This approach unlocks something powerful: a single competency model that works across all talent processes.

It can be used for external recruitment, as a filter to identify true fit.
It can be used internally, to detect high-potential talent already in the organization.
And it becomes the foundation for development.

This is where personalization finally becomes real.

Personalization is not creating the same learning path for everyone with the same title. True personalization means designing a development plan for Jorge, based on:

• His current role

• His specific competency gaps

• His career path inside the organization

For years, personalization was an ambition more than a reality. AI is making it achievable.

Skills as a Transversal Strategic Axis

When done right, skills models stop being an HR artifact and become a strategic backbone. They connect recruitment, performance, mobility, and development into a single system. They give clarity to employees about what excellence looks like in their role. And they allow organizations to move away from generic talent practices toward intentional capability building.

The impact of AI on skills is just beginning, but the direction is clear. For the first time, organizations can build competency models that are transversal, dynamic, and deeply tied to business reality.

The future of talent isn’t generic. It’s specific, contextual, and continuously evolving — and competencies are finally ready to play that role.