What to Know About the Future of HR and AI in 2026

Emily Gerson

mercredi 4 février 2026

Partager

HR is at an inflection point. AI isn’t just automating tasks; it’s reshaping how careers are built, how work is done, and how people learn. As a result, HR teams are being asked to move into strategic workforce leadership, and they often have to do so with fewer resources than before.

In a discussion about “The AI-Powered HR Team of the Future,” Ali Bebo, Chief HR Officer at Pearson, and Susie Lee, Chief Learning Officer in Residence at Degreed, addressed what that shift really means, and what HR leaders should do next. Here are the top takeaways:

1. Career ladders are breaking. Career systems are replacing them.

For decades, most organizations relied on a simple idea of linear career progression: climb the corporate ladder. Junior to senior. Individual contributor to manager. Up and to the right. 

That model no longer works for today’s non-linear career paths. 

Roles are changing too quickly. Skills expire faster. And pushing everyone into management roles just so they can “advance” creates disengagement on both sides. 

Today’s workplace is getting messier for employees and managers alike, especially with the outdated “career ladder” model still considered the norm in many employees’ minds. Bebo mentioned that as career progression gets more complicated, more and more employees are getting trapped in transition points, unsure where to go or how to improve. Meanwhile, HR is trying to answer questions like: “How do we successfully bring people in from school into work? How do we successfully move people up through different career paths that are in engineering or in operations or manufacturing?”

This will continue to be a growing challenge for HR. That’s why businesses—and HR teams in particular—need to reimagine this career progression structure and take ownership of this shift. The alternative, as Bebo said, is more of a flowing, integrated system: “It’s much more about creating career systems so people can have a bit more of a GPS system inside of career architecture or career framework to really figure out what it would take to move from one role to the next to be able to be prepared to go from one role to the next.”

But even within a system, there are still transition points where people need to move from one phase to another. For this, Bebo’s answer is hyper-personalization. It’s a dynamic talent system that responds to skills, background, and goals of the employee. 

What’s the difference between a system and a ladder? This kind of adaptable career system:

• Breaks roles into tasks, skills, and workflows, not static job descriptions
• Enables lateral, diagonal, and project-based movement, not just promotions
• Supports dual career paths, so employees can grow as experts or leaders
• Acts like a GPS for talent, helping people navigate what’s next, not just what’s up

In cooperative, tailored systems like this, employees don’t get stuck at transition points, unable to change or advance in their role. And organizations gain more flexibility to redeploy talent more fluidly as priorities change.

2. HR needs to shift to a product mindset to lead AI transformation.

HR management can no longer operate as a service function. It has to think and act like a product organization. For years, HR and L&D teams have been structured around programs, policies, and processes. Work was delivered in cycles: design, roll out, measure, then start again with something new. That model assumes relative stability in roles, skills, and business needs over a certain period of time.

The rate of change in the AI era breaks that assumption. 

By adopting a product mindset, HR professionals can reframe and reimagine how they deliver learning and talent development. In a product-oriented HR model:

• Employees are treated as users, not recipients, of programs.
• Careers, learning, and talent experiences are designed as living systems, not one-time interventions.
• Success is measured by adoption, outcomes, and continuous improvement.
• HR works in tight partnership with technology, data, and business teams, iterating based on real usage and feedback. (Bebo even playfully described the HR and IT organizational partnership as “the new power couple.”)

When AI is constantly reshaping workflows and bringing new skills to the forefront, HR can’t afford long planning cycles or overindexing on content. The half-life of skills is shrinking dramatically, especially for AI skills. HR teams need to ship, test, learn, and adapt, just like product teams do.

“We almost need to shorten our development timeframe to the agile way of working, so that it’s quarterly releases that are just continuing to add more value to what we offer,” Bebo suggested.

Because of the speed needed, this mindset is especially critical as organizations move toward dynamic career systems and AI-enabled development. HR solutions and systems have to evolve continuously based on skill demand, employee behavior, and business priorities.

Without a product mindset, HR risks spending too much time creating the “perfect” development opportunities, skill strategies, and architectures, only for them to be outdated upon release or shortly thereafter. A product release framework creates a more agile operating system, making talent and skill development programs available faster and ensuring constant iteration to improve as information changes.

3. Learning is now the most valuable skill.

With an estimated 65% of job skills expected to change by 2030, no organization can pre-train its way out of disruption. The only sustainable advantage in the coming years will be learning agility. That’s why “learning to learn,” as Pearson puts it, has emerged as a business-critical capability. 

Learning has become the power skill that stands the test of time. If your employees can learn quickly, they can keep pace with transformation. And if they can transform at pace, your business is adaptable and set up to meet whatever comes next.

AI accelerates this lean into learning by providing hyper-personalized content, and even guidance, in the flow of work. But the human capabilities of  adaptability, reflection, and application remain essential. It’s people who have to learn.

HR and L&D can make learning more effective by helping people focus on the skills that ladder up to broad, essential capabilities for organizational innovation and growth. For example, at Pearson, one area of interest is innovation, and Bebo points out that there are many “subskills” that feed into that—skills like creativity, client expertise, problem diagnostics, and problem solving. 

Once specific skills are homed in on, leveraging key learning science findings can help make upskilling even more effective at an individual level. 

The organizations that win won’t be the ones with the most courses or the best AI tools. They’ll be the ones that help people build capability at speed in key areas. They’ll be the ones with employees who learn most effectively and have the clearest guidance about what it’s important to learn next.

What this means for leaders and the future of HR

Career ladders are giving way to career systems. Jobs are being unbundled into skills and tasks. AI is becoming a daily collaborator. And learning agility is the currency of the future. These changes are practical and urgent. 

To be proactive, HR leaders should be asking:

1. Where are our career structures too rigid for today’s work?
2. Which tasks (not roles) are most ready for AI augmentation?
3. Do our learning strategies build adaptability, or just credentials?
4. How are we measuring success: efficiency alone or workforce readiness?

The human transformation that’s essential for success starts with Human Resources. Empower your HR team to take that lead. Watch the full “The AI-Powered HR Team of the Future” webinar to learn more about what comes next.