How AI Is Reshaping Talent, Teams, and Leadership -- and What Employers Must Do Next

February 13, 2026

Published in:

Innovation & Technology

A male and female entrepreneur stand together in an outdoor garden. — Robert van der Zwart and Brigitta Lops of EO Netherlands. Photo courtesy Maxime Beerkens.

Contributed by Brigitta Lops, an EO Netherlands member and owner of Jobtraining, and Robert van der Zwart., an EO Netherlands member, who is a coach, keynote speaker, founder of AIPO Network., and a host and organizer of the virtual EO Global AI Summit #4: Transforming to an AI-First Company which will take place on 26 February 2026 (EO members register free).

Artificial intelligence (AI) is no longer speculative—it is reshaping entry-level employment and redefining which skills matter. Organizations that see AI only as a tool risk missing a strategic chance: The shift is not just about boosting productivity, but about redefining which skills are important, how teams are organized, and how leadership prepares workforces for the future.

For employers, this is critically important. AI will both eliminate and reshape job roles, change the skill sets organizations need, and transform how talent views their career paths. If organizations don’t take a strategic approach instead of a reactive one, they risk skill shortages, disengaged employees, loss of their competitive edge, and damage to their employer brand. Conversely, companies that actively redesign work, reskill employees, and integrate human-AI collaboration into their foundation will promote growth, attract top talent, and build resilience.

The Labor Market: Who is Affected and How

Research from the Stanford Digital Economy Lab shows AI’s impact on the labor market. Their study, Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence, found that workers aged 22–25 in jobs most exposed to generative AI experienced a 13% relative decline in employment compared to less-exposed workers. Other studies confirm that early-career employment in fields like software development, customer service, and other AI-exposed areas is already shrinking.

Importantly, this trend is driven more by job losses than wage cuts—meaning people are not just earning less; they are losing jobs altogether.

This highlights a crucial point for employers: The future isn’t just about creating new jobs; it’s about preventing, reducing, and reshaping job displacements—especially among early-career talent.

Why Many AI Initiatives Fail (And What it Means)

Many organizations see AI as just an upgrade to tools instead of a true strategic transformation. They use AI to improve emails, automate small tasks, or streamline routine processes, but they don’t ask the bigger question: Which core business problem should AI address?

The main governance issues blocking AI adoption include:

Organizational silos
Leadership treating AI as IT
Legacy systems
Poor data foundations

These barriers produce experiments that deliver short-term gains but fail to transform the business.

The key takeaway for employers: Shift from “playing with tools” to purposeful innovation, where leadership defines the mission, aligns AI with business goals, and enables execution.

The Solution: Strategic Leadership and Problem-Driven Experimentation

To stay competitive, organizations should adopt a leadership-first, problem-driven approach to AI. Key steps include:

Leadership roles as “conductors”: Senior executives don’t need to create detailed models but must define, supervise, and allocate resources for the strategic direction of AI.
Small-scale experimental teams: Move beyond mere pilots and develop cross-functional teams focused on real problems.
Safe spaces for learning: Create environments where staff can experiment with AI without fear—where failure is acceptable, data remains protected, and promising experiments can expand.
Clear scaling process: Define how successful prototypes transition into full implementation.

How can AI provide strategic advantages when aligned with key business challenges? Examples include a global beverage company using autonomous agents to negotiate supplier contracts and an airline deploying predictive sensor AI to detect turbine issues earlier.

The Human Side: HR’s New Role

AI will automate many tasks, especially entry-level roles. Some professional services firms are hiring fewer junior consultants because AI tools now handle research and summaries. HR must prepare for this shift, not just manage it. HR’s evolving role includes:

Future-proofing employees by developing human skills like critical thinking, storytelling, and authenticity.
Facilitating internal mobility by using AI as a coaching tool.
Rethinking career growth away from narrow ladders toward broader, more fulfilling paths.
Automation of human interactions (such as AI-driven hiring and onboarding) introduces risks: top talent may feel disconnected. Human connection, mentorship, and trust are more important than ever.

Building an AI Growth Culture

From an HR and Learning & Development (L&D) perspective, the challenge of AI adoption is not primarily technical—it is behavioral. Many organizations still treat AI as a set of tools to be rolled out. But lasting impact requires creating a learning culture that rewards curiosity, experimentation, and reflection.

Leaders play a decisive role here. Across industries, leaders are discovering that their task is shifting from being the expert to orchestrating learning. The most successful AI-driven transformations are led by leaders who create clarity and psychological safety for people to experiment, fail, and learn in real time.

In this new landscape, L&D becomes a strategic partner rather than a support function. Its mission is to create expertise that helps employees:

Learn to learn with AI: Develop digital curiosity and critical reflection rather than passive tool use.
Translate knowledge into behavior: Use real-world experimentation (“learn by doing”) as the engine of change.
Strengthen essential human skills: Empathy, creativity, and authenticity become differentiators when tasks are automated.

AI does not replace learning; it enhances it. Adaptive tools, avatars, and AI coaches can customize development, but the core of growth remains human. Research shows that we need the process, the struggle, and the messiness of real-life interaction to truly develop new behaviors and apply them. Additionally, we learn deeply through connection: the dialogue with others, feedback from peers, and the shared courage it takes to unlearn and start anew.

In a series of interviews with L&D experts from different organizations, a shared observation emerged: AI adoption unfolds differently from traditional change curves. Teams move at uneven speeds, going back and forth between enthusiasm, resistance, and fatigue (Fear, Fans, FOMO, Frustration). L&D can act as a stabilizer and sense-maker, helping people remain grounded in this acceleration.

From Compliance to Curiosity

Where early AI programs focused on AI usage, literacy, and compliance, forward-thinking companies now focus on “AI growth culture,” an atmosphere in which employees are encouraged to ask:

What can AI help me learn and improve? And what should I never outsource?

This question reframes AI from a threat into a learning partner—supporting both performance and purpose.

When organizations combine strategic leadership with behavioral learning design, AI adoption becomes more than a technology project; it becomes a human transformation journey.

Why Employers Must Not Wait

AI isn’t just about doing things faster—it’s about doing new things differently. Companies that adopt AI strategically will redeploy staff into higher-value tasks, attract and keep top talent, avoid skill shortages, and strengthen their employer brand. Doing nothing risks losing your workforce, your culture, and your competitive edge all at once.

6 Actionable Strategies for Leaders

Launch an AI Leadership Bootcamp for senior managers.
Create a Problem-Driven AI Sandbox for experimentation.
Organize Growth with AI training for employees; to learn with AI, not just use it.
Redesign entry-level roles for human-AI collaboration.
Run a track alongside the technical AI rollout to strengthen human differentiators.
Build a Workforce Mobility Hub using AI for internal transitions.
Integrate authentic human connection into every AI-enabled process.

AI adoption fails when it’s tool-driven rather than strategy-driven. The future of work depends on leaders who can steer AI implementation with vision, experimentation, and empathy. Organizations that humanize AI—by promoting authenticity, creativity, and adaptability—will not only survive automation but lead it.