Samenvatting
The research Rise of the Superworker argues that AI transformation should focus on people, not just technology. Instead of fearing job losses, organizations can empower employees to become Superworkers—workers who use AI to automate tasks, gain insights faster, and free time for creativity. This requires a cultural shift: seeing AI as a multiplier of human potential, not just a cost-cutter.
HR plays a central role by redesigning work, enabling continuous reskilling, and fostering psychological safety so employees can experiment and adapt. Skills are shifting from technical prompt engineering toward broader AI literacy, critical thinking, and adaptability. Successful organizations embrace dynamic change, cross-functional HR, and systemic integration of AI. Companies like Mastercard, LEGO, and TomTom show how balancing AI tools with people-focused strategies creates resilience, innovation, and stronger business outcomes.
In a world where AI is rapidly reshaping industries, the focus of transformation is shifting from technology itself to the people who use it. The Rise of the Superworker, groundbreaking research by The Josh Bersin Company, explores how organizations must rethink work, workforce strategy, and the role of HR in the age of intelligent systems. We sat down with Kathi Enderes, SVP of Research and the lead analyst behind the Superworker report, to discuss the key findings from the study.
A lot of discussion about AI is focused on fears about job losses. How does the idea of the Superworker fit in?
Kathi Endreres: ‘The conversation around AI is often either very technical or very fear-driven. Understandably so – there have been layoffs and hiring freezes in some sectors, which make people anxious. But there’s another side. AI has immense potential to enhance how we work. One way we see that happening is through the rise of what we call the “Superworker.”
This isn’t just about tech-savvy professionals or C-level roles. Any employee – whether on the factory floor, in customer service, or behind a laptop – can become a Superworker by using AI to automate repetitive tasks, generate insights faster, and free up time for creativity and innovation. These Superworkers aren’t afraid of AI; they harness it to dramatically boost productivity and creativity.’
How does the Superworker mindset shift the way organizations view AI?
‘Organizations that embrace the Superworker mindset see AI as a multiplier of human potential – not just a way to cut costs. That’s a huge cultural shift. Too often, companies replace people, innovation declines, service levels drop, and they cut even more. But Superworker organizations invest in human-AI collaboration. That leads to new products, better customer experiences, and stronger business outcomes. It’s a mindset that requires bold leadership, continuous learning, and an openness to experimentation. HR is critical in fostering that mindset.’
How do organizations support the shift toward creating Superworkers?
‘Ultimately, the goal is to help employees not just survive the AI transformation, but thrive in it. Supporting this shift is complex, because AI is constantly evolving – and so are the skills needed to work effectively with it. Organizations must empower employees to experiment with AI, even if that means making mistakes. This requires psychological safety.
A key concept here is what we call skills velocity – the ability to rapidly learn and apply new capabilities. HR plays a central role, not just by providing training, but by redesigning jobs and workflows based on AI’s actual impact on work. This isn’t about cutting jobs, but about redesigning them so people focus on what machines can’t do: creative problem-solving, building relationships, and giving meaning to work. We call this productivity-based work design: moving beyond static job descriptions to truly understanding the specific tasks employees perform – and how AI can automate, support, or leave those tasks untouched. Because AI changes so quickly, this analysis must be ongoing. HR must also lead in what we call dynamic skilling – a continuous cycle of reskilling and upskilling, aligned with the new tasks people take on as AI reshapes their roles.’
You mentioned how rapidly the skills required to use AI are shifting. Which skills are gaining importance, and which might be losing relevance?
‘If we look back two or three years, one of the hot topics was prompt engineering – that is, learning how to write very specific, often complex prompts to get useful output from generative AI tools. That skill was critical early on because the tools were less intuitive and required a deep understanding of how to phrase requests. But the fascinating thing is that this skill is already becoming less important. AI tools are evolving to be smarter and more conversational. They no longer rely on users crafting perfect prompts; instead, they actively ask follow-up questions to clarify what the user really needs before delivering an answer.
What this means is the skill is shifting from “how do I engineer prompts?” to a broad spectrum of AI literacy – from understanding functional AI tools to tuning AI for specific business problems, to interpreting AI outputs critically. This is not just technical; it’s about cultivating an agile mindset where employees continually reskill and upskill to keep pace with evolving AI capabilities.’
How do these changes impact HR itself?
‘One big change is that HR must focus on fostering change agility. And I say that deliberately instead of the traditional change management. The old model treated change as a project – implementing an ERP system, training people, then moving on to “business as usual.” That model doesn’t work anymore because AI is not a one-time change. It changes daily, sometimes hourly, with new capabilities emerging constantly. So organizations can no longer afford to have a “big bang” change approach. Instead, they need to embed change as a continuous, small-step process. Employees need to feel comfortable adopting new tools, making mistakes in safe environments, learning fast, and adapting their work on the fly. This requires a culture of experimentation and learning agility supported by HR.
Another big shift HR must lead is in systemic HR. AI acts as a catalyst that demands we rethink how organizations are structured and how work flows across departments. It brings new opportunities to connect insights across functions like sales, marketing, and operations in real time, enabling more agile and responsive organizations.
Equally, AI use cases don’t fit neatly into traditional HR silos – learning and development, talent acquisition, compensation, and so forth. For example, reskilling is not just about training; it touches hiring, internal mobility, rewards, recognition, and how work is fundamentally redesigned. Many organizations are breaking down these silos to create a more integrated, cross-functional HR operating model. This approach enables a more holistic and strategic use of AI in managing the workforce and work itself.’
It sounds like there’s a strong psychological and cultural dimension to this transformation as well.
‘Absolutely, and it’s critical to recognize. AI impacts not only how people work but also their broader sense of security and identity, both professionally and personally. Massive technological shifts often create fear and resistance, which is natural. But interestingly, individuals tend to be far more adaptable to change than organizations or legislation.
Take the pandemic as a perfect example: overnight, millions of people had to radically change how they live and work—embracing masks, remote work, and virtual communication. Despite the fear and uncertainty, people adapted remarkably well. Organizations and laws took much longer to catch up.
People are wired to adapt quickly, especially when they feel supported. That’s the key. Organizations must provide that support, encouraging experimentation and learning, and creating clear boundaries so employees know when and how they can take risks safely. For example, experimenting with AI in patient note-taking in healthcare is feasible and encouraged, but experimenting on life-critical decisions is not.
When organizations fail to provide this support, it feeds fear and resistance. But when they foster trust and agility, employees tap into their innate ability to adapt and innovate.’
What distinguishes organizations that are on their way to becoming ‘Superworker’ organizations from those lagging behind?
‘The organizations that are well on their way, are those we call dynamic organizations. They embrace continuous change as part of their DNA and see innovation not as the responsibility of a single team but as everyone’s job. This means empowering every employee to innovate in their work, processes, and customer engagement.
They also support workforce mobility, focusing on skills rather than rigid job roles. These organizations break work into smaller, manageable pieces and redesign tasks to leverage AI’s strengths alongside human creativity. Critically, they view AI as a growth enabler – not merely a cost-saving tool.
A great example is Mastercard. They have a robust AI strategy that integrates AI governance with a strong focus on people and talent as the core enablers. They carefully balance buying off-the-shelf AI tools for common HR functions – like talent mobility platforms – with building custom AI solutions for unique business needs, such as their sales compensation model. This thoughtful approach ensures they harness AI effectively without reinventing the wheel unnecessarily. Mastercard also embraces systemic HR – breaking down traditional silos between centers of excellence and redefining HR roles to be more flexible and technology-enabled.
Another inspiring example comes from Europe. The LEGO Group is actively rethinking organizational design and leadership models to integrate AI effectively. Similarly, TomTom is moving away from traditional HR centers of excellence to a more integrated, systemic HR operating model that aligns tightly with AI transformation.’
