Reinvent for a human advantage: Why work redesign matters more than AI adoption 

Many organizations are still trying to fit AI technologies into legacy work models built for a different era — fixed jobs, rigid structures, and processes designed for stability rather than reinvention. This approach may create pockets of efficiency, but it will not unlock the full value of AI use in the workplace.

Intentional work redesign is what closes that gap. It starts not with software development or the information technology stack, but with the work itself. That means examining what work needs to be done, which tasks are best handled by people, which by machines, and which through human–machine collaboration. Mercer’s GTT Trend 1 report is clear: long-term AI success depends on a work-backward, not tech-forward, approach.

This is the shift away from layering AI systems onto outdated work models and toward redesigning work so machine capability improves human judgment, creativity, and adaptability. A small number of pilots may show promise, but scaling impact requires redesign across specific areas of the business function. Managers — not just engineers — must be part of the plan so new ideas can be operationalized and customers can see the benefit. Human advantage doesn't emerge by accident. It must be intentionally designed.

The design challenge is not only operational. It is cultural.

Mercer’s research shows AI inequity is emerging as a new fault line in the employee experience. More than a third of employees say they would consider leaving if they felt disadvantaged by unequal access to AI tools or training. Meanwhile, 56% say unequal access negatively affects morale. Yet only 19% of HR leaders say they consider the emotional and psychological impact of adopting AI as part of digital implementation.

A workforce that does not trust the transformation will not sustain it. If organizations want people to engage with AI to improve performance, they must build a culture of AI enablement grounded in transparency, equity, and support. This means:

• Communicating clearly about what is changing
• Involving employees in work redesign
• Ensuring fair access to training programs and tools
• Giving people confidence that they can continue to grow as work evolves
• Upskilling in AI capabilities, content creation workflows, and collaboration with technical specialists

Without these foundations, anxiety about using AI can harden into resistance — slowing adoption and weakening performance. Leaders should also address data privacy, data security, and governance concerns early. These remain critical drivers of employee and customer trust.

One of the clearest findings in the research is the growing misalignment between what the C-suite sees as critical to performance and what many HR functions are prioritizing. While 63% of C-suite leaders and 67% of investors see redesigning work around AI and automation as a top ROI driver, fewer than half of HR leaders are prioritizing it in 2026.

This is why this is not simply an AI story. It’s a work, skills, and leadership story. 

As work redesign becomes central to enterprise performance, HR cannot focus only on optimizing parts of the system while the entire system is being reinvented. Instead, HR has the opportunity to become the architect of the work system itself — shaping how work, skills, roles, and rewards evolve together in the AI-driven future of work. 

In this model, work architecture assumes continuous learning, intelligent systems, and seamless human–machine collaboration. The shift required is fundamental: from service delivery to outcome delivery. Organizations must start with the future — deciding which outcomes truly matter — and then assembling the right combination of humans, machines, and intelligent workflows to bring those outcomes to life.

Across industries, from public services to financial services to marketing functions, the leaders who treat redesign as the primary driver of value will be the ones who win. That means business leaders working closely with technical specialists, HR teams, and customers to identify where AI technologies can augment people, where to invest in training programs, and where to protect privacy and data security. This coordinated approach is how organizations turn new ideas into real advantage — and ensure AI serves people, not the other way around.

Work redesign cannot be a one-time exercise. As AI continues to reshape tasks and workflows, organizations need a dynamic view of capability, including:

• Where skills are changing
• Where gaps are widening
• Where talent can be redeployed fastest and most effectively

Skills intelligence is what makes reinvention repeatable. Dynamic skills intelligence is a foundational pillar of AI-centered reinvention. The case is compelling: 97% of investors say their investment would be negatively affected by a less progressive approach to agile and skills-based models. Yet only 36% of HR leaders say they have a clear understanding of talent development needs across their organization. Without better insight into future-fit skills, organizations will struggle.

Achieving a human advantage through reinvention calls for leaders to redesign work deliberately — not simply digitize legacy roles and processes.

This moment presents HR with a unique opportunity to take a central role in enterprise transformation. HR can help define how work skills, roles, and reward strategies must evolve in an AI-driven future.

As organizations enter their next phase of transformation, the question is whether leaders will approach work redesign with the intentionality needed to turn disruption into stronger, more sustainable performance.

Mercer’s Global Talent Trends — Reinvent for a Human Advantage report explores how organizations are making this shift, where the biggest opportunities lie, and why enabling AI adoption and building future-fit skills will matter most — alongside the evolving role of HR as the architect of work shaping the change.