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What drives transformation success – and what holds it back?
Find the answers in the exclusive results presentation of our study on the status quo of transformation in 2025.
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2025 was the year in which companies focused on how to integrate AI into their processes in a meaningful, effective, and responsible way. For many organizations, the biggest challenges were not technical, but cultural—questions of mindset, leadership, and collaboration. Looking ahead to 2026, the focus shifts to the next stage. As AI’s influence grows, it is not only processes that are changing, but responsibilities as well and with them, our understanding of the value of work itself. Which tasks will AI take on? What should remain deliberately human? And how should future roles be designed in this new context?
As we enter 2026, AI has become a core part of everyday work. The Work Trend Index 2025 shows that copilots and agent-based systems are increasingly becoming the foundation of how work gets done. The key question is no longer whether AI is used, but how work, roles, and responsibility must be redesigned.
From an organizational perspective, McKinsey reports that 88% of companies already use AI in at least one business area. Yet fewer than one-third consistently apply known best practices for scaling, leaving many AI initiatives fragmented or ineffective. Only a very small share of leaders describe their generative AI rollouts as “mature.” From an employee perspective, the situation is equally challenging. Gallup shows that global employee engagement has declined again, with the sharpest drop among managers. Since roughly 70% of team engagement depends directly on leadership, one thing becomes clear: when leaders are overwhelmed, their teams are too.
At the same time, the Future of Jobs Report 2025 highlights that the biggest obstacle to transformation is no longer tools, but missing capabilities. This leads to the central question for 2026:
How can organizations redefine the value of work, meaningfully evolve roles, and structure human–AI collaboration in a way that actually leads to better decisions?
Across many organizations, it is becoming clear that technology itself is not the bottleneck. The real challenge lies in understanding how work changes when AI becomes part of everyday decision-making. Leadership is therefore shifting away from the question “How do we implement AI?” toward a more fundamental one: “How do we create clarity, meaning, and psychological safety, and design work so humans and systems reinforce each other?”
Productivity and engagement increase where leaders clearly define which tasks AI takes on (such as research or data analysis), which activities remain deliberately human (such as prioritization or risk assessment), and how collaboration in hybrid teams should be structured to support better decisions. Leadership thus becomes a key design force in a world where responsibilities are constantly evolving.
What this means
As AI reshapes tasks and workflows, traditional role descriptions increasingly fail to reflect how work actually happens. Instead of fixed responsibilities, the focus shifts to the capabilities teams need to use AI effectively and achieve better outcomes together. The Future of Jobs Report 2025 shows that by 2030, around 40% of core skills will be redefined. Upskilling therefore becomes one of the most powerful levers for sustaining productivity, motivation, and adaptability in AI-driven environments.
What this means
AI doesn’t only change processes, it reshapes how people process information, make decisions, and carry responsibility. Many teams now face unprecedented volumes of data, options, and speed. Resilience becomes a structural prerequisite for good decisions. Gallup describes today’s global workplace as “at breaking point,” where productivity increasingly fails due to limited mental capacity. AI can reduce pressure but only if organizations consciously manage how much cognitive load teams carry and where AI truly provides relief.
What this means
These three trends show that the real leverage in working with AI does not lie in more technology, but in how work itself is designed. Leadership, mental resilience, and capability-building determine whether AI provides orientation—or adds complexity.
Looking ahead, 2026 will be less about new tools and more about redesigning work. Organizations must rethink roles, clearly allocate responsibility between humans and AI, and create environments where people can make sound decisions even under rapid change. Those who do will close the gap between technological potential and human effectiveness—and use AI as a catalyst for better decisions, rather than an additional source of stress.
In 2026, we are once again conducting our Transformation Status Quo Study to understand how organizations redefine the value of work, shape leadership, and structure effective human–AI collaboration. Participation is free and open to organizations of all sizes.
With five or more participants per organization, you will also receive an individual results presentation highlighting strengths (“tops”) and development areas (“downs”)—providing a solid foundation for next steps.
Take part now and assess your organization’s transformation readiness!
https://www.idc-a.org/insights/0bKr4NJQdK5sYcAQaGZD
https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
https://hbr.org/2025/05/research-gen-ai-makes-people-more-productive-and-less-motivated
https://www.thecrimson.com/article/2023/10/13/jagged-edge-ai-bcg/
https://neontri.com/blog/ai-trends/
https://www.foresightfactory.co/wp-content/uploads/2025/10/Trending-2026-Preview-Report.pdf
https://www.gallup.com/workplace/349484/state-of-the-global-workplace.aspx
https://www.weforum.org/reports/the-future-of-jobs-report-2025/