The third edition of the report draws on insights from 500 Chief Technology Officers and forms part of the Adecco Group's broader "Business Leaders 2026" research, titled "The Human Premium: Leadership Beyond the Algorithm," which surveyed 2,000 C-suite executives. The findings show that organizations are no longer constrained by access to technology, but by the challenge of integrating AI across enterprise systems, workflows and decision-making processes.
The report identifies agentic AI as the most influential technology trend shaping organizations in 2026. Around 40 percent of Chief Technology Officers described systems capable of planning, decision-making and task execution as the leading drivers of impact. This shift marks a transition from AI functioning as a support tool to becoming an active participant in enterprise execution, creating new demands for governance, accountability and operating model design.
Despite the rapid adoption of AI, many organizations have yet to establish the structures required to scale such systems effectively. More than half of Chief Technology Officers, representing 57 percent, said they are already using AI to determine which tasks should be assigned to humans and which should be handled by machines. However, uncertainty surrounding task allocation remains a major obstacle to progress.
The report highlights that scaling AI has evolved into an operational challenge rather than a technological one. Only 44 percent of Chief Technology Officers believe leadership teams possess sufficient understanding of artificial intelligence. Just 46 percent reported having established frameworks for responsible AI, while only 36 percent expressed satisfaction with workforce trust levels.
Several persistent barriers continue to hinder progress. Lack of in-house technology skills was identified by 32 percent of respondents, while 31 percent pointed to uncertainty over return on investment. Another 27 percent cited a lack of urgency at the business level. These challenges indicate that organizations must redesign systems, processes and decision-making frameworks to support successful AI integration.
The research also reveals a significant shift in digital transformation priorities. For the first time, innovation has overtaken efficiency as the primary reason for digital investment. This reflects a move away from cost-driven optimization toward growth, differentiation and the development of new business models. While the trend is global, priorities differ across industries, with aerospace focusing on workforce development, life sciences emphasizing innovation acceleration and the energy sector prioritizing resilience, underscoring the need for industry-specific strategies.
The report found that artificial intelligence is changing work rather than eliminating it. Half of the surveyed Chief Technology Officers reported changes in required skills, while 49 percent observed shifts in daily work activities. Only 21 percent reported workforce reductions caused by AI, reinforcing the need for organizations to redesign responsibilities and workflows to support collaboration between humans and AI systems.
Jo Debecker, President and Chief Executive Officer of Akkodis, said the current phase represents a moment of realism rather than a slowdown in AI adoption. He stated that organizations are moving beyond experimentation and confronting the challenges of scaling AI across complex environments. According to him, the key issue is no longer deploying AI but integrating it into everyday work. He added that companies making the greatest progress are redesigning their operating models by aligning technology, human expertise and governance to achieve consistent outcomes.
According to the report, organizations are adopting three broad approaches to AI implementation. Some remain task automators that primarily use AI to improve efficiency. Others operate as pilot operators, experimenting with AI but struggling to scale. A third group, described as enterprise orchestrators, has begun embedding AI into workflows and decision-making processes. The report concludes that long-term success will depend on moving beyond isolated pilot projects and orchestrating AI across systems, teams and processes to achieve measurable business results.
With organizations entering a more mature phase of artificial intelligence adoption, the Akkodis report underscores that the future of AI will depend not only on technology, but on how effectively businesses align governance, workforce capabilities and operational structures to build scalable and sustainable enterprise ecosystems.
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