Agentic AI – systems that can plan, reason and act autonomously – is moving rapidly from experimentation to enterprise scale. But as organisations begin to adopt these technologies, a new report suggests the real challenge is not technical, but human.
A new report by the UCL School of Management’s Analytics Lab in collaboration with consultancy firm Capgemini argues that scaling agentic AI requires a fundamental rethinking of how organisations are structured, managed and led. Their report highlights that success will depend on building a new kind of “human–agent” enterprise, where people and AI systems work in close partnership.
Unlike earlier forms of AI, agentic systems are capable of executing multi-step processes and orchestrating workflows, making context-aware decisions with increasing autonomy. This shift raises opportunities but of course raises risks too, particularly as organisations move from pilot projects to large-scale adoption.
The report identifies several key areas that must evolve in parallel if organisations are to realise the benefits of agentic AI and mitigate potential hazards:
· Human–AI collaboration: Organisations must carefully design how people and AI agents work together, ensuring clear roles, responsibilities and accountability.
· Organisational structure: Traditional ways of organising work will need to give way to more dynamic, product-led operating models capable of supporting networks of human and agent teams.
· Skills and talent: New roles are emerging – from “agent creators” and “agent governors” to “multi-agent collaborators” – requiring both advanced technical expertise and uniquely human capabilities such as creativity and judgement.
· Governance and trust: As AI systems take on more autonomous decision-making, organisations must embed robust oversight, ethical frameworks and accountability mechanisms from the outset.
The report emphasises that organisations often underestimate the “people challenge” associated with AI transformation. Employee anxiety, resistance to change and unclear organisational vision can all slow adoption and limit impact. For example, many workers express concern about job displacement and a lack of transparency in how AI systems operate.
At the same time, a narrow focus on cost reduction risks undermining the broader opportunities presented by agentic AI. Instead, the authors argue that organisations should reinvest productivity gains into innovation, new business models and improved customer experiences.
The research also introduces the concept of “human–AI chemistry” – the quality of interaction between people and AI systems – as a key determinant of success. This depends on clearly defined roles, well-designed interactions between agents and humans, and strong alignment with ethical and legal standards.
Ultimately, the report concludes that agentic AI is a catalyst for large-scale organisational transformation. Businesses will need to redesign their operating models, rethink talent strategies and build new governance frameworks to fully capture its value.
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