AI and Organizational Change: An HR Challenge Before a Technological One
Hi, this is Roberto Pezza and a few months ago I took part in a hackathon hosted by the Government Digital Service (GDS) in London, dedicated to the theme "Collaborative AI".
One remarkable aspect was the willingness of a government institution—often perceived as slow, bureaucratic, and constrained by security and compliance—to actively engage managers and professionals in exploring an innovative approach to AI adoption within organizations.
We were around 70 participants, representing a diverse mix of backgrounds and professional experience: HR professionals, L&D managers, agile coaches, transformation consultants, and software developers. This diversity reflects the direction taken by the most mature organizations today: a truly multidisciplinary approach to AI adoption.
A streamlined working process, with AI as a support
The structure of the hackathon was simple, collaborative, and highly pragmatic. In groups of six or seven, we were asked to work through a Business Case with the support of an "additional team member": Generative AI.
AI did not replace our work. Instead, it required each team to identify how to integrate Generative AI into the workflow in a meaningful and effective way.
The dynamics shaping team adoption and transformation
What I observed during the team activities mirrors the dynamics we see in our People & Development projects with clients when we introduce Generative AI.
These dynamics are increasingly present in organizations that intentionally and consciously adopt AI with a systemic perspective—one that recognizes people as the key enablers of this emerging technology.
1. Collaborative AI is no longer a technical topic: it is a people and organizational change challenge
AI adoption is not an IT project. First of all, it is a cultural and systemic transformation.
The UK experience shows that this shift is already being led by those responsible for people, processes, and collaboration—professionals who guide changes that are cultural, behavioural, and organizational.
For HR, this means establishing a new framework capable of supporting reskilling, redefining roles and responsibilities, and ensuring an overall governance model that unlocks the potential of AI.
2. Methodologies matter more than tools
The real value of this new way of working does not lie in Generative AI itself, but in how it is integrated into people's and teams' work.
AI is a technology whose impact is shaped day by day by human actions and behaviours. For this reason, effective adoption requires co-design, systemic thinking, and human-centered workflows.
AI amplifies what already exists:
- if collaboration dynamics are strong, AI accelerates and creates synergy across the system;
- if they are weak, AI amplifies misalignment and fragmentation.
3. Introducing AI requires organizational maturity
Agile, OKRs, continuous improvement, and ongoing feedback loops were already embedded practices in the British context. In the UK context they were taken for granted, reflecting the transformations that organization in the UK have already undergone. Within my team, speaking the language of these frameworks was essential to move quickly.
In many Italian organizations, however, these methodologies are still implemented as isolated "initiatives," rather than as widespread operational habits. This gap in organizational maturity can hinder AI adoption, generating resistance, confusion, and inefficiency.
It becomes crucial to strengthen culture, values, transparency, experimentation, and shared ownership.
4. AI does not eliminate roles: it changes how work happens
Observing people engage with the integration of AI in their work makes it immediately clear that what changes is the role, not its existence.
A widespread misconception needs to be addressed: the belief that AI necessarily equates to automation. In reality, it is agents—not AI itself—that automate tasks.
AI has the potential to enhance human capabilities and effectiveness, but only if guided properly. Otherwise, its contributions may be far from "intelligent," relying instead on probabilistic processes (see "AI Workslop: when the use of AI lower productivity").
Conclusion: Collaborative AI as a lever to redesign work
The London hackathon confirms that we are at the beginning of a new way of working.
For HR and Managers, this means rethinking how to support people in their adoption journey, within a broader organizational AI strategy.
Leaders of transformation must shift the conversation from:
"What can AI do?"
to
"How do we work with AI to generate more value?"
To fully realize the potential of AI adoption, organizations must operate on two parallel levels:
1. Technical and operational reskilling
- prompt design
- data interpretation
- effective use of AI copilots
2. Cultural and mindset reskilling
- working effectively in Human–AI systems
- navigating new boundaries of responsibility
- understanding that performance is no longer only individual, but emerges from the interaction between people and technology
Our direct experience confirms this duality (see "AI aptitude". When we help people discover their approach to using AI—and involve them in designing AI solutions aligned with their context—the best results emerge when these two levels are integrated.
Whether you are an individual, a team, or an entire organization, one question determines your future:
Are you leading the transformation, or are you being led by it?
Contact us to learn more about the projects we have delivered in this area.