As some of you may know, I have recently completed my MBA studies at Warwick Business School. While I wait for my graduation to be ratified, I wanted to share some of what I discovered during the process of creating my dissertation. This article — the first in a series of nine — draws on research with 18 UK-based SMEs, exploring how leaders are navigating Generative AI adoption under conditions of uncertainty, limited resources, and incomplete understanding.
The pattern that kept repeating
Across these organisations, there was broad agreement that GenAI matters. What varied sharply was how leaders approached readiness. Many treated it as a technical hurdle to be cleared later — after tools were selected, skills assessed, or strategies finalised. In practice, this delay proved costly.
In SMEs, uncertainty is often managed quietly. Leaders too often hesitate to speak before they feel confident. Employees, meanwhile, speculate. GenAI tools are explored informally, in pockets, without shared purpose or coordination — sometimes without leaders being aware. The result is rarely open resistance.
It is confusion.
Where initiatives actually stall
What my research consistently showed is that GenAI initiatives stall long before technical capability becomes the binding constraint. They stall at the level of meaning.
For employees, GenAI is not experienced as a neutral technology. It immediately raises unsettling questions: Why are we doing this? What does this mean for my role? Is this safe? Is this serious? When leaders do not actively engage these questions, they do not disappear. They are answered informally, emotionally, and often pessimistically.
This is why GenAI readiness is not a technical starting condition. It is an organisational outcome — shaped by leadership behaviour under uncertainty.
Leadership as the variable
In organisations where leaders waited for clarity before speaking, uncertainty intensified. Silence was interpreted as doubt. Experimentation felt risky, something to be hidden rather than shared. GenAI became something happening to people rather than with them.
By contrast, the SMEs that progressed were not always those with the clearest roadmaps. They were those where leaders were willing to frame purpose early and imperfectly. Readiness did not come from certainty. It came from legitimacy.
When leaders took responsibility for explaining why GenAI was being explored, how learning would happen, and what was not yet decided, employees were better able to engage without needing full answers. Ambiguity became manageable because it was shared.
The leadership challenge, then, is not "How do we implement GenAI?" It is "How do we lead meaningfully when we do not yet know what GenAI will become?"
GenAI readiness begins not with tools or pilots, but with leadership sensemaking made visible. In the next article in this series, I will examine what that looks like in practice — and the three specific moves that distinguished leaders in higher-performing SMEs.