In my research with 18 UK SMEs, one leadership process appeared repeatedly in organisations that made progress with GenAI: sensegiving.
What sensegiving means
Sensegiving refers to how leaders actively shape the way others interpret change — particularly when outcomes are uncertain and understanding is incomplete. It is not about providing answers. It is about framing meaning.
GenAI creates precisely the conditions where sensegiving becomes essential. Leaders are expected to act, but clarity is partial. Capabilities are evolving. Risks are real but poorly understood. In these conditions, many leaders default to waiting — hoping certainty will arrive before communication does.
What my research showed is that this waiting is itself a leadership signal. Employees were not waiting for perfect explanations. They were waiting for intent. When leaders remained silent, that silence was interpreted as doubt, lack of seriousness, or hidden risk.
Three moves that made the difference
In organisations that progressed, leaders engaged in three sensegiving moves.
First, they framed purpose. They explained why GenAI was being explored now, and what organisational problems or opportunities it related to. This prevented experimentation from feeling arbitrary.
Second, they legitimised experimentation. Leaders made it explicit that learning was expected, mistakes were acceptable, and provisional outcomes were part of the process.
Third, they established provisional boundaries. They clarified what would not be done — at least for now. These boundaries did not constrain innovation. They made engagement feel safe.
Uncertainty named is uncertainty managed
Crucially, none of this required certainty. Leaders who acknowledged what they did not yet know were often more trusted than those who avoided the topic altogether. By naming uncertainty, they reduced speculation and created shared understanding.
Employees do not need leaders to predict the future of AI. They need leaders to make uncertainty discussable.
Where sensegiving was present, GenAI became a collective inquiry rather than a private concern. Readiness began to form not because the path was clear, but because participation felt legitimate.