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AI is changing the way organisations work, make decisions and solve problems, but as AI becomes more capable, the role of the leader isn't becoming less important, it is becoming more complex. The pace of change is significant. The World Economic Forum reports that 86% of employers expect AI and information-processing technologies to transform their business by 2030. Leaders are now expected to combine AI fluency with something much harder to automate: emotional intelligence. They need to understand what AI can offer, where its limitations lie and how to help their people navigate the opportunities and uncertainty that come with it. This isn't simply about learning how to use new tools, it's about learning how to lead in an environment where technology is increasingly part of the team – and that means moving beyond experimentation. Many organisations have spent the last couple of years exploring what AI could do. The next challenge is turning that experimentation into something more meaningful by building the capability to use AI well, identifying where it can genuinely improve how work gets done and translating AI ambition into practical business value. That requires leaders to ask different questions: Where can AI genuinely make a difference to our organisation? What capabilities do our people need to use it effectively? How do we move from experimenting with AI to embedding it in the way we work? And alongside those questions: When should we trust an AI-generated recommendation – and when should we challenge it? How do we make ethical decisions when the data tells us one thing, but our experience tells us another? How do we build confidence in AI without losing the human connection that makes teams effective? These aren't simply technology questions. They are leadership questions. As organisations move towards embedding AI into everyday work, AI literacy is becoming an increasingly important part of leadership development, but technical understanding alone isn't enough. Microsoft's 2026 Work Trend Index found that 86% of AI users treat AI output as a starting point, not a final answer and remain responsible for the thinking. When asked which human skills matter most as AI takes on more work, quality control and critical thinking came out on top. That matters. Because the more capable AI becomes, the more important it is for leaders to understand where technology ends and human judgement begins. Leaders need the confidence to interpret AI-generated information with discernment, communicate openly about how AI is being used and create the conditions for their teams to experiment, learn and ask questions. Just as importantly, they need to know when not to delegate the decision to AI. Effective leadership is ultimately about people: it's about good judgement, developing relationships, trust and accountability – plus much, much more. An algorithm can identify patterns, analyse information and make recommendations. It can't understand the full human context behind a difficult conversation, recognise the concerns that aren't being voiced or take responsibility for the impact of a decision. The most effective leaders of the future won't be those who simply use the most AI. They will be those who understand how to combine the strengths of technology with the strengths of people. That means being curious enough to embrace what AI can offer, but discerning enough to recognise its limitations. Using data to inform decisions without losing sight of the people behind the data and helping teams adapt to new ways of working without losing the trust and connection that make those teams effective. AI may change how we lead, but the best leadership will always be human.