Making Sense of AI
In almost every conversation I’m having with leaders right now, there’s a similar undertone.
The technology is moving fast. The headlines about AI are loud. Time and headspace are limited. Some teams are experimenting. Others are hesitating. Most are doing a bit of both.
If you feel behind, you’re not. Most organisations are still working this out in real time.
The pressure many leaders feel is to “catch up” with large corporates or tech firms. But I’d push back on that. You do not need their scale or their budget. You need a way to move from hesitation to thoughtful action.
Let’s get it into it.
Consider Purpose
AI feels overwhelming because there are too many models, too many promises, and too many public examples of things going wrong. Add ethical concerns, job-impact worries, and quiet uncertainty about your data or systems, and paralysis makes sense.
Instead of starting with tools, start where you would begin any serious strategy conversation: purpose.
Why does your business exist? What problem do you solve, and for whom?
Your purpose is more than a slogan. It shapes how your team shows up and what your customers trust you for. It provides stability in a fast-moving environment. The question is not “How do we use AI?” but “How could AI support what we are already here to do?” And in some cases, perhaps it can’t.
If a potential use case undermines trust, weakens quality, or pulls you away from your core commitments, it is not strategic. It is distraction.
Once you are clear on purpose, the conversation becomes more practical.
Examine Processes
Rather than scanning the horizon for the most advanced use case, look inward. Where does time leak? Where are people bogged down in repetitive admin, first drafts, summaries, or internal coordination that takes longer than it should?
AI can often help at that level. Not as a transformation program, but as a support. Small, contained experiments that are low-risk and reversible. Early adoption should feel like learning, not upheaval.
Include People
And then there is the part leaders underestimate: people.
Even positive change triggers resistance. Before you talk about tools, anchor what is staying the same. Your standards. Your values. Your commitment to clients or customers. Continuity reduces anxiety.
Clarity matters more than over-sharing. You do not need to broadcast your own uncertainty. You do need to communicate a steady message: we will explore this carefully, we will test what fits, and we will discard what does not.
Most importantly, listen. Expect curiosity from some and skepticism from others. Make room for both. People are far more likely to support what they feel heard in shaping.
In closing…
You do not need a sweeping AI strategy to begin. You need a grounded frame.
Keep returning to three questions. Why are we here, and what must not be compromised? Where could small improvements genuinely help? How will we bring others along with clarity and care?
This is not a race. It is a leadership moment.
Ellie Hearne teaches AI, innovation, and strategy at Oxford University's Saïd Business School and facilitates offsites for leaders navigating complexity. She serves as a trustee of the University of St Andrews American Foundation.