Leading with purpose in an AI-driven world
November 2025
6 Ways of making AI work for people, not the other way around
When I hosted AI: Things You Need to Know but Nobody Tells You at AI Week 2025, I came away thinking less about algorithms and more about people. The session brought together two truly thoughtful voices, Professor Kerensa Jennings and Cayelan Mendoza of Clu. What struck me most was how the narrative around artificial intelligence is shifting from speed and capability to responsibility and design. The challenge is no longer about building smarter machines but about cultivating a wiser relationship with them.
One idea that stayed with me was how every AI decision sits inside a larger ecosystem. The smartest move in technology is not always acceleration but awareness of impact. So a small optimisation in one area can quietly distort another. Efficiency for a single team might reduce resilience across the organisation.
Leaders who understand this think ecologically. They know that every line of code touches people, processes, and markets. True progress depends on how well we see those interconnections and anticipate their consequences.
AI’s pace of innovation constantly tests our judgment. Just because we can automate something does not mean we should.
During the session, I was reminded that maturity in digital leadership comes from being able to pause and ask, “Who benefits, and who might be left behind?” That simple shift from “could” to “should” reframes innovation as a moral choice, not a mechanical one. This can be tricky if your actions are seen as getting in the way, but governance is not about slowing down progress but steering it in the right direction.
Another recurring theme was the irreplaceable role of human oversight. We often talk about keeping “humans in the loop,” but that phrase understates the importance of accountability.
AI can draft, predict, and accelerate, yet it cannot take responsibility. So the real test of automation is whether it amplifies human judgment or replaces it. The human still signs their name at the end. That accountability gives the work credibility. When people remain answerable for automated outcomes, systems become stronger, not weaker.
One of the most uplifting threads of their talk was about how AI is reshaping talent. As automation grows, value shifts from what we know to how we think. Skills like curiosity, empathy, and adaptability have become competitive advantages.
When organisations recruit for potential rather than pedigree, hidden talent surfaces. Skills-first thinking helps us see people not as replaceable, but as essential to the evolving ecosystem of work. I found that idea inspiring because it reframes technology as an enabler of inclusion rather than a threat to employment.
AI systems are living systems; they need care. Progress without vigilance quickly becomes a risk. Data changes, models drift, and assumptions degrade. Leaders should treat AI governance as maintenance, not management.
Monitoring, retraining, and revisiting policies are not signs of inefficiency but of maturity. Responsible use of AI is not about constant novelty; it is about disciplined stewardship.
The deeper lesson I took from this talk is that human strengths — judgment, ethics, imagination — remain the foundation of everything worth building. Technology may multiply capability, but only people give it purpose. So the more advanced the technology becomes, the more our humanity matters.
As I reflect on the conversation, I keep thinking that AI should never make us less human. The future belongs to those who design systems that protect our ability to think, question, and care.
I am sure that you can tell i enjoyed introducing this talk and if these reflections above also resonate with you then I would encourage you to watch the full AI Week 2025 discussion, AI: Things You Need to Know but Nobody Tells You, featuring Professor Kerensa Jennings and Cayelan Mendoza.
👉 Watch the full conversation on-demand
November 2025
November 2025
November 2025