When I decided to enrol in an MSc in Artificial Intelligence at the University of Bath, I was already leading two teams of analysts at the Post Office on one of the most high-profile improvement programmes in the organisation. People asked whether it was worth the extra commitment. My answer then — and now — is yes, but not for the reason most people assume.
It's not about collecting credentials
I've never been motivated by titles on a CV. What drew me to the MSc was a gap I could feel in my own practice: I was building models, presenting to board-level stakeholders, and leading teams — but the underlying theory of modern AI was moving faster than I could pick up through work alone.
Enigma machine simulations, hybrid optimisation algorithms, and advanced ML coursework aren't abstract exercises for me. They're tools I'm actively connecting back to the problems I see at work — even when the domains are completely different.
What studying alongside work actually teaches you
The biggest lesson isn't technical — it's prioritisation. When you have limited hours, you learn quickly which concepts are foundational and which are noise. You also learn to communicate complex ideas simply, because you don't have time to be verbose.
Leading teams while studying has made me a better manager too. I understand what it feels like to be stretched, which makes me more deliberate about protecting my team's focus and being clear about what matters most each week.
Looking ahead
AI isn't replacing analysts — but analysts who understand AI will have a significant edge. I'm investing in that edge deliberately, and I'll share more here as the programme progresses and as I find connections worth writing about.