I started out working on listed company audits. This gave me a close, technical understanding of how large businesses report and operate. I qualified as an ACCA member and moved across into consulting, focusing on finance strategy. That shift gave me my first real taste of advisory, helping businesses think through the financial side of strategic decisions rather than just reporting on the past.
After relocating to London to build my consulting career, I got my first exposure to a live merger. That changed the direction I wanted to take. I liked the pace, the pressure to solve real problems quickly, and being close to the decisions that actually shaped the outcome of a deal. My recent move to the deal advisory practice, as part of the deal execution team, felt like the natural progression of a path that started in audit and ran through consulting to where I am now.
At the end of the day, this is a people business
No two deals look the same. On one project I might be helping a client prepare for day-one readiness ahead of a merger. On another, I could be supporting cutover activity for a carve out. Elsewhere, I might be building a red flags report during due diligence on a merger. I enjoy that variety very much. Every new project brings a different client, and a different set of problems to solve.
I work with a strong team, and we make a point of getting together regularly to share experiences from our different projects. Those catch ups are some of the most interesting parts of my week; you end up learning from situations you weren’t even directly involved in.
Stakeholder management is a consistent challenge. Deals involve a lot of people with different priorities and levels of information, and often different levels of trust in the process. At the end of the day, this is a people business, and managing those relationships well is often just as important as getting the numbers right.
AI has raised the bar for what real expertise looks like
AI has made generalist knowledge widely accessible. That’s raised the bar for what real expertise looks like. Clients increasingly want people who’ve lived through the situation, can draw on real-world experience and tell them with confidence what works and what doesn’t in practice. That judgment isn’t something you can get from a search engine.
One of the most pressing issues for practitioners is adapting to new technology while building teams to work effectively within it. AI tools can now do a lot of the basic analysis and reconciliation work that juniors traditionally learned on. That’s efficient, but if that entry-level work disappears, how do juniors build the judgment and expertise that used to come from doing it themselves? Firms need to rethink training, so people are still developing real skills, not just learning to operate a tool.
There’s also a data-quality and trust issue. AI output is only as good as the data and prompts behind it, so teams need to learn how to sense-check what a tool produces rather than accepting it at face value. That’s a skill – and one that a lot of people, at all levels, are still building.
Away from work, I paint when I get the chance, and I’m a keen classical music fan. My husband sings with the London Symphony Chorus, so I attend all their concerts. It’s a nice contrast to the pace of deal work, and a lovely way to switch off.
