Senior Leaders in Regulated Orgs - Post-AI Professional Identity

What if you don't like the version of yourself when AI does the part of your work you love? I've been thinking about this from two sides. On one side, the executives I see commissioning AI tools to automate "the boring parts." The cost models. The customer service triage. The analytical grunt work. The framing is always efficiency. The unspoken bet is that the work you'll be left with is the work you've always wanted to do. On the other side, the senior practitioners quietly admitting the truth: the work they were planning to automate away was the work that made them themselves. The hours of structured analytical thinking. The conversations with frontline staff that the dashboard now summarises. The slow building of judgement that came from doing the thing, repeatedly, until you knew it in your hands. The version of yourself that emerges on the other side of automating "the boring parts" is not always the version you wanted to meet. I'm not arguing against AI tools. My practice is built on helping organisations adopt them responsibly. I am arguing that "responsible AI adoption" needs to include a harder question than the ones in the procurement framework: Who do I become when this work is no longer mine? If the answer is someone I'd rather be, automate with confidence. If the answer is someone smaller, less curious, less able to make the next judgement call, the efficiency gain has a cost the spreadsheet won't catch. The most important AI governance question of the next five years isn't "is this model safe to deploy." It's "what kind of professional remains after this is deployed." I'm exploring this question and others like it in The Version Question, a series on the costs and trade-offs we don't talk about in senior careers. If you're working on AI adoption inside a regulated organisation and this question is sitting on your desk too, I'd like to hear from you. #TheVersionQuestion #AIGovernance #SeniorLeadership #FutureOfWork