Self-Coaching in the Age of AI: Who Is Really Doing the Thinking?

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Episode: Self-Coaching in the Age of AI: Who Is Really Doing the Thinking?

What happens when the technology reshaping your workplace becomes the technology you turn to for help deciding whether to leave it?

Maddy has been offered voluntary redundancy after twenty-three years. She turns to AI looking for an answer — but discovers that more information isn't necessarily what she needs.

This WorkLife Story explores the difference between using AI to help us think and outsourcing our thinking to it — and why self-coaching may become more important, not less, in the age of AI.

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Maddy had been offered voluntary redundancy after twenty-three years. For months, there had been talk of restructuring, automation and the efficiencies AI would make possible. Now she had a decision to make. Stay. Or take the package and leave. And the place she turned for help deciding? AI. Welcome to WorkLife Stories from School of WorkLife. I'm Carmel O' Reilly. Today's episode is Self-Coaching in the Age of AI: Who Is Really Doing the Thinking? It's a story about one consequential decision — and where AI ends and self-coaching begins. Maddy's Decision Maddy had been offered voluntary redundancy. Twenty-three years with the same organisation, and now there was a figure on a page for leaving it. The announcement hadn't been entirely unexpected. For months there had been talk of restructuring, automation and the efficiencies AI would make possible. Roles would change. Some would disappear. Work that had once taken teams of people could increasingly be done differently. Maddy's role wasn't disappearing. Not yet. She could stay. Or she could take the package and leave. For three days she did what people do when a decision is too large to hold comfortably in their own head. She talked about it. Her husband thought she should take the money. "You've been saying you need a change for years." Her closest colleague thought she should stay. "Don't jump before you're pushed. You've got years of experience here." Her sister asked what the redundancy package was worth and immediately reached for a calculator. Everybody had an answer. Maddy didn’t. What Maddy needed wasn't another answer. She needed a way of finding her own. That is where self-coaching begins — not with knowing what to do, but with knowing how to question yourself well enough to discover what you think. On the fourth evening she opened her laptop. And asked AI. I've been offered voluntary redundancy after twenty-three years with my company. Should I take it? The answer arrived in seconds. It was sensible. Don't make the decision on the redundancy payment alone. Consider your financial position, pension, employability, future earning potential, appetite for change and the prospects of your current role. It suggested making a list of the advantages and disadvantages of staying and leaving. Maddy did. Then she gave AI more information. Her age. Salary. Savings. Mortgage. Pension. Industry. Experience. The answers became more specific. She asked about the employment market. She asked what jobs someone with her experience might move into. She asked what skills she had that could transfer elsewhere. She asked about the risks of staying in an organisation that was restructuring around AI. By eleven o'clock she knew considerably more than she had known at seven. She still didn't know what to do. When More Information Isn't the Answer The next evening, Maddy went back. This time she asked: Based on everything I've told you, what would you do? Another thoughtful answer appeared. But something about the question bothered her. She read it again. What would you do? Who was you? The technology helping her think about whether to leave a workplace being reshaped by technology? There was an irony in that. But that wasn't what bothered her. The problem was that she had spent two evenings giving AI everything she thought it needed to understand the decision. Her finances. Her employment history. Her qualifications. The redundancy terms. The state of her industry. What she hadn't given it was harder to put into a prompt. She was tired. Not the tiredness that disappeared after a week's holiday. She had been doing variations of the same work for twenty-three years and had become extremely good at it. She wasn't sure she wanted to become extremely good at it somewhere else. She hadn't told AI that. Perhaps because she hadn't quite told herself. So she changed the question. What should I be asking myself before I decide? The screen filled again. Questions this time, rather than answers. Some were practical. Some she had already considered. And then she reached one that made her stop. If you weren't being forced to make this decision now, what would you want the next stage of your working life to look like? Maddy closed the laptop. The Question That Followed Her She didn't answer it that evening. The question went to work with her the following morning. It sat beside her through a meeting about the restructuring. It followed her to lunch. It came home with her. That evening she opened a notebook rather than her laptop and wrote the question across the top of a page. What do I want the next stage of my working life to look like? Her first answer was predictable. Something secure. She looked at it. Twenty-three years in one organisation and a voluntary redundancy letter on her kitchen table had already taught her something about security. She tried again. Something I'm good at. That wasn't quite it either. She was already good at what she did. She sat with the question. Eventually she wrote: Something where I'm still learning. That felt different. Not an answer to whether she should take redundancy. But perhaps a better place from which to make the decision. This was self-coaching in practice. The question hadn't given Maddy an answer. It had taken her beneath the obvious ones — security, competence, staying or leaving — until she reached something she hadn't known she needed to say. That is what a good self-coaching question can do. It doesn't tell you what to think. It gives you somewhere better to think from. So Who Was Coaching Whom? AI had done something useful. Very useful. It had helped Maddy organise information, identify considerations, explore possibilities and eventually encounter a question she hadn't thought to ask herself. Was that coaching? Perhaps. But AI hadn't recognised the moment Maddy stopped at the question. Maddy had. It didn't know why something where I'm still learning mattered. Maddy did. It didn't know that she had spent the previous three years becoming increasingly restless in work she could almost do without thinking. She hadn't told it. AI knew what Maddy put into the conversation. Maddy had access to something much larger: twenty-three years of experience, forgotten ambitions, values, disappointments, conversations, instincts, compromises and knowledge of herself — including the things she hadn't yet found words for. The question helped her reach some of it. And that distinction matters. Using AI Without Outsourcing Your Thinking There is a temptation to make the relationship between AI and human thinking an argument about replacement. Can AI replace a coach? Can it give career advice? Can it make better decisions than we can? But perhaps there is a more useful question. How can we use AI without outsourcing our own thinking to it? Used well, AI can be a remarkably useful thinking partner. It can generate questions. Challenge assumptions. Offer alternative interpretations. Help us see options. Organise information. Ask us to consider something we have overlooked. But there is a difference between using something to help you think and asking it to do your thinking for you. Maddy's first question was: Should I take voluntary redundancy? She wanted an answer. The question that eventually helped her was different: What should I be asking myself before I decide? That returned the thinking to her. What Self-Coaching Still Requires of Us Self-coaching is the practice of asking yourself the questions that bring clarity, finding your own answers and acting on what you learn. AI doesn't make that practice redundant. It may make it more important. Because we now have extraordinary access to answers. We can ask almost anything and receive something plausible, articulate and useful within seconds. The skill we may increasingly need isn't simply knowing where to find an answer. It's knowing when an answer isn't what we need. Knowing which question matters. Knowing when something doesn't quite ring true. Knowing when we're looking for perspective and when we're looking for permission. Knowing when to close the laptop and continue thinking for ourselves. Maddy eventually took the voluntary redundancy. But not because AI told her to. And not because her husband thought she should, her colleague thought she shouldn't or the financial calculation made one option objectively better. She took it because somewhere between the questions on a screen and the question she carried into her own life, she understood what she was actually deciding. She wasn't simply deciding whether to stay or leave. She was deciding whether the next part of her working life would be a continuation of the last one. For the first time in twenty-three years, she wanted not to know exactly what she was doing. AI had helped her reach the question. The answer was hers. And so was what came next. That's today's WorkLife Story — Self-Coaching in the Age of AI: Who Is Really Doing the Thinking? AI helped Maddy reach the question. But the answer was hers. And perhaps that's one of the most important distinctions in self-coaching today: using AI to help us think without asking it to do our thinking for us. You can continue exploring Professional Self-Coaching through more stories and practical resources at School of WorkLife. All the details and links are in the show notes. Remember: a good question can help you think differently. What you do with the answer is yours. Thank you for listening.