Why This Executive Coach Went From Anti-AI To Using It As A Leadership Mirror
Ruth Pearce is an executive coach and speaker focused on leadership. In contrast to most of the experts we've interviewed, she initially vowed to avoid AI at all costs. But then, a friend challenged her to test her assumptions. And now, she uses AI to empower her people.
AI doesn’t replace human leadership — it exposes it: AI removes administrative excuses. Strong leaders use it to free time for empathy, clarity, and people development, while weak leadership becomes more visible and amplified. As Ruth Pearce puts it, AI widens the gap between effective and ineffective leaders by accelerating impact — for better or worse.
Human judgment must actively challenge AI outputs: AI is a powerful thinking partner, but only when leaders interrogate it. Asking for sources, counterarguments, blind spots, and alternative perspectives not only improves outcomes — it sharpens leaders’ own awareness of bias, intent vs. impact, and ethical responsibility. AI should be questioned, not trusted by default.
Ethical, intentional adoption matters more than speed: Sustainable AI use requires slow experimentation, strong guardrails, and human-in-the-loop design — especially in leadership, coaching, and performance contexts. Tools amplify behaviors, not values. Leaders must invest in learning, ethics, and accountability rather than rushing implementation and outsourcing responsibility to technology.
We chatted with Ruth to understand what changed. She shared her experience, use cases, and cautious optimism for the ways that AI is changing leadership forever.
The journey to executive coaching
I’m Ruth. British-born, long-time U.S. citizen, equal parts curious magpie and steady co-pilot. I’m the sort of introvert who loves a stage and then needs a quiet walk to listen for crickets and watch the butterflies. I mix UK and US idioms, collect good questions, and believe ethics isn’t a policy. It’s a practice.
I started out in London as an economist, but was quickly tempted into computing for banks and securities firms. At some point, I was asked to move from coding the programs to managing the projects—there is a story to that but we can keep that for another day.
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So, for years, I was a person in the middle. A project manager, sandwiched between team and leadership. I got drawn into the politics, succumbed to the pressure to toe the line, and focused on meeting others' expectations. And then one day I stopped. I spoke up. It cost me. And it clarified my path.
I have always searched for science-based, effective, actionable strategies that anyone can take, wherever they are in the spiral. And that's where I'm focused now, as a speaker and executive leadership coach.
My mission is to make sure no one has to feel the way I did, or has to crash as far to find the way forward. I experiment so others don't have to. And I learn: not to become the sum total of what I know, but to learn who I was always meant to be.
Why some leaders resist AI
At the beginning, I shied away from AI, telling friends and colleagues that I would never use it. Then, one day, one of those friends challenged me. She pointed out that it was unlike me to dismiss something before I had even tried it. I am decisive and form strong opinions, but I do it from data, experimentation, and facts, and always with a mind open to being persuaded otherwise.
I accepted her challenge and tried it out. And I let go of the belief, which was founded on very little, that:
- AI was something we could choose to use or choose not to
- AI had no value in my work
- My work was so entirely human-focused that nothing could be automated or assisted by smart technology
I started playing with AI and seeing what it could and could not do. I learned why it hallucinates. I partnered with people who knew more about it than me. Basically, I did what I do best: experimented, engaged in conversations, and came to a tentative conclusion that some may not like.
On one hand, AI helps good leaders get better because they get to focus on what AI cannot do — the human side.
They can pay attention to their people in a way that day-to-day leadership duties usually prevented them from doing. From generating notes and memos from meetings, to brainstorming the most efficient way to get something done, to synthesizing multiple sources of information into quickly-absorbable fact sheets. Now, leaders can reduce the energy and effort of administration and focus on their key differentiator — the ability to get the best out of their people, not just for the organization, but for the individuals themselves.
On the other hand, not-so-good leaders are going to be spotted more easily because workload will be less of an excuse for why they are struggling with the essential human side.
In other words, for good leaders, AI is a great opportunity. For underperforming leaders, AI is a big red flag.
How AI widens the gap between effective and ineffective leaders
That's the thing about AI in leadership— it widens the gap between effective and ineffective leaders.
People who are already great at what they do will become great at using AI to do what they do even better or more efficiently. Those who struggle or are less effective will find that AI accelerates the process by which people notice shortfalls.
For example, where someone may send out three ill-thought-out emails today, they may be sending out 100 with AI tomorrow.
Most people struggle to differentiate between what they are saying and what they mean to convey — it is the difference between intent and impact. AI reinforces impact and, when it does not match our intent, it does more harm more quickly.
Why leaders must challenge AI outputs
I'm not the only one with resistance to AI. At a conference recently, an HR leader explained how they are using AI in performance management: individual reviews to collate and aggregate feedback, and to provide goals for moving forward. This was exciting to the presenter, but the audience gasped.
There is always the concern about where the human enters the loop. And that's valid. AI left to its own devices can go off track, hallucinate, and make mistakes.
But I always come back to the fact that the AI is only as good as the human operating it.
There is a tendency to blame AI for things. "It hallucinates" is a common refrain. And it does — I, for example, am often told by AI that I am a well-known and successful Canadian politician.
But that is not intrinsic evil intent from AI; it is the training we have provided. We have told AI tools that "I don't have an answer for that" scores a zero because it does not satisfy the human need for answers. So, it has learned to "fill the gap" with something made up.
In other words, we have trained AI to be people-pleasing. So we need to train our humans to understand that and use AI well.
Instead of taking AI's answers as gospel, it is important to challenge AI by requesting sources, asking what it is leaving out, or even by prompting it to present both sides of an argument so you can see which seems stronger.
Here's a good example: My AI told me my business model was great. Then, I asked in what ways it was letting me down. The list was LONG!
Challenging AI in decision making is making me more thoughtful about my own biases — how much I want confirmation of the idea I already have and how much that influences the way I pose problems to AI — and that is having a big impact on how I lead.
There is always the concern about where the human enters the loop. And that’s valid. AI left to its own devices can go off track, hallucinate, and make mistakes. But I always come back to the fact that the AI is only as good as the human operating it.
Building a leadership tech stack focused on clarity, ethics, and data
In my current role, my software stack is built around a few core aims: clear communication, transparent priorities, and data-informed decisions.
- Core communication and collaboration: Day-to-day, most work runs through an Outlook and a team collaboration app called Signal, plus a video conference software for hybrid meetings. These tools are effective for keeping everyone reachable and for running quick touchpoints, but they can also create noise and always-on expectations if not managed intentionally. As a leader, I increasingly document channel structure, norms about response times, and meeting discipline to offset that.
- Project and workflow management: I use work-management tools like Asana, Trello, and even Microsoft tasks for initiatives, priorities, and cross-functional work. The biggest impact here is visibility — people can see what’s in progress, who owns what, and how work ties back to strategic goals. But these AI project management tools are only as good as our habits. When leaders consistently use dashboards in 1:1s and team meetings, they drive alignment; when we don’t, the tool quickly becomes extra admin. Use AI to help you with this.
- Knowledge and documentation: A shared AI knowledge base tool called OneDrive holds all our materials including decisions, business plans and tracking for our projects. This supports continuity, and accountability — decisions are written down, not just remembered. The gap I still see in AI in knowledge management from a leadership perspective is curating content so people know what is current versus historic.
- AI and productivity tools: We’re experimenting with custom GPTs for drafting communications, exploring scenarios, and summarizing information ahead of meetings. These AI productivity tools save time on first drafts and help leaders explore options more quickly. But they require clear guardrails and training so they augment judgment rather than replacing it. Users need to be effective prompt engineers to create responses that are not built on personal or systemic bias.
Ultimately, the stack is important, but the real value comes when leaders anchor it to behaviors: clear priorities, frequent communication, psychological safety, and visible use of data in decision-making. The best AI tools for business amplify good leadership; they don’t replace it.
How digital clones can scale leadership
One of the biggest challenges of leaders is being available, scalable, and accessible. How many times have leaders said, "I wish I could clone myself/you"?
So, that's what I did for my coaching clients — I created my own AI assistant to handle the repetitive tasks.
It's not like working with OpenAI. The data protection and safety protocols need to be much more robust. We also need secure handoffs so that the assistant can learn about the client and I can build on the AI in leadership development sessions that take place between our live human sessions. And the tool needs to be able to recognize when it is out of its depth and in need of a human touch from its human-in-the-loop.
To build it, I teamed up with a tech partner who focused on ethics, inclusivity, and human-in-the-loop AI use. And I trained it personally.
It takes a lot of time and skill to develop an effective assistant. It is not something you build in an afternoon. There are lots of loops and refinements. In fact, it took several months and we're still perfecting it. But I think the result will be a better experience where I can focus on what I do best — using empathy and building connections.
Instead of taking AI’s answers as gospel, it is important to challenge AI by asking for sources, asking what it is leaving out, or even by asking it to present both sides of an argument so you can see which seems the stronger.
How leaders can use AI without sacrificing the work that matters
Recently, I saw a post on Instagram where someone was complaining that they wanted AI to do the washing up and the laundry so they could spend more time being creative — but AI was doing the creative tasks instead. I think this is a very important insight.
I want AI in the workplace to help speed up the processes that are time consuming. Logical sequences of emails, practices, tailored content, and so forth.
I also want its help paying attention to detail after I say "good enough" so that I can avoid careless mistakes.
And I want its help as a thinking partner, accelerating idea generation.
But I don't want it to do the tasks where I get my sense of fulfillment.
Why leaders should adopt AI slowly and with intention
Overhauling processes is much slower-going than people realize.
In fact, I would say that we have not overhauled anything completely. I expect it will be another six months or more before we have changed even a single process fully as a result of AI.
If we make changes too soon and without enough experimentation, we risk compromising our clients and endangering their sense of safety. So, we're taking it slow.
I'm not alone. I think most organizations are far from AI-ready. They're struggling to understand what they need from AI in business strategy. They're building the plane as they fly it. And that can lead to a sense of overwhelm.
It's just such a big leap in such a short amount of time. Every day highlights new ways to be more effective through AI, as well as more ways that AI can pose a threat. Leaders and their teams are struggling to fully embrace what the opportunities and risks are.
Why leaders must take responsibility for ethical and informed AI adoption
Here's my advice: Experiment, research, take classes, learn prompt engineering. AI is here, and it is important that we not necessarily embrace using it, but embrace learning about it.
Gallup shared in a recent report that many employees assume leadership is putting together the plan for AI implementation, and yet those very same leaders are saying that they are waiting and seeing what happens. This disconnect is dangerous.
As leaders, it is important that we learn new skills, update our ethics, and stay current. Our teams and clients will assume that we are taking this seriously and that we are making sound, informed decisions about AI in business.
Let's live up to that expectation and obligation.
Why leadership judgment matters most
A big concern for me is ethical use. If we are all relying on someone else to ensure we do it right, we are in trouble.
And we have not had a chance to truly evaluate the cost of AI in areas like sustainability— environmentally, educationally, or otherwise.
So, some humans predict amazing advances while others predict doom and gloom.
But to my grandparents, front-loading washing machines were scary. To my mother, cell phones were scary — what's wrong with calling someone on a landline from a rotary phone anyway?
If there are two things we know from human history, it is that:
- There are always unintended consequences and benefits.
- Everything we invent can be used for good or not so good.
For better or worse, AI is here. Let's make the best of it.
Follow along
You can follow along with Ruth Pearce as she continues to push the envelope in her coaching business at A Lever Long Enough, her speaker page, and her LinkedIn. You can also check out her Amazon book page: Be Hopeful, Be Strong, Be Brave, Be Curiousᵀᴹ.
More expert interviews to come on People Managing People!
