Nova: Here's a number that should make every leader sit up straight: 87% of executives believe AI will significantly change their leadership role within three years. But only 23% feel prepared for that change. That's a massive gap between awareness and readiness.

Nova: And here's the thing — most leaders are responding to this gap the wrong way. They're signing up for prompt engineering courses, downloading every AI tool they hear about, and filling their browser tabs with tutorials. They're what Joel Salinas Frencia calls AI hoarders. Collecting tools without strategy.

Nova: : AI hoarders? Okay, that term definitely hits. I've definitely been guilty of that. So who's Joel Salinas Frencia, and what makes his approach different from all the other AI advice flooding our feeds?

Nova: That's the perfect place to start. Joel Salinas Frencia is an AI leadership author, executive coach, and the founder of Leadership in Change, a newsletter followed by over 7,000 CEOs, executives, and founders. He's an MBA-trained business strategist who was born in Bolivia, now works as a senior director at a global humanitarian organization, and runs three AI-powered businesses. He spent a decade leading teams through organizational change.

Nova: : So he's not a tech evangelist who parachuted in from Silicon Valley. He's actually inside organizations watching AI rollouts succeed or stall.

Nova: Exactly. And that real-world experience shapes his entire philosophy. His central message is captured in the phrase Leading with AI. Not just using AI. Not just adopting AI. Leading with it. It's the difference between letting the technology drive your decisions and using it as an amplifier for human judgment.

Nova: : That's a powerful reframe. So today we're unpacking the playbook of Leading with AI — the frameworks, the skills, and the practical habits that separate leaders who thrive from those who get left behind. Let's get into it.

Nova: Let's start with the centerpiece of Joel's philosophy: the AI Leadership Triad. When most people think about leading in the AI era, they imagine a long checklist — learn this tool, master that platform, understand large language models, get certified in prompt engineering. Joel argues that's exactly backwards.

Nova: : So he simplifies it? Down to three things?

Nova: Three specific human skills that actually become more valuable as AI advances. Not more obsolete. Creativity, Adaptation, and Innovation. And here's what's fascinating — they don't operate independently. They feed each other. Creativity without adaptation equals constant pivots with no direction. Adaptation without innovation equals busy work. Innovation without creativity equals what he calls innovation theater — adopting the latest AI tool just because everyone else is.

Nova: : Okay, break each one down for me. Let's start with creativity. I assume he doesn't mean watercolor painting.

Nova: Definitely not. Joel defines creativity as the ability to make connections AI doesn't see, ask questions AI doesn't know to ask, and solve problems when resources don't match ambitions. He brought in Anjeanette Carter, a seven-figure agency owner, to illustrate this. She'd built a successful YouTube channel until Google demonetized it overnight. Her income vanished. Her creative breakthrough wasn't a clever new video format. It was realizing she should never build her entire business on someone else's platform. That one insight led to her agency model. Creativity, in this framework, is treating failure as information rather than identity.

Nova: : That's not the kind of creativity people usually talk about. It's more like strategic clarity under pressure. What about adaptation?

Nova: Adaptation is the skill Joel considers most critical and most underestimated. It's about maintaining mission clarity while evolving your methods. Not changing direction every time a new AI model drops, but operating from the assumption that there's always a better way to do what you're currently doing. The reactive leader hears that Goldman Sachs projects up to 50% of jobs could be automated by 2045 and panics. The adaptive leader treats that as strategic information and starts evolving now.

Nova: : And innovation? I feel like that word gets thrown around so much it's almost lost meaning.

Nova: Joel draws a sharp line between real innovation and innovation theater. Real innovation might look boring — like automating expense reports so your staff can focus on strategy. But it compounds over time because it actually makes you better at your core work. He tells the story of a church leader who used AI to build a system matching volunteers with opportunities. Not flashy. But it reduced his administrative time by 40% and doubled volunteer engagement. That's real innovation. The question he wants leaders to ask is simple: does this make us better at our core work?

Nova: : And I love the diagnostic he offers. You ask yourself: when's the last time you read something completely outside your field? If you're only reading business books and AI articles, your creativity is starving. Do you believe there's always a better way, or are you defending the status quo? And did your last improvement actually improve your core work, or just look innovative? Most leaders, he says, are missing at least two of the three.

Nova: Here's where things get really practical. Joel noticed something troubling across organizations implementing AI. Companies would invest heavily in training their teams on ChatGPT, prompt engineering, and tool integration. Productivity metrics would go up. Everyone felt good. And then something would break.

Nova: : Like what kind of break?

Nova: A marketing team publishes AI-generated content with completely fabricated statistics. A hiring manager relies on an AI screening tool that systematically downgrades qualified candidates from certain demographics. A customer service chatbot confidently gives wrong information that creates legal liability. That last one actually happened. Air Canada's chatbot gave a customer wrong information about bereavement fares. The airline tried to argue the bot was a separate legal entity responsible for its own actions. The tribunal disagreed and forced them to honor the bot's promise.

Nova: : That's a perfect case study in why you can't just hand over decision-making to the machines. So what's Joel's solution?

Nova: He partnered with Sam Illingworth, a professor in Edinburgh who founded the Slow AI publication. Together they developed a framework for critical AI literacy. The key distinction is between functional literacy — knowing which buttons to press — and critical literacy — the ability to interrogate the system, its outputs, and its implications.

Nova: : So functional literacy is knowing how to drive the car. Critical literacy is recognizing when the GPS is confidently directing you off a cliff.

Nova: That's exactly the analogy Sam uses. And they've built a three-part evaluation framework for leaders. First is the Provenance Check: what data was this model trained on, and crucially, what data is missing? If you're using an AI sales coach, was it trained on enterprise B2B sales calls or used-car dealership transcripts? That matters enormously.

Nova: : I never even thought to ask that question.

Nova: Most people don't. Second is the Power Dynamics Check: if we implement this, whose job gets easier, whose gets harder, and who gets displaced? Automating customer service might save money, but if it frustrates your highest-value clients and empowers spammers, the net strategic value is negative. And third is the Fragility Check: when this AI makes a mistake — not if, when — what's the worst-case scenario, and do we have a human in the loop to catch it?

Nova: : Those three questions alone could prevent so many disasters. What's the practical tool they recommend?

Nova: They suggest running your AI-generated content back through AI with a specific prompt that forces critique. You ask the AI to act as a skeptical risk analyst and identify unstated assumptions, potential bias, and claims that require human verification. It's like building an institutional BS detector. And they have this memorable rule called the Billboard Test: never type anything into an AI, even in incognito mode, that would ruin your life if it ended up on a billboard.

Nova: : That's going to stick with me. But it also raises a deeper point. Joel says the leaders who win in the next decade won't be the ones who adopted AI fastest. They'll be the ones who adopted it smartest. Critical literacy is the foundation of smart adoption.

Nova: So we've covered the mindset, the framework, and the critical thinking skills. But Joel is also deeply practical. He's identified five specific habits that separate leaders who compound their AI advantage from those who stall.

Nova: : I love that word — compound. It suggests small, repeatable actions that build over time rather than one big transformation.

Nova: Exactly right. And that's the whole premise. The tools all eventually look the same, he says. The advantage is the habits the tools enable. Habit number one: test early and often. Most people use about 10% of AI's capability, and the gap isn't about intelligence. It's about reps. The leaders who win are in the sandbox every day, running prompts, tweaking, running again. The cost of testing is effectively zero. The cost of not testing is watching someone less experienced ship faster than you.

Nova: : So stop reading about AI and start using it on real problems. Got it. What's habit two?

Nova: Habit two is one of my favorites. He calls it building small things. Every time you hit a hurdle, your default question should be: can I use AI to solve this, not just once but the next ten times? He tells the story of a coaching client whose marketing team was burning hours every week repurposing one article into platform-specific posts for LinkedIn, Twitter, Instagram. Different post, same chore, every Monday. Joel built them a custom content repurposer. A few days of focused work, and the team got hours back every single week.

Nova: : And the punchline he offers is pretty striking — his seven-year-old built a working app in twelve minutes once she figured out how to talk to the tool. The excuse of I can't build this is just gone.

Nova: Habit three: keep your AI context current. Most serious AI users eventually set up a system prompt, a context document that tells the model who they are, what they're building, their tone and preferences. But then they leave it untouched for two years. That's like promoting someone and never updating their job description. Joel rewrites his context every quarter. What he's working on now, what he's moved past, what his voice sounds like this quarter. The model gets sharper because the picture is current.

Nova: : I've definitely been guilty of that one. What about habit four?

Nova: Push past the first answer. If you take whatever AI gives you on the first try and run with it, you're using it as a search engine. The first answer is the model's average response. The third or fourth answer, after you've pushed back, asked for counterarguments, and drilled deeper — that's where AI becomes a genuine thinking partner. Joel says if your AI never disagrees with you, you're using it wrong.

Nova: : And the fifth habit?

Nova: This one is surprisingly powerful and almost nobody does it. Twice a year, Joel opens a conversation and asks an AI model to interview him. Not a quick survey — twenty to thirty deep questions about his business, his voice, his values, what he's wrestling with. He saves the output and repeats it six months later. The comparison across cycles reveals how his thinking has evolved. Questions the model asks sometimes turn out to be the questions he should have been asking himself all along.

Nova: : That's brilliant. It's like having an external, patient mirror that catches the blind spots you can't see in yourself. He even provides the exact prompt so anyone can try it tomorrow.

Nova: There's one more layer to this. In a guest feature for Millennial Masters, Joel outlined six specific leadership skills that map to the AI era. They extend beyond the Triad and give leaders a complete picture of what they need to develop.

Nova: : Walk me through them.

Nova: Skill one is emotional intelligence. AI can tell you productivity is down 15%, but it can't tell you it's because your team feels like they're being replaced rather than empowered. Joel recommends what he calls emotional data literacy — learning to interpret the human signals AI misses, and creating psychological safety around AI adoption. He even provides a prompt to help leaders design an AI Impact Emotional Check-in for one-on-one meetings.

Nova: : That's so important. You can't just roll out AI tools and ignore how people feel about them.

Nova: Skill two is ethical AI judgment. AI decisions happen at machine speed, but ethical implications unfold at human timescales. The pressure to move fast can override the patience needed for ethical consideration. Joel recommends establishing ethical frameworks before you need them, mapping stakeholder impact before implementation, and creating bias auditing protocols.

Nova: : And skill three?

Nova: Adaptive change management. Traditional change management assumes you can plan, execute, and measure in linear stages. AI evolution makes that approach obsolete. Instead, he recommends iterative implementation — small cycles with constant feedback loops — and helping teams develop comfort with ongoing uncertainty rather than waiting for stable AI solutions.

Nova: : That's a big mindset shift for most organizations.

Nova: Skill four is creative problem-solving. As AI handles routine analysis, leaders must focus on problems involving ambiguity, conflicting values, and novel situations. The quality of AI output depends heavily on the quality of the questions you ask. Joel talks about cross-pollination thinking — connecting insights across industries in ways AI pattern recognition might miss.

Nova: : So it circles back to creativity again.

Nova: Exactly. Skill five is authentic communication. In an era of AI-generated content and deep fakes, authentic human communication becomes both more valuable and harder to achieve. He advocates radical transparency — being explicit when you're using AI assistance in communications, and grounding everything in clear human values.

Nova: : And the last one?

Nova: Systems thinking. Most leaders view AI as individual tools rather than as part of complex systems that include humans, processes, culture, and external stakeholders. Joel emphasizes feedback loop design — creating systems where human insights improve AI performance and AI insights enhance human decision-making. He calls it human-in-the-loop architecture.

Nova: : All six of these skills share a common thread, don't they? They're not about mastering technology. They're about doubling down on what makes us human.

Nova: Let's pull all of this together. Joel Salinas Frencia's Leading with AI philosophy isn't really about AI at all. It's about leadership. The AI is just the forcing function — the catalyst that's making it impossible to coast on old habits. His core argument is that the leaders who thrive aren't the ones learning the most AI tools. They're the ones developing specifically human skills that become more valuable as AI handles everything predictable.

Nova: : So what should a listener actually do after hearing all this?

Nova: Joel would say start with self-awareness. Take the AI Leadership Triad — creativity, adaptation, innovation — and ask yourself honestly: where are you strongest and where are you weakest? Most leaders are missing at least two of the three. Then pick one of the five compounding habits and commit to it for thirty days. Maybe it's the self-interview. Maybe it's pushing past the first answer. Maybe it's building one small thing that solves a recurring problem.

Nova: : And don't forget the critical literacy framework. The next time your team presents an AI-generated strategy, run it through the Provenance Check, the Power Dynamics Check, and the Fragility Check. That alone could save you from becoming the next Air Canada case study.

Nova: Here's the line that stays with me. Joel says: you don't drift into AI-era leadership success. Some people have these skills innately. Most don't. But all of us can develop them. And we're still in time.

Nova: : The leaders who win in the next decade won't be the ones who adopted AI fastest. They'll be the ones who adopted it smartest — leading with clarity, adapting with purpose, and creating value that lasts.

Nova: This is Aibrary. Congratulations on your growth!