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AI Learning Speed for Executives: The Neuroscience of Why Some Leaders Master AI Fast | Executive AI Training

• Sahar the AI Whisperer | Neuroscience Expert in AI and Leadership • Season 2 • Episode 15

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Join Sahar, The AI Whisperer, and her skeptical executive husband Joe in this episode of AI Café Conversations as they explore the neuroscience behind AI learning speed for executives. Discover why some executive brains adapt to AI quickly while others struggle, using brain science insights that require no technical knowledge.

Through real workplace examples and conversational dialogue, learn how cognitive flexibility, neural plasticity, and executive brain architecture affect AI adoption speed. Sahar explains the neuroscience of learning differences while Joe represents every skeptical leader wondering "Why am I so slow at this AI stuff?"

Perfect for executives, HR professionals, and business coaches seeking to understand AI learning challenges in leadership development. This episode provides practical, brain-based strategies for accelerating AI adoption without overwhelming executive teams.

Key topics include executive brain patterns, AI learning anxiety, neural rewiring for technology adoption, and organizational strategies for different learning speeds. All insights are presented in accessible, non-technical language designed for busy executives.

Ideal for leaders implementing AI coaching tools for executives, those struggling with AI integration, and anyone interested in the neuroscience of executive decision-making and technology adoption.

Subscribe to AI Café Conversations for weekly neuroscience insights that help executives master AI while maintaining human-centered leadership. No tech background required - just curiosity about how your brain works with AI.

This episode is designed for executives, HR professionals, and coaches who see the urgency of AI adoption but want it to align with human connection, not replace it.

Email me at sahar@saharconsulting.com with questions or topic suggestions for future episodes.

 My book "The Coach's Brain Meets AI" is available on Amazon, and I'll send extra guides if you email me after purchasing. Follow me on LinkedIn (Sahar Andrade) and Instagram (Sahar the Reinvent Coach). 

Subscribe now to start transforming your leadership with Human-Centered AI!

If you have any questions Email me at sahar@saharconsulting.com

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Connect with me on IG: @saharthereinventcoach

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Speaker 1:

Hello, hello, hello and welcome back to AI Cafe Conversation on this beautiful Wednesday morning. I am Sahar, your AI Whisperer, and I'm here for those who have been watching their colleagues navigate AI with very different results. Let me tell you, every single day I'm seeing different organizations, different leaders, different attitudes, different results, different thoughts, different processes, thoughts, different processes, and it's amazing because all of us are sometimes looking at AI from different point of view, from different approaches, because, remember, ai is still it's in infancy and we are still basically scratching the surface of what we can do. But that's why I'm really marrying AI with neuroscience, because I want always to base it on facts, not on maybe or maybe, an assumption or a perception. I really want to always kind of base it on neuroscience because, maybe, because it makes sense to me. So today I'm going to start this by saying that one of my clients told me that it was again like I said, everybody looks at AI from different points of view, and my client, like I was saying, told me it's fascinating but frustrating at the same time. Their business partner picked up ChatGPT in two weeks and now uses it for everything I do too, I have to confess. Anyhow, meanwhile, their cfo has been learning it for six months six months and still treats it like a fancy search engine. And, by the way, this is probably 80 percent of the people that are using um either chad, gpt or um or cloud or perplexity or meta whatever your heart desire as a platform for ai. They're using it as a sophisticated google search and this is so not what it's designed for. Okay, so we all use the same AI tool and we could have the same training, but completely different outcomes.

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And does that sound familiar to my executive listeners? Why? Because it's not about intelligence. For example, the CFO in that company is brilliant. He's a Harvard graduate, mba, cpa and all the abbreviations that you want at the end of the name, and he runs a complex financial model. But put him in front of ai and he's like a deer in a headlight, and by again, he's not the only one, so there is no shame in that. I see it every single day.

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This is one of the most common questions I get from executives why do some of my people get AI immediately, while others struggle for months? And the answer here is, again, pure neuroscience. So it's not about being tech savvy and it's not about being young, a Z generation or an X generation or a Y generation? All the alphabet letters, right? It's not about that. Those factors are important, especially for the younger generation that grew up basically as native digital, that internet and all that is part of of their dna. It's like an appendix to them, but they are quite factors, but they're not the primary drivers, though.

Speaker 1:

Your brain's learning architecture, how your neural pathways are structures from decades of experience, determines how quickly you adapt for ai. So some brains are just better at learning AI. Some brains are structured in ways that make AI learning feel natural. Others have neural patterns that create resistance, and that's what we see a lot, especially within the teams. But here is the key Both can be changed and, like you do and I think again I'm going to keep bringing that up whenever we are introducing ai and ai adaptation or integration, we need to treat it as a change management where 80 percent factors is human and only 20 percent processes, and not go with the wrong assumptions of change management that 80 percent processes and 20 human and that's when it fails, okay. So both mentalities can actually be changed.

Speaker 1:

Today's we are diving into the neuroscience of AI learning speed and how to accelerate it. So, for example, something that I observed in executives that pick up AI quickly. They seem kind of playful with it. They go with an open mind. It's like they're not afraid to experiment. They will try weird prompts, try different approaches, laugh when it gives them weird results. And these are like actually we see it, and they are the perfect observations that we have been seeing between the different executives, because those executives have what neuroscience call high cognitive flexibility. Their brains easily switch between different mental frameworks.

Speaker 1:

So what does actually that mean? Their prefrontal cortex, again in the front of the brain, like around our forehead, or the brain's executive center, has strong connections between creative and analytical regions. They can shift from structured thinking to experimental thinking without stress. So the question is are they more naturally adaptable? The brain architecture supports what we call divergent, convergent thinking cycles. They can brainstorm widely with AI, then organize the results logically. This is how the brain works. It's like having mental gears that shift smoothly, like if you ever drove a stick shift car. That's how I started driving. On a stick shift car you can downshift or upshift, you know, depending on how fast, how slow and how much control you want to have on driving a stick shift car. So why do some executives have this and others don't? It usually comes from career experiences that require constant adaptation Entrepreneurs, consultants, people who have worked across industries.

Speaker 1:

Their brains build flexibility neural pathways naturally in their brain Remember it's neuroplasticity Neurons that fire together, work together. They created pathways that connect together by repetition. And that's what we say when you do something for at least six weeks, like habits, they become automatic. Some of the people that are executive and using the AI, I can see them that through their career they moved from one level to the other or even through different industries. Their brain learned that changing approaches leads to better outcomes and when they encounter AI, those same neural pathways activate.

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Experimentation feels familiar, not threatening. So people sometimes ask me weird questions like is it a personality thing? Are extroverts better than AI, which I find really interesting questions. When it comes to AI, because again, it's a kind of intelligence, it's less about extroversion and more about what psychologists call openness to experience. They're open to experience. Some introverts are incredibly open to new ideas and learn AI fast. They just don't show it outside. Okay, there are even people that are introvert extrovert. You know there is a lot of variations, variations of between that. So it's not about being open or outgoing. It's not really about that, but openness correlates with neuroplasticity how easily your brain forms new connections.

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High openness, executive CAI is as interesting, not intimidating. It depends how you look at it, and that's what I always say. When we approach something new through our curiosity, what it does, it opens the door to our problem-solving center in the brain. Because two things cannot go at the same time. I cannot be fearful of something and curious at the same time. Okay, one of them will take over. So if I have fear, I have cortisol in my brain, I'm stressed, I cannot think straight and I cannot learn anything. But when I approach it for like, hmm, let's see what, where that can go, do I win? Do they win? If we come from a curiosity point of view, right away, analytical thinking and problem solving centers will open. So it becomes more, like I said, interesting and not intimidating.

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I don't know if you can measure it, but there are indicators. For example, fast AI learners typically ask what if questions? They enjoy puzzles, they have hobbies outside work and view failures just as data rather than defeats. It's like when I fail into something, I laugh and I'm like, haha, now I know what not to do okay, and I would avoid that next time I say it's like oh my god, I I failed, I'm not good, like I'm not worthy, blah, blah, blah, I don't do that, okay. It's all about how we look at failures.

Speaker 1:

So let's talk about executives who struggle with AI. What patterns do we see in them? They seem careful, almost paralyzed. They want to understand exactly how it works before they will use it. They have their conditions, like they want to be in control, right? They ask lots and lots of questions about reliability and accuracy. I don't blame them, but still classic science of what we call analytical dominant brain architecture. These executives have incredibly strong systematic thinking pathways, but they don't know weaker exploratory connections. They are too logical for AI. Not really, they're not too logical, but their brains are wired for sequential, predictable processes. Again, it's about control.

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Ai learning requires iterative, experimental processes that feel chaotic to systematic thinkers. They need to understand the methodology before trusting any tool. Their brain excel at structured analysis but struggles with ambiguous inputs. Ai responses vary. Sometimes they even hallucinate Okay, not perfect and they require interpretation. This triggers their brain error detection systems. Remember we never take everything AI takes up for granted. We are the human brain here we need to look at it, think about it, think about our experience, the pros and cons, and maybe add and push back, and this is the only way we can get accurate results that we want to have.

Speaker 1:

So sometimes the strength is the weakness actually, of the person that just wants to see whatever AI is doing only through the error detection system. Their analytical rigor, which makes them brilliant at financial modeling, for example, creates resistance to AI's probable nature. Their brain interprets inconsistency as being unreliable. I'm not saying this is like wrong way of thinking or this is being stupid, but because these executives run very complex organizations. They are extremely, extremely successful, but their cognitive architecture is perfectly designed for traditional executive tasks strategic planning, risk analysis, systematic decision making.

Speaker 1:

Ai just requires different neural pathways. And what makes them struggle? Several factors perfectionist neural patterns that resist trial and error learning, risk aversion circuits that interpret AI uncertainty as danger, and expertise bias that makes new learning feel threatening to identity. And you might tell me what? Expertise bias? What is that? When you are an expert in traditional methods, your brain resists tools that might reveal knowledge gaps. Remember control Learning AI means admitting there are better ways to do things you have mastered, so it can be, or can seem threatening to someone who built their career on specific expertise, because their brain's identity protection system fights against adoption tools that might take their hard-earned knowledge. That can make them obsolete. But here is the encouraging news Neuroplasticity means slow learners can become fast learners with the right approach, which means that we can actually rewire a brain for AI learning. The brain builds new neural pathways throughout life. It just requires intentional practice that works with your existing architecture instead of against it. Work with it, not against it. Less resistance. And how does that work practically For systematic thinkers like the CFO I was discussing in the beginning of the podcast?

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Start with structured AI experiments Instead of play around with chat, gpt. Give them specific prompts to test with measurable outcomes, and that can help make AI learning feel like a controlled experiment. Where they feel still they have control, their analytical brain needs frameworks. So create AI protocols that they can follow systemically. Once they see consistent patterns, their trust circuits will activate. And you might ask but what about the perfectionist executive who hate making mistakes? We can reframe mistakes as data collection Instead of I got a bad AI response. Maybe try to start. Make them think I collected useful information about prompt effectiveness. Change the language to change the brain response. Remember words have power. Okay, change your words, you change your word. Languages shape neural pathways. Experiment feels less threatening than trial and errors. Iteration sounds more professional than playing around than playing around. So there are something specific exercises to build AI learning speed so we can start with what we call micro experiments five minutes AI tasks with clear success metrics. This builds confidence pathways without triggering overwhelmed circuits like baby steps for the brain. Perfect analogy is that each successful micro experiment releases dopamine, reinforcing AI engagement, and over time these small wins build larger confidence neural networks.

Speaker 1:

You might ask how long does rewiring take? It varies actually by individual, but neuroplasticity research suggests that significant pathway changes in 30 to 60 days with consistent practice. The key is daily engagement, even if brief. That's basically creating new habits. Remember, and if you add an extra layer on the consistent practice and have triggers like put yourself a stick on notes on uh on your desk or have a screensaver or put an alarm on your phone at certain times to remind you of something like quick proko, like a trigger that will let you go and do that five minute or micro experiment. So 15 minutes daily beats three hours weekly for neural pathway development. Repetition is better than duration. Consistency builds stronger connection than intensity.

Speaker 1:

So let's get practical, okay. How can executives speed up AI adoption across their teams, especially when they have a mixed bag of facts, adopters and holdouts? Number one assess your team's learning architectures. Don't use one-size-fits-all training, which basically everybody has been doing. That's wrong. Match AI introduction methods to individual neural preferences. What does that mean? Analytical thinkers need structured framework and measurable outcomes. Creative thinkers need open-ended exploration time. Risk aversion personalities need safety nets and supervision. Different approaches for different brain types. Your systematic, for example, cfo, like we discussed in the beginning. They need AI standard operating procedures. The creative marketing director needs AI playground time with no specific objectives, hope it makes sense and how to build confidence in slow adopter.

Speaker 1:

Create AI wins quickly. Give them simple, low-risk tasks where AI obviously saves time, like email summarization, data organization, routine analysis, reading report, excel sheets. Routine analysis, reading report, excel sheets. So, building success before complexity. Each small success releases dopamine and builds positive AI associations. Start with tasks that complement their existing strength, not challenge them, and I know that some executives have some fear factor. They worry that AI will replace their jobs. We need to address this directly with neuroscience.

Speaker 1:

Explain or explaining that AI augments executive capabilities like strategic thinking, relationship building, creative problem solving that AI can't replicate. This is human skills that AI cannot replicate. That no matter what executive will have those very unique skills. So position AI as a power tool, not competitor. We are complemented by AI. We collaborate with AI and we don't compete with AI. Frame it as AI helps you do more of what only humans can do by handling what machines do well. This reduces threat response and activate curiosity circuits. So some of the specific organization strategies that I use is I use peer learning. Accelerates adoption.

Speaker 1:

Pair fast learners with slow learners, not as teachers, but as learning partners. Remember, like mentoring and reverse mentoring, social learning activates different neural pathways than individual studies. Body systems for AI learning anyone but structured body systems give pairs specific challenges to solve together. Collaboration reduces individual performance, anxiety while building collective capability. And how to measure progress? And how do we know if the rewiring is working? We track behavioral indicators frequency of AI tool usage, complexity of tasks, attempted comfort with imperfect output and willingness to experiment with new prompts. Practical metrics instead of just surveys, because the neural pathway changes show up in behavior before people consciously recognize them. Usage patterns reveal brain rewiring better than self-reporting. So let's create a simple protocol executives can use to speed up their own AI learning. So let me give you something that can actually be implemented.

Speaker 1:

Week one and two daily 10 minutes structured experiments same ai tool, same type of task, different approaches. Build familiarity, neural pathways, consistency and repetition first. Week three and four introduce complexity gradually. Add one new variable per week. Different prompts, different tasks or different tools. Build flexibility circuits slowly. Do not overwhelm the system.

Speaker 1:

Week five and six integration challenges Use AI for actual work problems, not practice exercises. This builds confidence and relevance neural connections. So now we move from practice to real application. Week seven and eight teaching others Remember to real application. Week seven and eight teaching others remember the best way to learn something is to teach it. Explaining ai approaches to colleagues activates deeper understanding pathways and reinforce learning. And the final step basically, like I just explained, is becoming a teacher yourself as an executive. Teaching forces your brain to organize AI knowledge into transferable patterns. It's the ultimate neural consolidation exercise.

Speaker 1:

So let me ask you this, guys what was your takeaway for executive? Wondering why AI learning speeds vary so much? And the answer is simple it's not about intelligence or age. It's about brain architecture built from career experiences. Fast learners have flexible neural pathways. Slow learners have systematic pathways. Nothing, no one, is better than the other. Okay, both can be changed with the right approach. Executive, remember your learning speed is not fixed. Neuroplasticity means you can build ai fluency at any career stage with intentional practice. So don't judge everybody because they're being systematic or about everything right. The systematic brain is actually an asset, just needs ai compatible frameworks. Next week we are diving into ai productivity paradox why more ai tools can feel like less control.

Speaker 1:

Subscribe if you want to understand why some brains love AI and others fight. Show me some love Like. Share this with someone else. Subscribe to our podcast so you don't miss any of the new episodes. This is Sahar, your AI whisperer, signing off from AI Cafe Conversations. Your brain is more adaptable than you think. Any questions, questions, any comments? Please email me at sahar at sahar consultingcom Website, sahar consultingcom. My book the coaches brain meat AI is still On top new releases on Amazon and is doing really well, is on the top 30 of three different categories and I'm very proud of it it and I hope you like it. I hope you get to read it and tell me what you think about it, but for now I'm over and out. See you next time. One, two, three, four.