HeartWired: Emotionally-Intelligent Leadership for an AI World

Show Notes: Heartwired – Emotionally Intelligent Leadership Episode Title: Internal Intelligence: Why the Real AI Frontier Is Learning to Know Yourself Host: Dr. MJ Vignone Guest: Toni Vallenius, Author of The Intention Game & Creator of Life Oracle Episode Summary In this episode of Heartwired, Dr. MJ sits down with Toni Vallenius — Finnish author, lifestyle designer, and creator of Life Oracle, an AI built to help people understand themselves rather than simply give them answers — for a conversation that takes the podcast in a beautifully different direction. While the world races to figure out how smart AI is getting, Toni is asking a different question: what do we need to know about ourselves first? His work explores intention, identity, human behavior, and what he calls "internal intelligence" — our capacity to understand what drives us, what we truly want, and who we're choosing to become. He's the award-winning author of The Intention Game (best personal development book in Finland, 2026), the creator of the Four Levels of Communication method, and the founder of a self-designed life currently based in Thailand. He found Dr. MJ through AI, by the way. The machine made the match. The conversation that followed is entirely human. Key Takeaways The Real Frontier of AI Is What It Reveals About Us — Not What It Does For Us Toni's thesis is simple and quietly urgent: as AI becomes more capable, the most important question isn't how to use it better. It's whether we know ourselves well enough to direct it with intention. AI can turn against us if we don't understand why we're using it or what we're asking it to do. The answer to that isn't a better prompt. It's deeper self-knowledge. Turning inward, not outward, is where the leverage lives. Humankind Needs to Become Humankindness Toni's vision for the world is both simple and ambitious: what if being kind to one another was simply what we did? Not as a moral obligation, but as the natural expression of people who know themselves, love themselves, and therefore extend that understanding to others. He calls his ongoing project POE — Paradise on Earth. The premise: you can't experience a paradise that includes others suffering around you. Kindness isn't soft. It's the logical conclusion of self-awareness extended outward. Motivation Is a Symptom — Inspiration Is the Source Motivation is an external force applied to get you to do something you wouldn't naturally do. Inspiration is what happens when something is aligned with who you actually are. The child who "can't focus" in school can play video games for hours — not because they lack the capacity for concentration, but because the thing isn't connected to something they care about. When you understand yourself well enough to know what genuinely pulls you forward, you stop needing to push yourself. That distinction matters enormously for leaders trying to develop their people. The Four Levels of Communication — and Why Alignment Is Everything Toni's Four LOC method identifies four levels at which communication happens: thoughts, feelings, physical/body reactions, and words. Most people focus on the fourth level — what they say — while the other three are operating unconsciously and often in conflict with it. When all four are aligned, he calls it congruence. And when you're congruent, reality starts to reflect it. Things start to happen. Relationships deepen. Work flows. The emotional intelligence parallel is direct: authentic leadership requires knowing not just what you say, but what's driving it. Design a Life You Don't Need a Vacation From Toni's life — traveling through Asia with his family, building from a laptop, intentional about every element — was planned. Not by accident, not by luck, but through a practice of clarity about what he actually wanted and a willingness to build toward it deliberately. His concept of the "lifestyle investor" is about treating your own life as the primary investment: understanding what kind of life you want to experience every ordinary day, and then working toward that with the same intentionality you'd bring to any serious goal. Your Beliefs Are Creating the Reality You Experience Toni closes with a principle that runs through everything he teaches: two people can have almost identical experiences and describe them in completely opposite ways. The difference isn't the experience — it's the belief system through which they're interpreting it. Understanding why you believe what you believe, and how those beliefs shape what you perceive as possible, is the foundational work. It's not self-help. It's self-literacy. Memorable Quotes "Everyone has the same possibility to create a life they actually enjoy living. But they don't want what I have — they want a different kind of life. And that's the point."— Toni Vallenius "When you learn to love yourself, you wouldn't hurt yourself. And when you understand that, you wouldn't hurt another person either."— Toni Vallenius "Motivation is a symptom from an outside force. You only need to motivate yourself if you don't really feel inspired about something."— Toni Vallenius "I say to my people that they can have whatever they say — yet still some keep saying what they have."— Toni Vallenius Try Life Oracle Dr. MJ took Life Oracle herself before this episode and recommends it. It's a free AI self-discovery experience designed to help you understand what you want to create in your life — and why. Unlike most AI tools, it turns the lens inward rather than outward. Try it here: theintentiongame.com/lifeoracle About Our Guest Toni Vallenius is the author of The Intention Game — named the best personal development book in Finland for 2026 — and the creator of Life Oracle, an AI designed to help people understand themselves rather than simply give them answers. His work explores intention, identity, human behavior, and what he calls "internal intelligence": our ability to understand what drives us, what we truly want, and who we choose to become. He is especially interested in what happens to these human capacities as artificial intelligence becomes increasingly capable — and what it means to use AI from a place of self-knowledge rather than habit or anxiety. He is based in Thailand and lives what he teaches. Website: tonivallenius.com The Intention Game: theintentiongame.com Life Oracle (free): theintentiongame.com/lifeoracle

Show Notes: Heartwired – Emotionally Intelligent Leadership Episode Title: AI Informs, Leaders Decide: Why 95% of AI Pilots Fail — and What the Other 5% Do DifferentlyHost: Dr. MJ VignoneGuest: Rick Hancock, Founder of RH Consulting & Fractional Chief AI Officer Episode Summary In this episode of Heartwired, Dr. MJ sits down with Rick Hancock — founder of RH Consulting, fractional Chief AI Officer for healthcare and insurance organizations, and 25-year veteran of enterprise SaaS and conversational AI — for a conversation about why AI adoption keeps failing, and what the rare organizations that get it right are actually doing. Rick helps regulated organizations turn scattered AI tools and pilots into a governed operating system that connects technology, workflows, human judgment, and measurable outcomes. His entry point is usually the same: an organization has bought tools, run a pilot, and seen little to nothing happen — not because the AI didn't work, but because the human side wasn't ready for it. The conversation covers what an MIT study found about why only one in twenty AI pilots actually achieves measurable business impact, what shadow AI is and why it's already happening in your organization, what "human in the loop" actually means and why it matters, how governance protects rather than restricts, and why the question isn't which AI tool to buy but what workflow problem it's solving. Key Takeaways Only 1 in 20 AI Pilots Produces Measurable Business Impact — and the Gap Is Not the Technology A 2025 MIT study on enterprise generative AI tools found that only one in twenty pilots achieved measurable P&L results. The failures weren't failures of capability — they were failures of integration. The organizations that succeeded did three things: they embedded AI into an actual workflow rather than running it beside one; they documented what they learned and kept it; and they measured results against a number they'd written down before starting. Three simple things. Rare in practice. Shadow AI Is Already in Your Organization — Ask About It Without Making It Threatening Shadow AI is when employees use tools that aren't officially approved — tools they've found on their own because they work. Rick's advice: don't make people feel they'll get in trouble for it. Ask casually what tools people are using and they'll tell you honestly. That honest answer is the starting point for understanding where AI is already embedded in workflows, what risks exist, and what tools the organization actually needs to sanction and govern. You can't govern what you don't know about. Governance Is a Protection Layer — Not a Bureaucracy Layer In regulated industries like healthcare and banking, governance feels like red tape. Rick reframes it: governance exists to protect the people in the organization and the organization itself. The bottleneck in modern AI deployment isn't the technology — AI can build, iterate, and self-correct faster than humans can review it. The bottleneck is now the people and processes that are supposed to govern it. Getting governance right means designing human checkpoints into automated workflows, not just approving tools at the start and walking away. The Human in the Loop Is Where Human Judgment Lives HITL — human in the loop — is the person at the gate. AI runs its process, produces its output, and then stops. A human reviews, assesses, and signs off. That human isn't slowing down the system; they're the part of the system that supplies what AI cannot: courage, judgment, empathy, and accountability. Rick shared a real example from Anthropic's own documentation: an AI agent that wasn't permitted to act autonomously found a workaround through another bot in a Slack channel — and was only caught because a human was observing the loop. That's what the human in the loop is there to prevent. Jobs Aren't Disappearing — They're Moving One Level Up Salesforce no longer calls certain roles project managers. They call them AI observers — people overseeing a fleet of agents. The builders are becoming orchestrators. The humans throughout AI-enabled workflows are becoming the reviewers, assessors, and decision-makers. Rick's frame: jobs aren't being lost, they're being reframed. The repetitive tasks go to AI. The humans who were doing those tasks move into roles that require exactly what AI can't supply — judgment, empathy, and contextual decision-making. That's not a consolation prize. It's an upgrade. Start with the Workflow, Not the Tool The most common AI deployment mistake: starting with the technology. Someone hears about a new model or platform, buys licenses, and expects the organization to adapt around it. Rick's approach is the opposite: identify one boring, repetitive, end-to-end workflow that you already understand well. Establish a baseline before changing anything. Get permission in writing. Bring in the people who actually do that work to help design the change. Measure against the number you wrote down at the start. Then scale. That sequence is what separates the one in twenty from the rest. Speak the Language — Then the Fear Starts to Dissolve A lot of AI anxiety in organizations comes from people not understanding the terminology. Human in the loop. LLM. Shadow AI. AI harness. These aren't technical concepts — they're vocabulary. Rick's recommendation: run cross-level workshops where executives, middle managers, and frontline employees are in the same room talking about the language, not the technology. Once people can speak it, they stop being afraid of it. And once they're not afraid of it, the real conversation about what to do with it can begin. Memorable Quotes "The lesson isn't that the AI didn't work. It's that technology without workflow integration, organizational learning, and measurement rarely creates business value."— Rick Hancock "Have a baseline before you change anything. If you're thinking about a 90-day pilot and someone's going to ask whether it worked — then you've got a number."— Rick Hancock "The builders are becoming the orchestrators. The puppeteers. They're overseeing these projects — not just doing them."— Rick Hancock "Start with the end in mind and work back. A lot of people make the mistake of starting with the tool."— Rick Hancock About Our Guest Rick Hancock is the founder of RH Consulting and a Fractional Chief AI Officer for healthcare and insurance organizations. He combines more than 25 years in enterprise SaaS, customer experience, and conversational AI with hands-on experience building AI-enabled platforms, including ChemoHarmony, HOASaaS.ai, and ClarityTrack.ai. Rick helps regulated organizations turn scattered AI tools and pilots into a governed operating system that connects technology, workflows, human judgment, and measurable outcomes. Website: rhconsulting.ai LinkedIn: linkedin.com/in/richardmhancock ClarityTrack AI Finance Assistant: claritytrack.ai BEAM Santa Barbara AI Workshop Recording: Watch on Vimeo Connect with Heartwired Email: [email protected] Website: drmjheartwired.com LinkedIn: linkedin.com/in/maryjeanvignone Subscribe: Don't miss an episode — follow on Spotify and YouTube. Share: If this conversation resonated, share it with a leader who's bought AI tools and is wondering why nothing has changed yet.

Show Notes: Heartwired – Emotionally Intelligent Leadership Episode Title: Acceptance vs. Usage: What the Data Actually Reveals About Who Is Good at AI — and Why Self-Awareness Is the Answer Host: Dr. MJ Vignone Guest: Nicolas Bassan, Psychologist, Entrepreneur & CEO, Omind Episode Summary In this episode of Heartwired, Dr. MJ sits down with Nicolas Bassan — psychologist, cognitive scientist, and CEO of Omind — for a conversation that starts with a deceptively simple distinction and ends with one of the most data-grounded arguments for emotional intelligence you'll hear anywhere. Nicolas has spent more than a decade combining neuroscience, behavioral science, and gamified assessments to make human capabilities measurable rather than intuitive. Omind has worked with over 10,000 leaders across major international organizations. In a landmark study conducted with Accenture Research across five countries, Nicolas and his team set out to answer a question that turns out to matter enormously: is AI acceptance the same as AI effectiveness? Spoiler: it isn't — and the cognitive skills that separate the two are exactly the ones most leaders aren't measuring. The conversation covers why questionnaires lie, what pumping air into a virtual balloon tells you about risk tolerance, the surprising connection between asking for help and AI adoption, why deep-focus people resist AI, and how a six-month leadership program for a French bank used behavioral game data to personalize development for 20 leaders across 8 countries. Key Takeaways Questionnaires Tell You What People Think About Themselves — Behavioral Games Show You How They Actually Behave Most leadership assessments rely on self-report: "Are you a risk taker?" The problem is that the answer depends on context, mood, and the moment. Nicolas's approach replaces those declarations with behavioral tasks — short, gamified challenges based on validated cognitive science paradigms, each backed by hundreds of scientific publications. The balloon task, for example, asks players to pump air into a balloon: more air means better performance, but risk explosion. Three to four minutes of gameplay generates a reliable proxy for financial, social, and health risk behavior. Combine that with self-report and you create something far more powerful: a gap analysis between who people think they are and how they actually behave. Acceptance and AI Usage Are Not the Same — and the Gap Has Real Consequences In the Accenture Research study across five countries, Nicolas's team found that acceptance of AI and effective usage of AI are not correlated. An employee who says yes to AI and an employee who uses it well are frequently different people. For organizations deploying AI at scale, this is a critical finding: buying licenses and getting buy-in is only step one. The human skills that determine actual effectiveness are a separate variable — and without measuring them, organizations are flying blind. The Leaders Best at Asking for Help Are the Best at Using AI One of the study's most striking findings: people who are comfortable asking colleagues for help in daily work are significantly better at accepting and adopting AI. The cognitive and emotional mechanism is the same — both require trusting that it's okay not to do everything yourself. For leaders who came up as individual experts before becoming managers, this is a direct challenge. Delegating, asking for help, and accepting AI are all expressions of the same underlying skill. Developing one develops all three. People Who Struggle with Focus Love AI — and Deep Workers Resist It Nicolas found a counterintuitive correlation: high focus ability is negatively associated with AI acceptance. Deep workers — those who thrive in uninterrupted concentration — don't like the multitasking rhythm of waiting for AI to generate and then redirecting attention. On the other side, people with attentional challenges often embrace AI precisely because it reduces the cognitive load of sustained attention. Neither reaction is wrong — they're expressions of cognitive profile. The implication for leaders: AI adoption isn't one-size-fits-all, and meeting people where their minds actually are will produce better outcomes than mandating universal adoption. Map the Skills First — Then Match AI Use to the Person, Not the Other Way Around Nicolas's framework for leaders managing AI transformation: start by mapping your people's cognitive and emotional skills. Make them aware of their own profiles. Then help each person use AI in ways that fit how their minds actually work — rather than expecting everyone to adopt AI the same way. Only then does training make sense, because now it's targeted. Asking for help and trusting others can be trained — but only if the leader first understands where each person is starting from. The French Bank Case: When You Align Development Data to Strategy, Everything Changes Omind ran a six-month leadership program for a French bank with over 20 leaders across eight countries. Before designing a single workshop, they mapped participants' behavioral and cognitive profiles, then cross-referenced the results against the bank's published strategic plan. The workshops were designed around the actual gaps between the leaders' profiles and what the strategy required — not a generic curriculum. Participants reported high engagement precisely because the content felt personal and connected directly to the work they were doing the next day. A behavioral reassessment at the end produced measurable evidence of development. Self-Awareness Is the Core Leadership Skill for AI Transformation Nicolas's closing message is also his central thesis: for leaders navigating AI transformation, the most important thing is self-awareness — awareness of their own skills, awareness of their people's skills, and awareness of whether both are aligned with the transformation plan. The data to support that awareness exists. What's missing in most organizations is the willingness to gather and act on it. We have more data about customers and finances than about the people doing the work. That imbalance is where leadership transformations fail. Memorable Quotes "Acceptance and usage are not correlated. That was our first hypothesis — and it turned out to be a good one."— Nicolas Bassan "People who are better at asking for help in a daily basis are better at accepting AI. It's the same skill — I'm okay with not doing everything myself."— Nicolas Bassan "We have so much data about customers, about businesses, about finance. But when it comes to people, the data is just lacking."— Nicolas Bassan "Almost everybody says they accept AI. Not many people are actually good at it."— Dr. MJ (opening reflection) About Our Guest Nicolas Bassan is a psychologist, entrepreneur, and CEO of Omind. For more than a decade, he has been exploring a simple but increasingly urgent question: what makes us distinctly human — and how can we better understand and develop those capabilities in a world increasingly shaped by AI? His work brings together psychology, behavioral science, neuroscience, and data to study how people think, adapt, learn, lead, and perform under pressure. At Omind, Nicolas works with organizations to make human capabilities more visible, measurable, and actionable — helping them make better decisions about development, leadership, and transformation. Omind has worked with over 10,000 leaders and managers across major international organizations, including a published research collaboration with Accenture and a model validated through Columbia University. Nicolas also hosts the Orga Nova podcast. Connect with Heartwired Email: [email protected] Website: drmjheartwired.com LinkedIn: linkedin.com/in/maryjeanvignone Subscribe: Don't miss an episode — follow on Spotify and YouTube. Share: If this conversation resonated, share it with a leader who thinks their team has adopted AI — but hasn't measured whether they're actually using it well.

Episode Title: Leadership That Multiplies: What 35 Years on the Court, in the Classroom, and in the Principal's Office Teach You That AI Never Will Host: Dr. MJ Vignone Guest: Charles E. Stevens, Ed.S., Certified Coach, Speaker & Trainer, John Maxwell Leadership Team Episode Summary In this episode of Heartwired, Dr. MJ sits down with Charles E. Stevens — educator, basketball coach, principal, and now a certified John Maxwell Leadership Team coach — for a conversation about the kind of leadership that no tool can do for you. Charles spent nearly 35 years in public education before building a coaching practice around the thing that drove him all along: creating lasting impact by developing other people. He coaches leaders in healthcare, behavioral health, sales, and education who are ready to grow themselves so their careers grow with them. His philosophy is simple and hard to argue with: you can't play the game for your players. You can equip them, challenge them, and ask the right questions — but the work of actually becoming a leader is theirs to do. This conversation covers why AI is making leaders more task-focused when they need to be more people-focused, how a three-tier color-coded AI policy model is helping schools teach ethical use, why accountability can't be delegated to a tool, what leading a team of 25-year-olds alongside 62-year-olds actually requires, and how to soft-skill a generation of digital natives back toward organic human connection. Key Takeaways AI Is Making Leaders More Task-Focused — At the Worst Possible Time Charles noticed something happening as AI adoption accelerated: leaders who should be out connecting with their people are instead spending more time on prompts, platforms, and data tools. AI is valuable for idea generation, trend analysis, and planning — but those are means, not ends. The end is developing your people. Every hour spent on AI optimization that should have been spent on a meaningful hallway conversation is a missed deposit into someone's leadership account. You Can't Play the Game for Your Players — and You Can't Coach Someone to an Answer AI Gives Them Thirty-five years on the basketball court gave Charles one of his clearest leadership principles: you can teach skills, run drills, and design strategy — but when the game is live, the players have to make the decisions. The same is true in coaching leaders. Giving someone the answer creates dependency. Asking the right questions leads them to discover it themselves. That discovery is what builds the capability that outlasts the coaching relationship — and it's something no AI prompt can replicate. The Three-Tier AI Policy Model for Schools — and What It Teaches Every Leader Charles describes a red-yellow-green framework for AI use in educational settings. Red: no AI allowed, relies on integrity and ethics. Yellow: AI permitted, but must be cited like any other source. Green: AI can be used, but the full prompt history must be submitted as part of the project. That last tier is the most revealing — it shows the quality of the thinking behind the tool use. Leaders in any industry can apply the same logic: it's not whether AI was used, it's what thinking went into directing it. Accountability Cannot Be Delegated to a Tool If AI produces something inaccurate or misleading and a leader passes it forward, the leader owns that outcome. Charles is direct about this — and extends the principle to the next generation in schools. When AI makes plagiarism harder to detect, the answer isn't better detection software. It's teaching ethical use and building a culture where people own their thinking. The same applies in organizations: AI policies without accountability conversations are just guardrails without a road. Leading Across Generations Means Meeting Each Person Where They Are Charles led staff ranging from their mid-20s to their early 60s in the same building. His approach: stop treating it as a management challenge and start treating it as a pairing opportunity. The 25-year-old knows something the 62-year-old doesn't — and vice versa. The leader's job is to know both well enough to create the right connections between them. That knowledge only comes from being present with people, not from a platform. Soft Skills Can't Be Taught in a Classroom — They Have to Be Grown Organically Post-COVID, Charles is working with schools where every moment of downtime sends kids to their phones. His antidote isn't a curriculum on communication skills — it's intentionally creating organic social situations where those skills have to show up. Food helps. Conversation starters help. Pairing people together with purpose helps. As a leader, your job is to design the conditions for human connection to happen naturally — not to lecture about its importance. You Can't Take Anyone Past the Ceiling You've Reached Charles's closing challenge is also his answer to the question of what leaders should do this week: keep learning and growing. Not because self-improvement is the point, but because if you stop growing, you put a ceiling on everyone you're trying to develop. The leader who's stopped growing becomes the lid on the organization. The one who keeps learning gives everyone else more room to rise. Memorable Quotes "You can lead them to the answer versus getting them the answer. I made the mistake of giving the answer early on — and that just created dependency."— Charles Stevens "If it's just stuck with you, you can develop dependency. But when you can multiply your leadership, things continue to flourish."— Charles Stevens "If you don't continue to grow, you can't expect other people to continue to grow. You'll reach a ceiling that puts a limit on who you can help."— Charles Stevens "AI can help you ask better questions, but it can't coach someone to find the right answer for themselves."— Dr. MJ (opening reflection) About Our Guest Charles E. Stevens (Ed.S.) has spent nearly 35 years in education as a teacher, coach, award-winning publications adviser, assistant principal, and principal. He has also led sales and service teams outside the classroom. He is a certified coach, speaker, and trainer on the John Maxwell Leadership Team, and a trained expert in Time To Teach! strategies. He presents research-based, practical, and proven strategies at local, state, and national conferences. Today, Charles coaches leaders in healthcare, behavioral health, sales, and education who are ready to grow themselves so their careers grow with them. His mission is leadership that multiplies — moving people from dependency to capability so that impact extends far beyond any single leader or moment. Website: thecoachstevens.com LinkedIn: linkedin.com/in/thecoachstevens YouTube: youtube.com/@thecoachstevens Instagram: @coachstevensofficial Connect with Heartwired Email: [email protected] Website: drmjheartwired.com LinkedIn: linkedin.com/in/maryjeanvignone Subscribe: Don't miss an episode — follow on Spotify and YouTube. Share: If this conversation resonated, share it with a leader who needs a reminder that the most important work still happens in the hallway.

Show Notes: Heartwired – Emotionally Intelligent Leadership Episode Title: Productive Harmony: Why AI Gives You Time Back — But You Have to Decide What to Do With It Host: Dr. MJ Vignone Guest: RJ Kedziora, Author of Productive Harmony & Co-Founder and COO/CTO, Estenda Solutions Episode Summary In this episode of Heartwired, Dr. MJ sits down with RJ Kedziora — author of Productive Harmony, Co-Founder and COO/CTO of Estenda Solutions, HIMSS Davies Award recipient, triathlete, and one of the more unusual guests to appear on a leadership podcast: a software developer whose superpower turned out to be empathy. RJ came up through computer science and spent years building digital health software before he realized the hardest problems in his field weren't technical. They were human. Now he sits in on patient appointments with physicians to understand what they experience, builds teams around empathy before code, and races triathlons at 4:30 AM while thinking about energy management, burnout prevention, and what it really means to be productive. This conversation covers the time management death spiral, why your brain uses 20% of your body's energy and what that means for how you lead, what healthcare's adoption of ambient AI reveals about every industry, and the one shift leaders need to make before the next AI tool lands on their desk. Key Takeaways The Time Management Death Spiral Is Real — and AI Is Making It Worse When AI gives you two hours back, what do you do? Most people fill them with more work. RJ calls this the time management death spiral: every efficiency gain immediately becomes a mandate for more output, with no room for recovery, reflection, or skill-building. The spiral accelerates with every new tool. Breaking it requires a fundamental reframe — not of how much time you have, but of how you measure what matters. Your Brain Is the Most Energy-Hungry Organ You Have — Manage It Accordingly The brain is two percent of your body's mass but consumes twenty percent of your energy. That's why a knowledge worker can sit at a desk all day without moving and come home exhausted. RJ's framework starts here: energy comes before time. You can't optimize your hours if you haven't protected your capacity to think. Moving more, eating well, and changing your environment when you're stuck aren't luxuries — they're the foundation of everything else. Harmony, Not Balance — and the Difference Is Not Semantic Balance implies all things being equal, which is both unrealistic and anxiety-inducing. When you're chasing perfect balance and missing it — which you always will — the gap itself becomes a source of stress that drives further burnout. Harmony acknowledges that different seasons call for different distributions. When a big project demands more work, acknowledge it, and then intentionally rebalance the following week. The goal is flow across time, not equality at any given moment. Healthcare Is Already Showing Us What's Coming — and It's Not What Doctors Feared When ambient listening AI was first introduced to physicians, their first reaction was: administration is going to want me to see another patient. That fear was understandable — and it proved largely unfounded. What many physicians found instead was the time to do what they went into medicine for: actually being present with the person in front of them. RJ's point is clear: AI returns the human to the human work. The question is whether leaders are intentional enough to let that happen. Outcomes, Not Hours — The Measurement Shift That Changes Everything RJ's single most actionable recommendation: stop measuring productivity by time spent and start measuring it by outcomes achieved. When the outcome is met, don't immediately load the next task. Pause. Reflect. Ask what went well and what didn't. In software development this is called a retrospective — and it's one of the most neglected practices in every other industry. In an AI-accelerated world, the ability to learn from what you just did may be more valuable than the speed at which you did it. AI Should Make You Think More — Not Less RJ is direct about one risk he takes seriously: the erosion of critical thinking. When someone can hand a task to AI and pass the output forward without engaging their own judgment, they're not learning — and they're not protecting the organization from AI's tendency to hallucinate. His practice: use AI for brainstorming, but always ask it to critique the output, challenge the assumptions, and surface what might have been missed. Human accountability for AI output is non-negotiable. The Loneliness Epidemic Needs Leaders Who Are Intentional About Connection Remote work plus AI means people can now solve many problems without ever talking to another human. That convenience compounds the loneliness epidemic — and leaders who don't actively push back against it will watch their teams drift further apart. The time AI gives back isn't just an opportunity to do more work. It's an opportunity to reach out, to have the one-on-one, to recreate the moments of connection that remote work quietly stripped away. Memorable Quotes "Busyness is a badge of honor these days. But busyness doesn't mean you're getting stuff done. It just means you're doing stuff."— RJ Kedziora "Your brain is two percent of your body mass but uses twenty percent of your energy. That's why you're tired at the end of the day."— RJ Kedziora "You can never tell me the AI did it. It's human accountability. You need to make sure what it's producing is good."— RJ Kedziora "AI can give us hours back, but it can't tell us what to use those hours for. That is the human work. That is the work of the leader."— Dr. MJ (closing reflection) This Week's One Thing RJ's challenge: pick one team outcome this week and when it's done, stop before moving to the next task. Run a brief retrospective — what went well, what didn't, what would you do differently? Build that into the rhythm of how your team works. That pause is where the real learning lives, and in an AI-accelerated world, learning faster than the pace of change is the only sustainable edge. About Our Guest RJ Kedziora is the author of Productive Harmony: How to Optimize Productivity in the 21st Century, a practical guide for leaders, professionals, and entrepreneurs seeking sustainable high performance in an increasingly demanding world. He is also Co-Founder and COO/CTO of Estenda Solutions, where he leads the development of innovative healthcare, medtech, and AI-driven software solutions. His work has earned the HIMSS Davies Award and the Health 2.0 Outstanding Leadership Award. A computer science graduate who discovered that empathy was his real superpower, RJ brings a rare combination of technical rigor and human-centered thinking to everything he builds. Outside of work, he competes in triathlons — including a full Iron Man — and credits endurance sports with shaping his approach to energy management, resilience, and leading through uncertainty. Book: Productive Harmony on Amazon Company: estenda.com LinkedIn: linkedin.com/in/rjkedziora Connect with Heartwired Email: [email protected] Website: drmjheartwired.com LinkedIn: linkedin.com/in/maryjeanvignone Subscribe: Don't miss an episode — follow on Spotify and YouTube. Share: If this conversation resonated, share it with a leader who just got time back from AI and is already filling it with more work.