Lead The Machine Podcast

Kirstin Marr is a C-level exec and board member who has helped over 100 companies adopt transformative tech and data analytics for 25 years.

Lead The Machine Podcast explores the human side of AI at work. Join the conversation with today's leaders and tomorrow's about what it takes to make AI work for real people, in real organizations. leadthemachine.substack.com

  1. Only 13% Can Measure AI ROI. Now What?

    6h ago

    Only 13% Can Measure AI ROI. Now What?

    When only 13% of companies feel confident measuring AI ROI, you know two things: you are in a hype cycle for a new technology, and operational issues prevent progress. AM Best’s report, “Artificial Intelligence Appears to be Ready, But Most Insurers Are Not,” makes that reality hard to ignore. Sure enough, 45% of insurers cite data readiness as a top challenge. For those of us who have spent years saying “it’s all about the data,” it lands with a thud. The “told you so” moment feels tempting. It also does not help. Data readiness is a problem across every industry, and insurance carries extra complexity because of legacy, regulatory oversight, and the need to defend decisions that affect consumers. Why there’s a gap between pilots and board-ready outcomes should be interrogated, and this episode delivers insight. You’ll gain a pragmatic view at how both organizational and industry dynamics significantly impact success or failure. Two industry veterans offer a front-line view: Jeff Rieder, Partner and Head of Benchmarking at Aon, and Stefan Holzberger, Executive Vice President and Chief Operating Officer at AM Best. Jeff brings a benchmarking lens on how insurers evolve through tech cycles, where job families shift, and why executive alignment and measurement determine whether adoption sticks. Stefan brings AM Best’s lens on innovation, stability, and risk. He shares where insurers deploy AI first, why claims and back-office workflows move faster, and why underwriting adoption demands governance discipline and regulatory awareness. Leadership, culture, and talent development emerge as the common thread. AI does not move through an organization on its own. Companies need leaders who set direction, teams who build foundations, and talent strategies that expand skills instead of amplifying anxiety. It is no surprise that ROI confidence remains low when organizations still struggle to connect data readiness, governance, and adoption behavior to measurable outcomes. Three takeaways from the episode: * Treat data readiness as an operating priority, not a side project. * Define board-ready success measures early, then manage to them with leadership alignment. * Build governance and talent development in parallel so adoption scales without breaking trust. Thank you for listening. - Kirstin This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    49 min
  2. Systems Thinking for AI: How to Get Results Faster

    May 20

    Systems Thinking for AI: How to Get Results Faster

    Hi everyone, The rubber meets the road when we need to prove ROI with any new technology. It’s inevitable and it’s hard. Rob Cressy is an AI enablement coach who works with leaders and teams that want measurable performance from AI. I like that he brings a human-first approach, and anchors AI adoption in identity, vision, and values. Then turns that into execution through systems. AI results come from systems, not dabbling Rob and I talk about a pattern I see across industries. Teams treat AI like a search box. They ask a question, accept the first output, and stop. When the output disappoints, they blame the tool, the data, or the moment. Rob calls this a foundation problem. He says: “the first prompt is the start, not the end.” He also gives a clear reason executives should care. AI adoption creates performance spread inside the same team. Rob shares an example where one person doubles output using AI. That person creates a gap that compounds when peers stay on old workflows. Leaders feel the impact in slower delivery, lower win rates, and more friction across the organization. We also talk about what leaders can do right now. Rob recommends a simple discipline. Teams should list daily friction, choose one workflow to improve, then ship a small win. He pushes leaders to build a roadmap from the work people already dislike, and he reinforces a systems lens. Systems scale, and clarity scales. Rob offers one prompt I expect to reuse: “What is hidden and non-obvious?” He uses AI to surface blind spots, simplify systems, and reduce unnecessary complexity. He treats AI as a tool that supports structured execution, not a replacement for leadership. If you lead a team through AI adoption, this episode will help you build a foundation, improve output, and keep the work human. — Kirstin This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    48 min
  3. Talent Strategy in the Age of AI

    May 6

    Talent Strategy in the Age of AI

    Hi everyone, This week on Lead The Machine, I recorded a special dual interview on site at the Emerging Leaders Conference in Nashville with Wendy Davis Johnson and Marguerite Tortorello. We used the moment to look backward and forward. We traced the early days of the Insurance Careers Movement (ICM), and we connected that work to the talent and skills demands AI creates right now. I’ve shared before that I helped co-found ICM, now in its 11th year. It’s one of my proudest accomplishments. Wendy, author and corporate strategist, took us back to the beginning. She described how she and Brian Duperreault looked for a topic that mattered, researched diversity and leadership visibility, and then found the deeper signal. The industry faced a looming talent gap as experienced professionals retired and fewer young people entered the field. Wendy described how that research led to a simple conclusion. The industry needed a louder voice, and leaders needed to treat talent as a strategic priority. Marguerite, Executive Director of ICM, described what happened next. ICM grew from humble beginnings into a global collaboration. Today, 22 countries participate in Insurance Careers Month, over 1,000 organizations engage in the initiative, and the Emerging Leaders program has produced more than 1,000 alumni across functions, roles, and career stages. Companies now treat February as a kickoff for year-long talent planning, not a one-off recruiting campaign. We also talked about AI. Headlines focus on layoffs and replacement. I see a different path for winning. Organizations win when they invest in people, build AI fluency, and connect that fluency to real customer and operational outcomes. Marguerite described how companies already run intentional upskilling efforts, and she highlighted the role of legal, compliance, government affairs, and regulators in responsible adoption. Wendy reinforced the core reality. AI accelerates research and analysis, and leaders still differentiate through human judgment and relationships. If you care about talent strategy, leadership development, and the human side of AI at work, this episode will give you history, context, and a grounded view of what winning looks like. — Kirstin This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    49 min
  4. AI Tools That Reduce Burden and Restore Dignity

    Apr 22

    AI Tools That Reduce Burden and Restore Dignity

    Hi everyone, This week on Lead The Machine, I spoke with Dakota Koontz, Executive Director at Housing Heroes Hub, about what it takes to lead inside broken systems, and how AI can reduce the load for leaders who carry too much. Now… this may seem counter to my consistent advice to fix broken processes first, rather than slap AI onto inefficient workflows. This is different. Dakota works with housing leaders who face rules layered on rules, outdated technology, and constant pressure to stay compliant while serving vulnerable communities. He also names the part leaders rarely say out loud. The job includes heavy emotional labor. Leaders manage tenants, staff, funding risk, and public scrutiny, often at the same time. These leaders aren’t in a position to fix government systems and regulations. They must adapt, ensure compliance and advocate for their constituents - while being overworked. We focus on that business problem and talk about the technology that can help. Dakota shares concrete ways teams use AI: * Convert long intake packets into digital forms. * Reduce back-and-forth with cleaner inputs. * Prepare for board, funder, and stakeholder conversations with mock dialogues. * Improve prompting with a standard operating procedure (SOP) mindset so output stays consistent. He also makes AI adoption accessible. He does not come from a traditional tech path. He invested the time, built skill through repetition, and taught thousands of people how to do the same. This episode focuses on clarity, dignity, and workload relief. It also shows how leaders can use AI as a tool while keeping the work human. Thanks for listening. Kirstin This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    42 min
  5. Board-Ready AI: Leadership, Data, and Risk with Bill Walsh

    Apr 8

    Board-Ready AI: Leadership, Data, and Risk with Bill Walsh

    Hi everyone, Bill Walsh, the CEO of Mediafly, has played a meaningful role in my leadership journey. I met him more than a decade ago when he served on the board at Valen Analytics, and he has been a steady mentor for me since then. Bill brings 30 years of executive leadership across enterprise software, analytics, logistics, and AI-driven solutions. He has led organizations through growth, product innovation, M&A, and cultural change. He has also served on public and private company boards, taught as an adjunct professor, and coached senior leaders. So what does “Board-Ready AI: Leadership, Data, and Risk” mean? Bill shares an adoption approach leaders can apply immediately: crawl, walk, run. Leaders learn the basics, use AI personally, and create a safe internal environment where teams can practice. Teams build confidence internally, and leaders use what they learn to shape customer-facing AI with clearer requirements and better discipline. Bill also makes the data requirement concrete. AI models depend on the quality of the underlying data. Leaders need accurate, consistent, complete, timely, and unified data to produce reliable outputs. Bill does not ask teams to make data perfect. But they do need to reduce errors, remove duplicates, clarify definitions, and connect silos in the places that matter most. He offers a practical lens for where to start: high value and low friction. He shares examples such as sales content personalization, predictive forecasting, churn analysis, recommendation engines, and knowledge and search. These use cases often deliver value without requiring a full rebuild of every system. We also talk about the board conversation. Boards prioritize risk and governance. Management teams prioritize innovation and speed. Bill advises leaders to bring transparency, explainability, and trusted expert input into board discussions so the company can move with discipline and direction. If you lead a team through AI adoption, or you support leaders who do, this episode gives you a clear framework you can use. Thanks as always for tuning in. Kirstin This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    38 min
  6. Everyone Has Access to AI. A Millennial Leader Explains What Matters Now.

    Mar 25

    Everyone Has Access to AI. A Millennial Leader Explains What Matters Now.

    Hi everyone, I love intergenerational conversations about AI and the future of work, especially with Millennial leaders like John Hyde, a real estate and hospitality project management consultant. AI brings us a rare opportunity to learn from each other, across generations and levels of an organization. John brings a Millennial perspective to questions many leaders are wrestling with right now: What is leadership supposed to look like when everyone has access to the machine? What happens to work when technology keeps promising more flexibility and efficiency, but people still feel stretched, blurred, and exhausted? John’s right on point. The Wall Street Journal published an article showcasing one of the biggest studies of AI’s effect on work. The ActivTrak study included 164K workers and 443 million work hours from 1,111 employers. The bottom line: · Rather than easing workloads, AI is intensifying activity across the board. · Focused work dropped 9%. · We’re getting caught up in the AI prompts of “Do you want to now consider this or that” at the end of most AI output. One of the ideas that stayed with me from this conversation is that leadership can no longer be about gatekeeping. For a long time, leaders often held power because they controlled access to information, tools, relationships, or decision-making. But in the age of AI, that model is eroding quickly. If everyone has access to powerful tools, then the real question becomes: what are you bringing that is unique and additive? John makes the case for people enablement. The leaders who matter most going forward will be the ones who help others grow, develop judgment, build confidence, and become more capable in how they use technology. A few of the themes we explored:🤝 what technology cannot replace in human work📈 why younger generations are rethinking identity, work, and success🛠️ how leaders can help people leave stronger than when they arrived At the heart of the episode is a simple but important idea: AI should make us more human, not less. As a deeply religious person, this reflects John’s interest in keeping humanity at the center. This conversation will resonate with anyone trying to lead well, adapt thoughtfully, and think clearly about what work should become from here. Thanks for reading, listening, and being part of the conversation. Kirstin Marr This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    35 min
  7. The Problem With AI Recruiting Isn’t AI. It’s How We’re Using It.

    Mar 11

    The Problem With AI Recruiting Isn’t AI. It’s How We’re Using It.

    Hi everyone, What happens when recruiting becomes AI talking to AI? That is the question at the center of my newest Lead the Machine episode with Jessica Peskin, CEO of Global Recruiters of Denver. It is one of the most practical and timely conversations I’ve had on the show because it tackles a growing problem hiding in plain sight: companies are adding more AI to hiring, but that does not automatically mean they are getting better at identifying talent. In many cases, the opposite is happening. Candidates are using AI to write resumes. Employers are using AI to write job descriptions. Then automated systems are evaluating both sides and deciding who gets seen. The process may look efficient, but it often strips out the very thing that matters most in hiring: human judgment. Jessica brings a rare lens to this issue. She is a recruiter and two-time founder and experienced operator who has worked across real estate, insurtech, and insurance growth organizations. She has seen firsthand how businesses scale, how leaders hire, and how often the best people do not fit neatly into a keyword match. One of the most compelling ideas in this episode is the importance of the gray area. That is the space where transferable skills, resilience, judgment, and growth potential live. It is also the space many systems are designed to filter out. We talk about:🧠 How companies are over-automating one of the most human decisions they make📄 How candidates flatten their own story into polished but generic resumes🚫 The story of a hiring leader who applied for his own open role and was rejected by the system🎙️ Why leaders need to become better interviewers, not just better users of hiring tools Jessica also shares one of the most surprising pieces of advice from the episode: tell your story honestly, including failure. In a hiring market filled with sameness, that kind of authenticity can be the signal that sets someone apart. The bigger message is one I come back to often: AI can help organize, streamline, and scale. But it should not replace discernment and human connection where it matters most. If you are building a team, looking for your next role, or thinking about the future of work, this conversation will resonate. Thanks for reading and listening. Kirstin Marr This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    39 min
  8. AI Is Inevitable, Relevance Is a Choice

    Feb 25

    AI Is Inevitable, Relevance Is a Choice

    Hi everyone — This week on Lead The Machine, I’m truly honored to share my conversation with Brian Duperreault — former CEO & Chairman of AIG, and a leader who has shaped modern insurance through CEO roles at Marsh & McLennan, ACE (now Chubb), and Hamilton. He’s currently Executive Chairman of Cedar Trace. Brian and I begin where real transformation always begins: people. We talk about why talent remains a true C-suite priority, and why it becomes even more urgent in the age of AI. This is personal for me: Brian and I worked together through the Insurance Careers Movement (ICM), a CEO-led collaboration created to attract and develop the next generation of insurance professionals, including the Emerging Leaders Conference. I helped co-found ICM, now in its 11th year, which is led by the American Casualty Property Insurance Association, The Jacobson Group and AM Best. Over 1,000 companies from 20 countries participate each February for Insurance Careers Month. Be optimistic and pragmatic From there, we turn to AI as the next major technology shift leaders must navigate. Brian offers a grounded perspective: big tech transitions are often slower than we expect, deliver less than we assume early on, and cost more than planned. But they are still inevitable. “I’m an optimist,” Brian shares. The leaders who win are the ones who engage early, shape adoption responsibly, and keep their organizations relevant as the competitive bar rises. We also discuss how AI shows up in practical ways: augmentation over replacement, using technology to reduce drudgery, improve decision quality, and free people to focus on judgment and relationships — the parts of the work that actually differentiate. Finally, Brian shares a simple message for professionals coming up the ranks: do your job well, stay curious, raise your hand for the hard work, and become the person leaders can count on during change. In a world where tools evolve quickly, those habits are what keep you relevant. It’s not often we get to hear from a business titan in an informal setting. Brian’s broad view of AI, risk, and the leadership talent required to navigate AI offers perspective and forward-thinking ideas. His recent biography Faith & Purpose: The Life & Vision of Insurance Icon Brian Duperreault, written by Wendy Davis Johnson (also an ICM co-founder) is well worth reading. Thanks for engaging with Lead The Machine. — Kirstin This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit leadthemachine.substack.com

    23 min
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About

Lead The Machine Podcast explores the human side of AI at work. Join the conversation with today's leaders and tomorrow's about what it takes to make AI work for real people, in real organizations. leadthemachine.substack.com

Information

  • Creator
    Kirstin Marr is a C-level exec and board member who has helped over 100 companies adopt transformative tech and data analytics for 25 years.
  • Years Active
    2025 - 2026
  • Episodes
    21
  • Rating
    Clean
  • Copyright
    © Kirstin Marr
  • Show Website
    Lead The Machine Podcast