Podcasts about mit sloan management review

Today's episode, the final one of Season 13, explores how Bank of America is preparing a massive global workforce for an AI future through upskilling and reskilling. Bernard Hampton, head of the financial institution's Academy, explains how the learning and development organization focuses on workforce agility and a building combination of technical and soft skills. Bernard outlines a three-level approach to adopting artificial intelligence and shares situations in which he feels humans need to stay in the loop. Read the episode transcript here. Guest bio: Bernard Hampton leads The Academy, which is responsible for onboarding and upskilling more than 200,000 employees as Bank of America's chief people organization. The Academy, a team of more than 1,000 dedicated professionals, provides expert facilitation and coaching, compliance education, and immersive technology. Hampton joined the bank in 2004 and has served in many leadership roles, including as a consumer banking division executive. In addition to serving as the bank's executive market sponsor for the West Palm Beach market, he is an executive sponsor for multiple employee engagement groups, networks, and development programs including the Intergenerational Employee Network. Hampton also serves on the global advisory board for Operation Hope, and he is a Herndon Directors Institute fellow and a 2022 inductee to the Executive Leadership Council. He also serves as an executive board member of the Urban League of Palm Beach County. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

On today's episode, Philips's chief medical officer Carla Goulart Peron shares how artificial intelligence is reshaping health care — not by replacing clinicians but by expanding access, improving diagnostics, and freeing doctors to focus more time on patients. Drawing on her experience practicing medicine in Brazil's strained public health system, she explains how technologies like AI-assisted imaging and remote collaboration can bridge critical gaps in care. Carla also explores the challenges of trust, bias, interoperability, and women's health data in the next era of AI-enabled medicine. She offers a grounded, global perspective on how technology can make health care more human. Read the episode transcript here. Guest bio: Dr. Carla Goulart Peron is chief medical officer at Philips. A physician by training, she leads the global team shaping the health technology company's medical strategy for achieving scientific excellence across medical affairs, clinical research, medical safety, and health economics. Before joining Philips, she was vice president and chief medical officer for surgical innovations and robotics at Medtronic. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

On today's episode, Andrew Palmer, senior editor at The Economist, describes how organizations can experiment with generative AI while balancing speed, quality, and risk. At his own organization, Andrew and others test AI with human oversight to develop editing and publishing efficiencies. As the host of The Economist's Boss Class podcast, Andrew speaks with leaders as well as early-career professionals, and highlights interesting insights from recent conversations around skills and hiring. Read the episode transcript here. Guest bio: A senior editor at The Economist, Andrew Palmer writes about the workplace for the “Bartleby” column and hosts Boss Class, a limited-season podcast about management. His previous roles at the publication, which he joined in 2007, include Britain editor, executive editor, business-affairs editor, head of the data team, Americas editor, finance editor, and banking correspondent. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

The AI fallacy is thinking the transformation is only in the tool. AI is already transforming education and work; not just because of what it can do, but because of what people believe it can do. Students, workers, managers, universities, and companies are all changing their behavior around AI, sometimes rationally, sometimes badly, and often before they even fully understand it. The AI paradox is that it is both a technology and a social event. It is a technology because it is something we install, manage, govern, and use. But it is also a social event because it functions as a moment in history, one that is already altering how people learn, work, teach, hire, manage, and make decisions. Treating AI only as technology leads to the fallacy: the mistaken belief that because a challenge is technical, the solution must also be purely technical. My guest is Professor Gerald C. "Jerry" Kane. Prof. Kane is the C. Herman and Mary Virginia Terry Chair in Business Administration and Professor of Management Information Systems at the University of Georgia's Terry College of Business, he has also served as a Visiting Scholar at Harvard Business School, a Guest Editor at MIT Sloan Management Review, and a Senior Editor at MIS Quarterly. Jerry's research explores the role of digital technologies in business strategy, organizational culture, and talent development, with a particular focus on how people and organizations respond to digital disruption. He is also the author of two books on that topic: The Technology Fallacy and The Transformation Myth: Leading Your Organization Through Uncertain Times. I had Jerry on the podcast before. This time, I wanted to talk to him because he sits in both worlds: he studies how companies adapt to digital transformation, and he is also a professor watching AI hit higher education in real time, not as a theory, but in his classroom, with his students, right now. Treating AI as a software update rather than a cultural shift results in 'bolted-on' systems that people neither trust nor understand. Some highlights from the episode. 02:13 Meet Professor Jerry Kane 07:12 How fast AI hit campus 13:22 The university policy divide 14:19 Workplace tools and incentives 17:36 Young minds and the outsourcing of thinking 20:20 Teach the basics first, then add AI 24:22 Degrees vs. lifelong upskilling 29:34 Curation as the new core skill 31:50 AI pushback from artists and creators 32:47 Ethical use over refusal 33:18 What's actually happening inside companies 34:13 Building a coalition of the willing 36:13 Shadow AI and the risks of unsanctioned use 38:25 Efficiency vs. transformation 40:44 Layoffs and AI washing 42:12 Middle managers and org structure 43:27 Adoption steps and safety 47:29 Minimal viable governance 55:35 Jobs anxiety vs. reality 58:30 Bullish long-term, uncertain short-term 1:00:49 Chatbots and attention traps Enjoy! For show notes and more, visit https://www.larryweeks.com/podcasts/

In this episode, Sam speaks with Vineet Khosla, CTO of The Washington Post, about how AI is reshaping the way news is produced, delivered, and consumed. Vineet argues that journalism itself isn't broken — but the formats people use to consume news are rapidly evolving, especially as audiences increasingly interact with information through AI. The conversation explores how the Post is experimenting with personalized AI podcasts, AI-powered research tools for journalists, and conversational news experiences that help readers understand not just what happened but why it matters and how it connects to other world events. Behind the scenes, the Post is deploying artificial intelligence across the entire organization, and Vineet shares details about the organization's “AI everywhere” philosophy. Read the episode transcript here. Guest bio: Vineet Khosla, chief technology officer at The Washington Post, is a renowned AI engineer whose career has been marked by groundbreaking achievements. Before joining the Post in 2023, Khosla created Uber's global maps routing system with cutting-edge AI tools. He was the first engineering hire for Siri's natural language engine, and as a senior AI engineer with Apple, he played a central role in developing the core natural language understanding engine and the architectural framework that allowed the virtual assistant to operate on devices.  Khosla has been working with AI since 2005 and is the holder of two patents and multiple white papers published on the subject. He earned a master's in artificial intelligence at the University of Georgia and a bachelor's in computer science at Pittsburg State University. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

In this episode, Sam talks with Peter Koerte, member of the managing board and chief strategy and technology officer of Siemens, about how industrial AI is quietly transforming the infrastructure that powers everyday life. While consumer AI grabs headlines, Peter explains how artificial intelligence is improving factories, transportation systems, energy grids, and buildings behind the scenes. The conversation explores what makes industrial AI different — from the need for near-perfect accuracy to the challenge of working with proprietary, domain-specific data. Peter shares examples like predicting train door failures days in advance, optimizing building energy use, and accelerating complex engineering simulations. Peter and Sam also discuss the importance of domain expertise, the value of data-sharing partnerships across companies, and why transformation is as much about people and workflows as it is about technology. Read the episode transcript here. Guest bio: As a member of the managing board, chief strategy officer, and chief technology officer of Siemens, Peter Koerte is responsible for developing the company's strategy and leading its worldwide research and development activities. His current priorities include accelerating development of innovative sustainable technologies and continuing development of the Siemens Xcelerator business platform. Koerte previously headed Digital Health, a Siemens Healthineers unit that develops AI-supported diagnostic procedures for health care. He joined the corporate strategy side of the company in 2007 after working for the Boston Consulting Group. Koerte holds a master's degree in business and engineering from the Karlsruhe Institute of Technology and a doctorate in strategy and international management from the WHU-Otto Beisheim School of Management. He also completed the General Management Program at Harvard Business School. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

If workplace culture is failing, are we brave enough to use Gen Z as the prototype for what comes next?In this episode of Practice Disrupted, Amanda Schneider, the founder and president of ThinkLab, joins host Evelyn Lee to discuss her transition from a "designer by degree" to a leading researcher in the built environment. As the author of the upcoming book Work for What's Next, Amanda explores the uncomfortable truth that current workplace structures are struggling to keep up with the shifting expectations of the modern workforce. She shares insights from her viral research into Gen Z, explaining how this generation is not a "problem to manage," but a vital signal for the digital-first evolution that the architecture and design industry must undergo to remain relevant.The conversation delves into the "trust gap" currently widening between leadership and staff, and the specific role physical space plays in closing it. Amanda breaks down the findings from ThinkLab's latest research, challenging architects and designers to think beyond traditional ROI and consider how physical environments can foster psychological safety and authentic connection. She discusses the friction between "analog natives" and "digital natives," offering a roadmap for firms to move beyond describing industry problems and toward building a culture that prioritizes people as much as projects."Workplace culture is failing. Gen Z can see why. And if we're willing to use them as a prototype rather than a problem, they show us exactly where the profession needs to go." - Amanda SchneiderBeyond generational shifts, Amanda and Evelyn discuss the business of research itself and the importance of data in shaping the future of practice. From her journey of building and selling a company to her current focus on the "trust survey," Amanda emphasizes that the future of the profession belongs to those who can bridge the gap between digital-first thinking and the irreplaceable value of physical space.Guest:Amanda Schneider is the founder and president of ThinkLab, a premier market research company wholly focused on the built environment (now a part of Sandow). A designer, journalist, and researcher, her work on Gen Z and workplace culture has been featured in Forbes, MIT Sloan Management Review, and a TEDx talk with over half a million views. Her book, Work for What's Next, focuses on the evolution of professional culture.This episode is especially for you if:✅You want to understand why Gen Z is the "prototype" for the future of work rather than just a generational trend.✅You are a firm leader interested in closing the "trust gap" within your organization.✅You are an "analog native" looking for strategies to pivot toward a digital-first mindset in a design practice.✅You are curious about the evolving ROI of physical office space and how it impacts firm culture.✅You want to hear how market research can be a catalyst for meaningful change in the architecture and design industry.What have you done to take action lately? Share your reflections with us on social and join the conversation.

In this episode, Sam is joined by Jacqui Canney, chief people and AI enablement officer at ServiceNow. Jacqui outlines how the software company has embedded AI agents into processes like employee onboarding to automate tasks, personalize experiences, and free up people's time to focus on higher-value work. She emphasizes that successful adoption of artificial intelligence requires strong change management, workforce training, and a focus on talent — not just technology — including companywide AI skill assessments and personalized learning paths. Tune in to learn why Jacqui sees AI as a human capital opportunity. Read the episode transcript here. *Please take our listener survey: ⁠⁠mitsmr.com/podcastsurvey⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Guest bio: Jacqui Canney is the chief people and AI enablement officer at ServiceNow, where she leads the enterprise software company's talent strategies for improving employees experience and preparing them for the future workforce through the use of technology and generative AI. Before joining ServiceNow in 2021, Canney served as chief people officer at WPP and Walmart. She previously worked at Accenture for 25 years. Canney currently sits on the board of directors for food delivery platform Wonder and nonprofit Project Healthy Minds. She's also on the Institute for Corporate Productivity's Chief HR Officer Board and Boston College's board of trustees, and she cochairs the Boston College Wall Street Business Leadership Council. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

Learn why scaling AI is as much a human challenge as it is a technological one. Stefano Puntoni, Co-Director of Wharton Human-AI Research and Professor at The Wharton School, examines the limits of data-driven decision making in the age of AI and why insights so often fail to translate into action. He breaks down the psychology behind AI resistance and outlines the leadership and change management strategies needed to turn AI potential into real organizational impact. Key Moments: Why More Data Doesn't Lead to Better Decisions (02:26): Stefano challenges the assumption that smarter algorithms automatically produce smarter decisions. He argues that decision quality depends on rigorous conceptual thinking before turning to data. Without clearly defining objectives, alternatives, and success criteria, analytics efforts rarely translate into meaningful action. Conversational AI and the Lowering of the Cost of Action (07:26): Stefano explains how conversational AI brings decision makers closer to data by reducing friction. By lowering the cost of experimentation, AI enables managers to test hypotheses in real time instead of waiting days for analysis. This shift moves organizations from analysis paralysis to faster, more confident action. Rethinking Your Role in the Age of AI (17:16): For professionals navigating disruption, Stefano outlines two paths forward. One is becoming a complement to AI by upskilling and using the technology as a productivity multiplier. The other is pivoting toward skills AI is less likely to replace, such as strategy, orchestration, and human judgment. The AWARE Framework: Pairing Technical Rollout with Human Rollout (22:41): Stefano introduces the AWARE framework to help leaders anticipate and manage the human reactions to AI transformation. He argues that every technical implementation must be matched with structured communication, identity support, and organizational alignment. Without this dual-track approach, even well-designed AI systems can fail to gain traction. Change Management, AI Literacy, and the Gap in Organizational Readiness (31:11): Only a small percentage of organizations have formal AI change management programs. Stefano questions whether companies are truly prepared for large-scale AI transformation. He emphasizes that AI literacy, leadership accountability, and structured change management will determine whether AI investments translate into sustained performance. Key Quotes: “ The leaders need to know why we are doing AI. AI is not a strategy; AI is just a tool. So what is it that we're trying to achieve?” - Stefano Puntoni “ I think the problem is that technology is almost like taking all the oxygen from the room. There's so much attention and urgency around the tech itself that we often forget the people around it.” - Stefano Puntoni “You don't want to be the substitute to the technology because if that is what you do, then there's no future. But if you're a complement, the technology might be a multiplier of your productivity.” - Stefano Puntoni Mentions Decision-Driven Analytics: Leveraging Human Intelligence to Unlock the Power of Data The Wall Street Journal: The Boss Has a Message: Use AI or You're Fired 2025 Report Accountable Acceleration: Gen AI Fast-Tracks Into the Enterprise How AI Affects Our Sense of Self Why Gen AI Feels So Threatening to Workers Conversational AI: The Next Frontier of Digital Platform Monetization Guest Bio  Stefano Puntoni is the Sebastian S. Kresge Professor of Marketing at The Wharton School. Prior to joining Penn, Stefano was a professor of marketing and head of department at the Rotterdam School of Management, Erasmus University, in the Netherlands. He holds a PhD in marketing from London Business School and a degree in Statistics and Economics from the University of Padova, in his native Italy. His research has appeared in several leading journals, including Journal of Consumer Research, Journal of Marketing Research, Journal of Marketing, Nature Human Behavior, and Management Science. He also writes regularly for managerial outlets such as Harvard Business Review and MIT Sloan Management Review. Most of his ongoing research investigates how new technology is changing consumption and society, including how humans are adopting and evolving with AI. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

In this episode, Sam speaks with Taylor Stockton, chief innovation officer at the U.S. Department of Labor, about how artificial intelligence is reshaping the workforce. Taylor emphasizes that AI is having an economywide impact, transforming tasks within nearly every job rather than affecting only certain industries or specific roles. He stresses the importance of helping workers and businesses adapt. He also argues that AI literacy is becoming a foundational skill and should be prioritized alongside soft skills like relationship building, which will remain essential for differentiation in an AI-driven economy. Taylor calls for shifting the public narrative from fear to optimism, toward highlighting the ways that AI expands opportunity, mobility, and meaningful work, instead of deepening uncertainty. Read the episode transcript here. Guest bio: As the chief innovation officer of the U.S. Department of Labor, Taylor Stockton leads an exploration into how artificial intelligence and emerging technologies impact the labor market and American workers, as well as what new innovations can support workers in achieving the American dream. Stockton cofounded venture capital firm Pathway Ventures, which focuses on the future of work, and was the chief operating officer of an AI-powered workforce development company. He received his bachelor's in management at Boston College and Master of Business Administration from Harvard Business School. *Please take our listener survey: ⁠⁠⁠mitsmr.com/podcastsurvey⁠⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.  

On today's episode, Sam talks with Alice Xiang, global head of AI governance at Sony and lead research scientist for AI ethics at Sony AI, about what it actually takes to put responsible artificial intelligence into practice at scale. Alice shares how Sony moved early on AI ethics and why governance, not just principles, is now the real challenge as AI spreads across products and workflows. The conversation dives into FHIBE, Sony's publicly available and ethically sourced benchmark for evaluating bias in computer vision, and why measuring fairness is often harder than fixing it. Along the way, they tackle data consent, “data nihilism,” and the very real risks of deploying biased systems in everyday and high-stakes contexts. Read the episode transcript here. Guest bio: As the global head of AI governance at Sony, Alice Xiang leads the team guiding the establishment of AI governance policies and governance frameworks across the company's business units. She's also the lead research scientist for AI ethics at Sony AI, which is working on cutting-edge sociotechnical research to enable the development of more responsible AI solutions. Xiang holds a Juris Doctor from Yale Law School, a master's in development economics from Oxford University, and a master's in statistics and bachelor's in economics from Harvard University. *Please take our listener survey: ⁠mitsmr.com/podcastsurvey⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

What you will learn in this episode: Why the title of "thought leader" is something earned from others, not a label you give yourself What the critical difference is between attention and authority in a landscape of endless content How consistency and repetition differentiate true thought leaders from self-proclaimed ones Why your ideas need to be tested and challenged for them to be trusted Why context is king, and how skipping to conclusions erodes trust Communications is the CENTER OF ALL THINGS. Lee Caraher talks all things communications – from language to format to channel, from employee engagement to great leadership, from PR to social media, and reputation management to personal branding, and crisis communication, bringing you key insights from her experience and expertise that can be used in the day-to-day to make your work, your PR, and your culture, and your potential …WORK. Resources: Website: https://leecaraher.com/ Website: www.double-forte.com Instagram: https://www.instagram.com/leecaraher/ LinkedIn: https://www.linkedin.com/in/leecaraher Facebook: https://www.facebook.com/LeeCaraher1/ Twitter: https://twitter.com/leecaraher Edelman Trust Barometer: https://www.edelman.com/trust/2026/trust-barometer MIT Sloan Management Review: https://sloanreview.mit.edu/

How much do we know about the way organizations are adopting agentic AI, and what it means for the human employees working alongside?  Our friends at The MIT Sloan Management Review did a deep dive on these questions and several more late last year, and they found some pretty surprising things.This week, we're going to talk about what those things might mean for companies as we continue to unpack this latest phase of agentic rollouts.We Meet: Sam Ransbotham is a professor of analytics at Boston College, the editor for the MIT Sloan Management Review AI Initiative, and the host of Me, Myself and AI. Credits:This episode of SHIFT was produced by Jennifer Strong with help from Emma Cillekens. It was mixed by Garret Lang, with original music from him and Jacob Gorski. Art by Meg Marco.

In this bonus episode, Nobel Prize-winning economist Daron Acemoglu joins Sam to challenge some of the most common assumptions about artificial intelligence's future. Drawing on his book Power and Progress, Daron argues that technology doesn't have a fixed destiny — and that today's choices will determine whether AI boosts workers or simply accelerates automation and inequality. He makes a case for focusing on new tasks that complement human skills, rather than replacing them, and warns that current incentives push AI toward centralization and automation by default. The conversation tackles productivity myths, reliability risks, and why regulation should proactively steer AI toward social good. Read the episode transcript here. Guest bio: Daron Acemoglu is an institute professor at MIT, faculty codirector of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work, and a research affiliate at MIT's newly established Blueprint Labs. He is an elected fellow of the National Academy of Sciences, American Philosophical Society, the British Academy of Sciences, the Turkish Academy of Sciences, the American Academy of Arts and Sciences, the Econometric Society, the European Economic Association, and the Society of Labor Economists. He is also a member of the Group of Thirty. He has authored six books, including Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity with Simon Johnson. His work in economics has been recognized around the world, notably with the Nobel Prize in economic sciences, along with co-laureates Johnson and James A. Robinson, in 2024. *Please take our listener survey: ⁠⁠mitsmr.com/podcastsurvey⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

In this episode, host Fred Davis sits down with Sam Ransbotham, Professor of Analytics at Boston College and AI Editor for MIT Sloan Management Review.We strip away the hoopla and doom-and-gloom to get to the "brass tacks" reality of how this technology works in the wild and academia. From the classroom to the boardroom, Sam explains why we are focusing on the wrong risks—and why the biggest danger isn't that AI will replace us, but that we'll use it to automate our own bad habits.Key Topics:The Calculator Analogy: Why banning ChatGPT in schools is exactly like banning calculators in math class (and why we need to get over it).The "Fax Machine" Trap: How companies are spending millions to use AI to read bad data, instead of just fixing the process.The "Sycophant" Effect: Why AI models are programmed to be "people pleasers," and why that makes them dangerous "Yes Men" in business.Magic vs. Math: Why understanding the limitations of these models is the only way to actually get value from them.

In this bonus episode, Princeton University professor and artificial intelligence researcher Tom Griffiths joins Sam to unpack The Laws of Thought, his new book exploring how math has been used for centuries to understand how minds — human and machine — actually work. Tom walks through three main frameworks shaping intelligence today — rules and symbols, neural networks, and probability — and he explains why modern AI only makes sense when you see how those pieces fit together. The conversation connects cognitive science, large language models, and the limits of human versus machine intelligence. Along the way, Tom and Sam dig into language, learning, and what humans still do better — like judgment, curation, and metacognition. Read the episode transcript here. *Please take our listener survey: ⁠mitsmr.com/podcastsurvey⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

In this not-to-be- missed episode Dr. Hannes Leroy, professor of leadership development at the Rotterdam School of Management, joins Michael and Gregg to discuss his somewhat radical thoughts on authenticity and leadership. As this spirited conversation evolves, Dr. Hannes challenges us with the question: “Is much of our popular leadership development just happy-making?'Read the MIT Sloan Management Review article

In this season premiere of The Data Chief podcast, host Cindi Howson sits down with three industry leaders to unpack what's next for AI, and the concrete moves data and AI leaders need to make in 2026—many of which are detailed in ThoughtSpot's Top Data & AI Trends of 2026 ebook.Get ready for a deep dive into:Agentic AI goes mainstream with Paul Baier, CEO and Co-Founder of GAI InsightsAI-ready data and the rise of the AI manager with Jennifer Belissent, Principal Data Strategist at SnowflakeScaling agents with trust and control with Rory Blundell, CEO of GraviteeConsider this your field guide to navigating AI in 2026.Key Moments:Agentic AI Goes Mainstream with Paul Baier, GAI Insights (1:50): Paul Baier, CEO and Co-Founder of GAI Insights, explains why enterprises that already have GenAI in production are pulling decisively ahead, how agentic AI is reshaping enterprise operating models, and why leadership alignment and AI literacy will determine winners in 2026.AI-Ready Data and the Rise of the AI Manager, Jennifer Belissent, Snowflake (19:16): Dr. Jennifer Belissent, Principal Data Strategist at Snowflake, breaks down why data quality, transparency, and governance remain the foundation of AI success, and why the next critical enterprise skill is learning how to manage AI agents as part of the workforce.Scaling Agents with Trust and Control with Rory Blundell, Gravitee (35:11): Rory Blundell, CEO of Gravitee, shares how the agentic era is redefining API integration, why most enterprises are stuck at early AI maturity stages, and how agent management and security frameworks will unlock real action in 2026.Key Quotes:“Yo u have to treat AI as a capability and not an IT project.” - Paul Baier“ Transparency as a requirement is not slowing down adoption. It's actually accelerating it.” - Jennifer Belissent“My prediction is that companies that adopt robust security frameworks in 2026 will be the companies that accelerate fastest.” - Rory Blundell MentionsGAI Insights' Corporate Buyers Guide to Enterprise Intelligence ApplicationsHarvard Business Review: GAI Insights' WINS FrameworkGravitee's AI Readiness CurveThoughtSpot's Top Data & AI Trends of 2026 ebookGuest Bios Paul BaierMr. Baier is the CEO and principal analyst at GAI Insights. Mr Baier co-authored 4 articles about enterprise GenAI that were featured in Harvard Business Review and MIT Sloan Management Review. He was appointed an Executive Fellow at Harvard Business School and is a Forbes contributor. He is a seasoned software entrepreneur with two decades of experience and multiple exits. Related to AI, he was VP of Product at First Fuel Software, an enterprise AI company for 5 years. He holds an MBA from Harvard and a BA from Kenyon College.Jennifer BelissentAs Principal Data Strategist, Jennifer advises Snowflake customers on data and AI strategy and best practices in building world-class organizations. Previously, she spent over a decade as a Forrester Analyst, and has held management positions in tech sales and marketing, designed urban policy programs, taught secondary school math as a Peace Corps volunteer, and earned a Ph.D. in political science from Stanford University and a B.A. in econometrics from the University of Virginia.Rory BlundellRory Blundell is the CEO of Gravitee. He joined the company in March 2020, first as Chief Revenue Officer, before becoming CEO in September 2020. Prior to Gravitee, Blundell led SnapLogic's EMEA expansion from a technical sales perspective, overseeing significant growth in EMEA revenues over three years. Prior to SnapLogic, he was the CEO and founder of Velinko, a UK software and consultancy company for the legal and accounting sectors. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Welcome back to another episode of Pushing Beyond the Obvious. I recently read a blog post from the MIT Sloan Management Review titled "Your people are not all right," which highlights the immense overwhelm and stress employees are currently facing. This inspired me to talk about a critical responsibility we have as leaders: having a clear understanding of what is happening in our team members' lives, not to spy on them, but to genuinely ensure their wellbeing. In this video, I break down the subtle but vital differences between an average leader, a good leader, and a leader worth following. While a good leader might only notice a problem when it negatively affects the team's results, a leader worth following is always on the lookout for shifts in behavior—whether it's a top performer slacking off, someone suddenly arriving late, or a typically cheerful person becoming withdrawn. I discuss why regular check-ins and asking simple questions like "Are you okay?" or "Tell me what's going on?" are the best tools you have. These questions give your people the space to share what they are comfortable with and help them feel truly seen, heard, and invested in. Listen in to learn how to spot these signals early so you can take care of your team before they burn out.

Innovation has long been a Western strategy, but how can it be made effective against an industrially and economically strong China? Dame Fiona Murray explains. A defining feature of the West's Cold War approach to the Soviet Union was leveraging its technological and economic advantages, including through 'offset strategies'. While defence innovation remains a pillar of Western security, its focus has shifted toward dual-use technologies, reflecting a broader move of the locus of innovation from states to private industry. However, just as earlier episodes in Season 5 explored (Episodes 10 and 11 regarding US industrial mobilisation during the Second World War, and Jean Monnet's plans for European post-war cooperation), success requires many actors coming together to create a resilient ecosystem. Achieving this demands alignment by all parties. Professor Dame Fiona Murray is the Chair of the NATO Innovation Fund and William Porter (1967) Professor of Entrepreneurship at the Massachusetts Institute of Technology. She advises the UK Government and sits on the European Innovation Council Joint Expert Group. Her work is published widely in Science, Nature, American Journal of Sociology, Organisation Science and the Journal of Economic Behaviour and Organisation. Her most recent book Accelerating Innovation: Competitive Advantage through Ecosystem Engagement, (MIT Press, 2025) is with Phil Budden. Further Reading Phil Budden and Fiona Murray, Accelerating Innovation: Competitive Advantage through Ecosystem Engagement, MIT Press, 2025. Edlyn V. Levine and Fiona Murray, How the US and its allies can rebuild economic security, in MIT Technology Review, 30 July 2024. Stefan Raff, Fiona E. Murray, and Martin Murmann, Why You Should Tap Innovation at Deep-Tech Startups, in MIT Sloan Management Review, Fall 2024. Gene Keselman and Fiona Murray, Dual-use is a Strategy, Not a Category (Nor a Trap), War on the Rocks, 2 January 2025.

On today's episode, Wendy's product manager Will Croushorn joins host Sam to share how FreshAi, the fast-food restaurant's voice-based AI ordering system, is reinventing the drive-through experience for millions of customers. From handling 200 billion ways to order a Dave's Double burger to making fast food more accessible for guests in multiple languages, Will reveals how empathy and innovation will positively impact the future of convenience. Learn how his team turns speech data into insight, builds trust in automation, and can even hide a few Easter eggs in your next order. Read the episode transcript here. That's a wrap on Season 12! We'll back in January with a bonus episode. Guest bio: Will Croushorn is a product leader at Wendy's and cocreator of its drive-through voice agent, FreshAi, which handles more than 150,000 orders each day across hundreds of stores throughout the U.S. Recognized by Fast Company as one of the “Next Big Things in Tech,” the artificial intelligence platform shows that AI can deliver measurable impact at enterprise scale. Croushorn's career has been shaped by relentless curiosity: He started a school in northern Iraq, became fluent in Behdini Kurdish, and now advances vision and multimodal AI serve customers in entirely new ways. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

Before the Space Shuttle Challenger exploded in 1986, NASA management officially estimated the probability of catastrophic failure at one in one hundred thousand. That's about the same odds as getting struck by lightning while being attacked by a shark. The engineers working on the actual rockets? They estimated the risk at closer to one in one hundred. A thousand times more dangerous than management believed.¹ Both groups had access to the same data. The same flight records. The same engineering reports. So how could their conclusions be off by a factor of a thousand? The answer isn't about intelligence or access to information. It's about the mental frameworks they used to interpret that information. Management was using models built for public relations and budget justification. Engineers were using models built for physics and failure analysis. Same inputs, radically different outputs. The invisible toolkit they used to think was completely different. Your brain doesn't process raw reality. It processes reality through models. Simplified representations of how things work. And the quality of your thinking depends entirely on the quality of mental models you possess. By the end of this episode, you'll have three of the most powerful mental models ever developed. A starter kit. Three tools that work together, each one strengthening the others. The same tools the NASA engineers were using while management flew blind. Let's build your toolkit. What Are Mental Models? A mental model is a representation of how something works. It's a framework your brain uses to make sense of reality, predict outcomes, and make decisions. You already have hundreds of them. You just might not realize it. When you understand that actions have consequences, you're using a mental model. When you recognize that people respond to incentives, that's a model too. Think of mental models as tools. A hammer drives nails. A screwdriver turns screws. Each tool does a specific job. Mental models work the same way. Each one helps you do a specific kind of thinking. One model might help you spot hidden assumptions. Another might reveal risks you'd otherwise miss. A third might show you what success requires by first mapping what failure looks like. The collection of models you carry with you? That's your thinking toolkit. And like any toolkit, the more quality tools you have, and the better you know when to use each one, the more problems you can solve. Here's the problem. Research from Ohio State University found that people often know the optimal strategy for a given situation but only follow it about twenty percent of the time.² The models sit unused while we default to gut reactions and habits. The goal isn't just to collect mental models. It's to build a system where the right tool shows up at the right moment. And that starts with having a few powerful models you know deeply, not dozens you barely remember. Let's add three tools to your toolkit. Tool One: The Map Is Not the Territory This might be the most foundational mental model of all. Coined by philosopher Alfred Korzybski in the 1930s, it delivers a simple but profound insight: our models of reality are not reality itself.³ A map of Denver isn't Denver. It's a simplified representation that leaves out countless details. The smell of pine trees, the feel of altitude, the conversation happening at that corner café. The map is useful. But it's not the territory. Every mental model, every framework, every belief you hold is a map. Useful? Absolutely. Complete? Never. This explains the NASA disaster. Management's map showed a reliable shuttle program with an impressive safety record. The engineers' map showed O-rings that became brittle in cold weather and a launch schedule that left no room for delay. Both maps contained some truth. But management's map left out critical territory: the physics of rubber at thirty-six degrees Fahrenheit. When your map doesn't match the territory, the territory wins. Every time. How to use this tool: Before any major decision, ask yourself: What is my current map leaving out? Who might have a different map of this same situation, and what does their map show that mine doesn't? The NASA engineers weren't smarter than management. They just had a map that included more of the relevant territory. Tool Two: Inversion Most of us approach problems head-on. We ask: How do I succeed? How do I win? How do I make this work? Inversion flips the question. Instead of asking how to succeed, ask: How would I guarantee failure? What would make this project collapse? What's the surest path to disaster? Then avoid those things. Inversion reveals dangers that forward thinking misses. When you're focused on success, you develop blind spots. You see the path you want to take and ignore the cliffs on either side. Here's a surprising example. When Nirvana set out to record Nevermind in 1991, they had a budget of just $65,000. Hair metal bands were spending millions on polished productions.⁴ Instead of trying to compete on the same terms and failing, they inverted the formula entirely. Where hair metal was flashy, Nirvana was raw. Where others added complexity, they stripped down. Where the industry zigged, they zagged. The result? They didn't just succeed. They created an entirely new genre and sold over thirty million copies. They won by inverting the game everyone else was playing. How to use this tool: Before pursuing any goal, spend ten minutes listing everything that would guarantee failure. Be specific. Be ruthless. Then look at your current plan and ask: Am I accidentally doing any of these things? Inversion doesn't replace forward planning. It completes it. Tool Three: The Premortem Imagine your project has already failed. Not "might fail" or "could fail." It has failed. Completely. Now your job is to explain why. Researchers at Wharton, Cornell, and the University of Colorado tested this approach and found something striking: simply imagining that failure has already happened increases your ability to correctly identify reasons for future problems by thirty percent.⁵ Why does this work? When we think about what "might" go wrong, we stay optimistic. We protect our plans. We downplay risks because we're invested in success. But when we imagine failure has already occurred, we shift into explanation mode. We're no longer defending our plan. We're forensic investigators examining a wreck. Here's proof the premortem works in the real world. Before Enron collapsed in 2001, its company credit union had run through scenarios imagining what would happen if their sponsor company failed.⁶ They asked: If Enron goes under, what happens to us? They made plans. They reduced their dependence. When the scandal broke and Enron imploded, taking billions in shareholder value with it, the credit union survived. They'd already rehearsed the disaster. Every other institution tied to Enron was blindsided. The credit union had seen the future because they'd imagined it first. How to use this tool: Before any major decision, fast-forward to failure. It's one year from now and everything has gone wrong. Write down why. What did you miss? What risks did you ignore? Then prevent those things from happening. You can't prevent what you refuse to imagine. How These Three Tools Work Together Each tool is powerful alone. Together, they're transformational. Imagine you're considering a career change. Leaving your stable job to start a business. Start with The Map Is Not the Territory. What's your current map of entrepreneurship? Probably shaped by success stories, LinkedIn posts, and survivorship bias. But what's the actual territory? CB Insights analyzed over a hundred failed startups to find out why they died. The number one reason, responsible for forty-two percent of failures, was building something nobody wanted.⁷ Founders had a map that said "customers will love this." The territory said otherwise. What is your map leaving out? Apply Inversion. How would you guarantee this business fails? Starting undercapitalized. Launching without testing the market. Ignoring early warning signs because you're emotionally invested. Now look at your current plan. Are you doing any of these things? Run a Premortem. It's two years from now. The business has failed. Write the story. Maybe you ran out of money at month fourteen. Maybe your key assumption about customer behavior turned out to be wrong. What happened? One tool gives you a perspective. Three tools working together give you something close to wisdom. This is exactly what the NASA engineers were doing, and what management wasn't. The engineers were constantly asking: Does our map match the territory? What would cause failure? What are we missing? Management was stuck in a single frame: schedule and budget. The difference between a one-in-one-hundred-thousand estimate and a one-in-one-hundred estimate? The difference between confidence and catastrophe? It was the thinking toolkit each group brought to the problem. Practice: The Three-Tool Test Here's how to put these tools to work this week. Identify a decision you're currently facing. Something real. Something that matters. Write it in one sentence. Check your map. What assumptions are you making? Where did they come from? Who might see this differently? Invert it. Set a timer for five minutes. List every way you could guarantee failure. Be ruthless. Run the premortem. It's one year from now. You chose wrong. Write two paragraphs explaining what happened. Find the overlap. Where do your inversion list and premortem story agree? That's your highest-risk blind spot. Take one action. What's one step you can take this week to address your biggest risk? Twenty minutes. One decision. Run it once, then try it again next week on a different decision. As you use these tools, you'll notice other mental models worth adding. Your toolkit will grow. Most decisions feel routine until they're not. That morning at NASA felt routine. Seven astronauts boarded Challenger. They trusted that the people making decisions had the right tools to think clearly. Management had maps. The engineers had territory. The distance between those two things was seventy-three seconds of flight time. The engineers saw it coming. Management didn't. Same data. Different tools. When your moment comes, and it will, which group will you be in?   If this episode helped you think differently, hit that Subscribe button and tap the bell on our YouTube channel so you don't miss what's coming next. And if you found value here, a Like helps more people discover this content. To learn more about mental models, listen to this week's show: Mental Models — Your Thinking Toolkit. Get the tools to fuel your innovation journey → Innovation.Tools https://innovation.tools [irp posts="4392" name="Subscribe to Podcast"] ENDNOTES Rogers Commission Report, Volume 2, Appendix F: "Personal Observations on Reliability of Shuttle" by Richard Feynman (1986). Management estimated 1 in 100,000; engineers and post-Challenger analysis found approximately 1 in 100. Konovalov, A. & Krajbich, I. "Mouse tracking reveals structure knowledge in the absence of model-based choice." Nature Communications (2020). Participants followed optimal strategies only about 20% of the time even when they demonstrably knew them. Korzybski, Alfred. Science and Sanity: An Introduction to Non-Aristotelian Systems and General Semantics (1933). Wikipedia, "Nevermind"; SonicScoop, "Time and Cost of Making an Album Case Study: NIRVANA" (2017). Initial recording budget was $65,000. Mitchell, D.J., Russo, J.E., & Pennington, N. "Back to the future: Temporal perspective in the explanation of events." Journal of Behavioral Decision Making (1989). As cited in Klein, G. "Performing a Project Premortem." Harvard Business Review (2007). Schoemaker, P.J.H. & Day, G.S. "How to Make Sense of Weak Signals." MIT Sloan Management Review (2009). Describes how Enron Federal Credit Union survived the Enron collapse through scenario planning. CB Insights. "The Top 12 Reasons Startups Fail." Analysis of 111 startup post-mortems (2021). 42% cited "no market need" as a reason for failure.

All tech is witchcraft…until it isn't. Today, we're talking to Sam Ransbotham, AI editor at MIT Sloan Management Review and host of the Me, Myself, and AI podcast. We discuss why 76% of executives now view AI as a coworker rather than a tool, how healthcare privacy laws from 1996 can't handle modern AI capabilities, and why cheaper coding will create more programming jobs instead of eliminating them. All of this right here, right now, on the Modern CTO Podcast!  Thank you to Digital Ocean for sponsoring this episode. For simple cloud and powerful AI that's built to scale, check out Digital Ocean here. To read MIT Sloan's AI study, "The Emerging Agentic Enterprise," check it out here!

On this episode, OpenAI's chief economist Ronnie Chatterji describes how artificial intelligence is reshaping both the economy and scientific innovation. Ronnie discusses the dual economic impacts of AI — the near-term boost from infrastructure investments like chips and data centers, and the longer-term productivity gains as AI tools integrate into enterprises and consumer life. Beyond consumer convenience, he notes, the key question for economists and corporate leaders alike is when — and how — AI will unlock sustained economic value inside organizations. Tune in for Ronnie's perspective on how AI can help researchers test ideas faster, combine insights across disciplines, and make better choices about which problems to pursue. Read the episode transcript here. Guest bio: Aaron (Ronnie) Chatterji is OpenAI's first chief economist. He is also the Mark Burgess & Lisa Benson-Burgess Distinguished Professor at Duke University. He served in the Biden administration to implement the CHIPS and Sciences Act and was acting deputy director of the National Economic Council. Before that, he was chief economist at the Department of Commerce and a senior economist at the White House Council of Economic Advisers. He also previously taught at Harvard Business School, worked at Goldman Sachs, and was a term member of the Council on Foreign Relations. Chatterji is on leave as a research associate at the National Bureau of Economic Research. He holds a Ph.D. from University of California, Berkeley and a B.A. in economics from Cornell University. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

According to Forbes magazine, in 2020 alone global spend on corporate training programmes, often focused on leadership development, exceeded $350 billion. Yet how effective, if at all, are these programmes? And are they perhaps just a massive waste of time and money? To dig deep into the question of why leadership development might be failing us I am delighted to be joined on the podcast by Professor Moran Anisman-Razin.About our guest…Dr. Moran Anisman-Razin, is an Associate Professor of Work and Organizational Psychology in the Department of Work and Employment Studies at the Kemmy Business School, University of Limerick. She is also a Visiting Research Scholar at the Behavioral Science and Policy Center, Social Science Research Institute at Duke University, USA and Faculty Affiliate at the Center for Innovative Leadership, Carey Business School, Johns Hopkins university. Through her work, Moran explores questions of leadership in organizations and is particularly interested in examining leaders' perspectives and identities as shaping behavior, leader development, and exploring ways to make leadership development programs more evidence-based and rigorous.The MIT Sloan Management Review article discussed in the interview - Leadership Development Is Failing Us. Here's How to Fix It - is available here: https://sloanreview.mit.edu/article/leadership-development-is-failing-us-heres-how-to-fix-it/A key article also referenced in the interview - Uncomfortable but Developmental: How Mindfulness Moderates the Impact of Negative Emotions on Learning - https://journals.aom.org/doi/abs/10.5465/amle.2023.0434 Hosted on Acast. See acast.com/privacy for more information.

What's the real value in AI tools — and what separates those who use them well from those who don't? Sam Ransbotham, professor of business analytics at Boston College and host of the "Me, Myself and AI" podcast from MIT Sloan Management Review, compares notes with GeekWire Podcast host Todd Bishop in a two-part collaboration between the shows. On this episode, they discuss the new digital divide emerging in the classroom, AI's measurement problem (and what Wikipedia teaches us about it), the "race to mediocre," how AI is democratizing startup creation, and the tension between AI productivity, time, and the moments that make us human. Find the rest of their conversation in the Me, Myself and AI podcast feed. See omnystudio.com/listener for privacy information.

AI isn't taking jobs — it's changing what jobs are.On today's episode, GeekWire's Todd Bishop joins host Sam Ransbotham to dive into how artificial intelligence is reshaping work, learning, and creativity — not by replacing humans but by amplifying what we can do. From classrooms where students use AI on exams to newsrooms rethinking how news stories get written, they explore the opportunities (and headaches) of this new era. It's a smart, funny, and refreshingly real look at how we're all learning to work with our newestcoworker — artificial intelligence. Read the episode transcript here.  Guest bio: Todd Bishop is cofounder of GeekWire, the Seattle-based business and technology news site, where he covers topics like AI, Microsoft, and Amazon, in addition to hosting a weekly podcast. A native of Orland, California, the longtime journalist previously worked at The Philadelphia Inquirer, Puget Sound Business Journal, and the Seattle Post-Intelligencer. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

This week: Jeff Bezos is back in startup mode (sort of) with Project Prometheus — a $6.2 billion AI-for-the-physical-world venture that instantly became one of the most talked-about new companies in tech. We dig into what his return to the CEO title really means, why the company’s location is still a mystery, and how this echoes the era when Bezos was regularly launching big bets from Seattle. Then we look at Amazon’s latest real-world experiment: package-return kiosks popping up inside Goodwill stores around the Seattle region. It’s a small pilot, but it brings back memories of the early days when Amazon’s oddball experiments seemed to appear out of nowhere. And finally…Todd makes the case for upgrading his 2007 Toyota Camry with CarPlay, Android Auto, and a backup camera — while John questions the logic of sinking thousands into a beloved older car. All that, plus a mystery Microsoft shirt, a little Seattle nostalgia, and a look ahead to next week’s podcast collaboration with Me, Myself and AI from MIT Sloan Management Review.See omnystudio.com/listener for privacy information.

Kdo má právo získat zaměstnanecké akcie? Jak se budou nově danit a co musí startup udělat, aby je mohl rozdávat? V podcastu Business Intelligence radí Martin Jiránek, předseda České startupové asociace, a Martin Švalbach z advokátní kanceláře PRK Partners. Co všechno ještě nový zákon o zaměstnaneckých akciích od ledna v Česku přinese? Kolik bude program startupy stát? Jak dlouho potrvá jeho příprava a na co by si měli zaměstnanci dát pozor? To vše se dozvíte v novém podcastu Business Intelligence z dílny MIT Sloan Management Review a iLead Institute Česko.

Kdo má právo získat zaměstnanecké akcie? Jak se budou nově danit a co musí startup udělat, aby je mohl rozdávat? V podcastu Business Intelligence radí Martin Jiránek, předseda České startupové asociace, a Martin Švalbach z advokátní kanceláře PRK Partners. Co všechno ještě nový zákon o zaměstnaneckých akciích od ledna v Česku přinese? Kolik bude program startupy stát? Jak dlouho potrvá jeho příprava a na co by si měli zaměstnanci dát pozor? To vše se dozvíte v novém podcastu Business Intelligence z dílny MIT Sloan Management Review a iLead Institute Česko.

Vishal Gupta, engineering manager, machine learning at Reddit, joins the podcast to explain how the social media community platform uses artificial intelligence to improve user experience and ad relevance. Much of the advertising work relies on increasingly sophisticated recommender systems that have evolved from simple collaborative filtering to deep learning and large language model–based systems capable of multimodal understanding. https://mitsmr.com/4onhUMgVishal and Sam also explore the philosophical and ethical aspects of AI-driven platforms. Vishal emphasizes the importance of balance — between exploration and exploitation in recommendations, between advertiser goals and user experience, and between human- and machine-generated content. He argues that despite the rise of AI-generated material, authentic human conversation remains vital and even more valuable as models depend on it for training. Read the episode transcript here. Guest bio: Vishal Gupta is a seasoned engineering leader who leads multiple artificial intelligence and machine learning teams at Reddit in the ads domain. He has a decade of experience working on cutting-edge machine learning techniques at companies like DeepMind, Google, and Twitter. Gupta is passionate about applied AI research that significantly contributes to a company's top and bottom lines. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

New research from MIT Sloan Management Review shows how to avoid the ‘hero complex' and lead change that actually lasts. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Kathleen Peters brings a background with digital communications companies and tech startups to her role as Experian's chief innovation officer. On this episode, Kathleen shares a bit about Experian's Innovation Lab, outlining some of its projects and explaining how the recent democratization of generative AI tools has made even more innovative thinking possible, both for tech experts and for contributors who have other core competencies. Read the episode transcript here. Guest bio: As Experian's chief innovation officer, Kathleen Peters explores new ways to solve market challenges in identity, risk, and fraud detection. She and her team define business strategies and investment priorities while incubating new products, analyzing industry trends, and leveraging the latest technologies to bring ideas to life. Peters joined Experian in 2013 to lead business development and global product management for its newest fraud products. She later led its Fraud & Identity business in North America until being named chief innovation officer for decision analytics in 2020. Peters has twice been named a “Top 100 Influencer in Identity” by One World Identity (now Liminal), which annually recognizes influencers and leaders in the identity space. Peters is regularly quoted in prominent media outlets, including Forbes and Bloomberg, and she frequently shares her insights on innovation, AI, and fraud prevention at industry events. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Cisco is well known for its data, networking, security, and collaboration products. On today's episode, Cisco's president and chief product officer, Jeetu Patel, joins Sam for a discussion about artificial intelligence, a “megatrend” Jeetu sees as perhaps more significant than the development of the internet or the automobile because of its ability to build on past technological advances. Jeetu and Sam discuss how to manage AI and how to staff for it — Jeetu argues that replacing less experienced or younger workers with technology deprives organizations of key perspectives and new ideas, and instead advocates for developing reverse-mentoring programs inside organizations. Read the episode transcript here. Guest bio: Jeetu Patel, Cisco's president and chief product officer, combines product design and development expertise, operational rigor, and market understanding to create high-growth businesses. He is tasked with building world-class products to solve customers' problems, and connect and protect every aspect of their organization in the AI era. Previously a general manager at Cisco, he led the strategy and development of its Security and Collaboration businesses. Before Cisco, Patel was the chief product officer and chief strategy officer at cloud content management company Box. He's also held roles at EMC, including chief executive of its Syncplicity business unit, CMO for the Information Intelligence Group, and chief strategy officer. He currently serves on the board of JLL, a commercial real estate services company. Jeetu has a bachelor's degree in information decision sciences from the University of Illinois at Chicago, and lives in the San Francisco Bay Area. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

A chemical engineer by training, Angela Nakalembe worked in the sciences and management consulting before landing at YouTube as the company's engineering program manager for trust and safety. At YouTube, Angela explains, AI has become a first line of defense against harmful content. The technology not only accelerates content moderation tasks but makes the process more humane, by filtering out problematic content before it reaches a human reviewer. To combat the proliferation of AI-generated content that may be hard to discern from assets created by humans, YouTube, its parent company Google, and others have joined the Coalition for Content Provenance and Authenticity Alliance to establish standards for the origin of content they observe. Also on today's episode, Angela shares some personal experiences using large language models (LLMs) and Google's own AI tools to illustrate how she sees individuals using AI in the future. Read the episode transcript here. Guest bio Angela Nakalembe is an operations leader, internet safety expert, and advocate for responsible AI development. As an engineering program manager at YouTube, she leads strategic initiatives focused on protecting billions of users through innovative safety features and risk mitigation strategies, work that has earned multiple Google product excellence awards. Nakalembe developed her strategic expertise as a management consultant, when she supported multimillion-dollar technology migrations for Fortune 50 companies. She currently provides mentoring through TechWomen, a U.S. Department of State initiative creating the next generation of women technology leaders worldwide, and she teaches yoga. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Thomas Wolf is the cofounder and chief science officer of open-source AI platform Hugging Face, which provides access to thousands of pretrained AI models that can be downloaded and run locally. With over 10 million users, getting started on the site can be a daunting task. Thomas explains how the company aims to improve its accessibility through documentation on the company blog as well as community feedback, similar to social media likes and upvoting. Thomas and Sam discuss the benefits and trade-offs of both open-source and closed-source AI models, as well as the evolution of microchips and the future of hardware and software development — as well as the hopes Thomas has for the future of coding with AI, starting with his children's generation. Read the episode transcript here. Guest bio: Thomas Wolf is cofounder and chief science officer of Hugging Face, a collaborative AI platform. Wolf likes creating open-source software (OSS) that makes complex research, models, and data sets widely accessible. He can also be found pushing for open science in research in AI and machine learning, to try lowering the gap between academia and industrial labs through projects like the BigScience Workshop. He also writes and produces education content on AI, machine language, and natural language processing, including the reference book Natural Language Processing with Transformers, The Ultra-Scale Playbook, his blog, and videos. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

David is the founder of Strategy Shift. He's worked with more than 50 CEOs and hundreds of other C-suite executives to design bold strategies, supercharge their leadership, and transform their cultures in 20 countries. He's a contributor to Harvard Business Review, MIT Sloan Management Review, and Strategy+Business, and a guest lecturer at London Business School. He is a former senior partner at Strategy&, PwC.In today's episode of Smashing the Plateau, you will learn actionable strategies for navigating major career transitions and aligning your work with your values and aspirations.David and I discuss:What prompted David to leave his senior partner role and start something new [01:48]The role of personal needs and values in career decisions [04:13]How to adopt a strategic approach to career pivots [04:56]The importance of building a supportive, challenging network [06:24]Why making small decisions can energize bigger changes [07:21]The value of not rushing your transition [08:15]How to navigate career strategy in times of chaos and complexity [10:38]Advice for consultants facing indecision and radio silence from clients [14:21]What CEOs and leaders really need from consultants today [16:24]How to tap into and nurture a community of thinking partners [20:19]Where to find David's resources and get in touch [22:57]Learn more about David at:• Strategy Shift: https://strategyshift.co.uk/• Profile: https://strategyshift.co.uk/founder/• Newsletter: https://davidlancefield.com/newsletter/• Courses: https://strategyshift.co.uk/courses/• Writing: https://davidlancefield.com/writing/• Lancefield on the Line Podcast: https://davidlancefield.com/lancefield-on-the-line/• https://strategyshift.co.uk/media/Thank you to Our Sponsor:The Smashing the Plateau CommunitySubscribe now to receive expert strategy tips—unlock your next level of success with every episode!

Hone: How Purposeful Leaders Defy Drift by Geoff Tuff, Steven Goldbach https://www.amazon.com/Hone-Purposeful-Leaders-Defy-Drift/dp/1394304536 A clarion call to business leaders to recast their conception of leadership and strategy execution to meet the demands of the modern world Have a problem with your organization's strategy in an era of accelerating, exponential change? Modern business orthodoxy has an easy answer: transform it. Hone: How Purposeful Leaders Defy Drift argues this thinking is itself in need of an overhaul. Rather than devote time to expensive, long, and often unsuccessful transformations, leaders should instead focus on holistically designing and honing the management systems that are the nervous systems of their businesses. They can take a cue from chefs and other artisans and hone their organizations. After all, honing doesn't sharpen knives; it realigns a knife's steel to its original position. Choosing and honing the set of management systems that promote an organization's desired outcomes (and uninstalling them when they are past their prime) is one of the most important things a business leader can do―and is just as much art as science. The third in a trilogy of business strategy books written by renowned strategists and two-time Thinkers50–nominated authors Steven Goldbach and Geoff Tuff, this book explains why and how to optimally hone your organization's execution of its strategy, with highlights including: The importance of recognizing and taking action to defy the drift that often afflicts organizations undergoing massive transformation Guidelines on how to design and continually reshape effective management systems to influence organizational and individual behaviors Reframing the job of CEOs to be Chief System Designers for their organizations Reflections on how honing principles within organizations can be used on broader societal challenges such as addressing climate change via the energy transition Engaging, pragmatic, and inspiring, Hone: How Purposeful Leaders Defy Drift earns a well-deserved spot on the bookshelves of all private, public, and nonprofit sector professionals seeking to bring new sources of advantage to their organizations in a time of accelerating uncertainty and exponential change.About the author Geoff Tuff is a globally recognized thought leader and widely sought-after speaker and writer on the subjects of strategy, growth, innovation, and adapting business models to deal with change. He and his co-author, Steve Goldbach, have written two bestselling books – Detonate (Wiley 2018), and Provoke (Wiley 2021). Their latest book, Hone: How Purposeful Leaders Defy Drift, will be released on September 30, 2025. Both Detonate and Provoke were recognized by Thinkers50, the leading authority on management thinking, with award nominations for strategy and leadership. Geoff's writing has also appeared in journals such as Harvard Business Review and MIT Sloan Management Review and as a regular contribution to HuffPost. Finally, he and Steve are two of the hosts of "The Provocateurs", a monthly leadership podcast based on the book Provoke. About the author Steven Goldbach is a globally recognized strategist and executive advisor, combining creativity and rigor to help organizations create their own future. Together with Geoff Tuff, Steve has co-authored two bestselling books – Detonate (Wiley 2018), and, Provoke (Wiley 2021). Their latest collaboration, Hone: How Purposeful Leaders Defy Drift, will be released in late September, 2025. Both Detonate and Provoke were recognized by Thinkers50, the leading authority on management thinking, with award nominations for strategy and leadership. Steve is one of many rotating hosts of "The Provocateurs", a monthly podcast based on the book Provoke. It features leadership lessons from leaders from all a variety of disciplines.

Today's episode is a bonus drop from our friends over at the MIT CSAIL Alliances podcast. We'll be back on September 16 with new episodes of Me, Myself, and AI. Chris Miller is professor of international history at Tufts University. He joins the MIT CSAIL Alliances podcast to share insights from his recent book, Chip War: The Fight for the World's Most Critical Technology. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the executive producer is Allison Ryder. Stay in touch with us by joining our LinkedIn group, AI for Leaders at ⁠mitsmr.com/AIforLeaders⁠ or by following Me, Myself, and AI on ⁠LinkedIn⁠. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Marc Zao-Sanders reveals the key to breaking the cycle of overwhelm with a power tool that makes a huge difference.— YOU'LL LEARN — 1) How to prune your to-do list effectively2) How to use timeboxing to plan your day with intention3) The art of choosing breaksSubscribe or visit AwesomeAtYourJob.com/ep1071 for clickable versions of the links below. — ABOUT MARC — Marc Zao-Sanders is the CEO and co-founder of filtered.com, a learning tech company. He regularly writes about algorithms, learning and productivity in Scientific American, Harvard Business Review and MIT Sloan Management Review. He has followed the practice of timeboxing for over ten years. He lives in London. • Book: Timeboxing: The Power of Doing One Thing at a Time by Marc Zao-Sanders • Podcast: The ADHD Skills Lab Harvard Business Review Article: "How Timeboxing Works and Why It Will Make You More Productive"• LinkedIn: Marc Zao-Sanders • Website: MarcZaoSanders.com — RESOURCES MENTIONED IN THE SHOW — • Study: "Implementation Intentions and Goal Pursuit" by Peter M. Gollwitzer and Veronika Brandstätter • Article: “To-Do Lists Don't Work” by Daniel Markovitz• Book: The Fountainhead by Ayn Rand• Book: The ONE Thing: The Surprisingly Simple Truth About Extraordinary Results by Gary Keller and Jay Papasan• Book: Eat That Frog!: 21 Great Ways to Stop Procrastinating and Get More Done in Less Time by Brian Tracy• Book: Winning the Week: How To Plan A Successful Week, Every Week by Demir Bentley• Past episode: 038: Establishing the Essential with Greg McKeown• Past episode: 080: Finding and Doing the One Thing with Jay Papasan• Past episode: 2024 GREATS: 935: The Five Steps to Winning Every Week with Demir Bentley— THANK YOU SPONSORS! — • Strawberry.me. Claim your $50 credit and build momentum in your career with Strawberry.me/Awesome• Quince. Get free shipping and 365-day returns on your order with Quince.com/Awesome• Plaud.ai. Use the code AWESOME and get a discount on your order• Rula. Connect with quality therapists and mental health experts who specialize in you at Rula.com/AwesomeSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Why do we so often work incredibly hard without seeing the results we want?   The answer lies not in our effort, but in how we design that effort.  Drawing from an insightful MIT Sloan Management Review study on leadership development programs, this episode reveals 3 critical mistakes that prevent both organizations and individuals from achieving meaningful growth. These same principles explain why many of us struggle to reach personal and professional goals despite genuine commitment.  The first fatal flaw?... tune in to find out!  With this powerful framework you'll ensure your valuable time and energy create the future you truly desire, rather than simply keeping you busy with tasks that ultimately lead nowhere.  Are you just doing things, or are you designing efforts that add up to something meaningful?    Text Me Your Thoughts and IdeasSupport the showBrought to you by Angela Shurina Behavior-First Change Leadership & Culture Transformation ConsultantEXECUTIVE & OPTIMAL PERFORMANCE COACH

Most leaders agree that culture drives performance – but too often, it's reduced to a values exercise rather than a measurable, strategic asset. The reality is that negative workplace behaviours are among the strongest predictors of attrition, reputational damage and productivity decline. And in many cases, the warning signs are visible long before the damage becomes public.In this episode, we're joined by Charlie Sull – a globally recognised expert in corporate culture and AI. As co-founder of CultureX and a regular contributor to MIT Sloan Management Review, Charlie draws on one of the world's largest workplace culture datasets to help organisations decode what's really happening inside their walls – and take action where it matters most.He shares why culture must be measured and managed with the same rigour as financial or operational performance, and how AI is transforming the way we understand workplace dynamics.Thank you to HR Partner for sponsoring this season. If you want to explore a simple HR solution that streamlines your HR admin, you can book a demo today: https://bit.ly/4dAYxugSHOW NOTESLearning:Learn how to understand the basics of generative AI for HR with this short course from AHRI: https://bit.ly/40221k4Explore CultureX's thought leadership and culture champion profiles: blog.culturex.comConnect:Connect with Charlie on LinkedIn: https://bit.ly/4kTMV8HConnect with AHRI on LinkedIn: https://bit.ly/4kAaLWJAHRI members can join the AHRI LinkedIn lounge, exclusive to AHRI members to discuss some of the themes explored in this episode with their HR peers and access bonus content. Become a member today: https://bit.ly/41tcOFu

Julian Adams tried but didn't succeed at retirement after a productive career as a medical chemist with several U.S. Food and Drug Association approvals of cancer-related treatments, including cell therapy for bone marrow transplantation. Soon after, his participation in a Stand Up To Cancer advisory group led to his appointment as the nonprofit's president and CEO. The research organization raises money to advance the diagnosis of numerous cancers. Given rapid technological advancements, our podcast hosts were eager to invite Julian on the show to share how Stand Up To Cancer uses artificial intelligence to aid in this pursuit. Read the episode transcript here. For more information on Stand Up To Cancer and how to donate to the organization, please visit this website. Guest bio Julian Adams, president and CEO of Stand Up To Cancer, is among the world's foremost oncology researchers. He was previously CEO of biopharmaceutical company Gamida Cell and president of R&D at Infinity Pharmaceuticals, where he oversaw development of small molecule drugs to treat cancer. He has also held roles at Millennium Pharmaceuticals, Boehringer Ingelheim, LeukoSite, and ProScript. Adams's recognitions include the 2012 Warren Alpert Foundation Prize for his role in the discovery and development of bortezomib, an anti-cancer drug; the 2012 C. Chester Stock Award Lectureship from Memorial Sloan Kettering Cancer Center; and the 2001 Ribbon of Hope Award for Velcade from the International Myeloma Foundation. He holds more than 40 patents and has authored more than 130 papers and book chapters. He received his bachelor's degree and an honorary doctor of science degree from McGill University and his Ph.D. from MIT in synthetic organic chemistry. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the executive producer is Allison Ryder. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

In this episode, Bob ‘n Joyce dive into how to create and sustain organizational resiliency—a must-have competency in today's fast-changing business world. We kick things off with a little game we call “learning.” First, we share our personal and professional takes on what makes a workplace truly resilient. Then, in the next episode, we'll check in with the experts at MIT Sloan Management Review to see how our perspectives stack up. Some of the ideas we unpack today: • Getting real about the challenge • Community – We are ‘in this' together • Focusing on excellence and winning • Embracing risk—and yes, learning from failure So grab a snack, pull up a chair, and join the conversation. And hey, we'd love to hear your take on resiliency too.

What You'll Learn:In this episode, hosts Shayne Daughenbaugh, Andy Olrich, and guest Steve Spear discuss the evolution of industry, emphasizing the importance of cultural shifts driven by Lean thinking. They interview Steve Spears, a senior lecturer at MIT Sloan, who highlights the role of innovation in organizational transformation.About the Guest:Steve Spear is a senior lecturer at MIT Sloan, founder of the software firm See to Solve, and author of Wiring the Winning Organization (with Gene Kim) and The High-Velocity Edge. His work, featured in Harvard Business Review, MIT Sloan Management Review, and The New York Times, focuses on solving complex organizational challenges through innovation, systems thinking, and technology.Spear's ideas have shaped product design at Pratt & Whitney, accelerated pharma development cycles, and optimized operations at firms like Intel, Alcoa, and DTE Energy. He has advised the U.S. Army's Rapid Equipping Force and the Navy's Chief of Naval Research, aiding in tech deployment and operational innovation.Links:Click Here For Steve Spear's LinkedInClick Here For "See to Solve" Website

Josh Weiner, senior vice president of consumer engagement and analytics at CVS Health, is passionate about making health care more personalized, connected, preventative, and accessible. On today's episode, Josh joins Sam and Shervin to explain how the integrated health care company is structured and how it is using AI to achieve those goals. Read the episode transcript here. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the executive producer is Allison Ryder. Guest bio At CVS Health, where Josh Weiner is the senior vice president of consumer engagement and analytics, his priority is personalizing consumer experiences and developing the health care company's app. Previously, he was a health care leader at Meta, where he supported product development, algorithm engineering, and acquisitions. He was also a senior analytics expert at McKinsey and Co. Weiner is a board member at nonprofits Enduring Hearts and Docs for Tots. He holds a bachelor's degree from Carnegie Mellon University and a master's from Northwestern University. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

If you're feeling like you're ready for that corporate board seat but keep getting overlooked, then you are not alone! It's frustrating to see others land those opportunities while you're left wondering what's holding you back. Maybe you've been networking, applying for positions, or even serving on non-gov committees, but still not seeing the results you want. It's time to break free from the cycle of missed opportunities and finally get the recognition and opportunities you deserve. Let's unravel the mystery and unlock those boardroom doors together! Dr. Keith D. Dorsey is a seasoned board member, researcher, and speaker specializing in guiding executives toward corporate board service. His book, The Boardroom Journey, offers actionable strategies for leaders seeking their first or next corporate board seat. Keith's insights have been featured in leading publications, including Harvard Business Review, MIT Sloan Management Review, Directors & Boards, Forbes, and Fast Company, where he writes extensively on leadership, governance, and board effectiveness. Keith is a member of the Private Directors Association and National Association of Corporate Directors Certified Director and was recognized as an honoree of the 2023 NACD Directorship 100TM, an annual recognition of 100 leading corporate directors and corporate governance experts who impact boardroom practices and performance. He serves as a board member at Vimly Benefit Solutions, a private technology and third-party administration company; Continu, a private learning management system SaaS company; Pepperdine University's Graziadio Business School, Pacific Crest Trail Association; and the Chair of the City of La Quinta's Financial Advisory Commission. Former Board Member, Orion Talent is a talent acquisition firm. Keith holds a Doctorate in Organizational Change and Leadership from the University of Southern California. The key moments in this episode are:00:00:02 - Introduction to A World of Difference Podcast 00:00:49 - Importance of Cognitive Diversity in Boardrooms 00:01:23 - The Boardroom Journey for Women 00:02:28 - Overcoming Barriers to Board Service 00:03:51 - Landing a Board Position 00:16:19 - The Power of Networking and Visibility 00:18:44 - Unconscious Bias and Gender Disparities 00:23:18 - Diversity, Equity, and Inclusion 00:26:11 - Systemic Challenges and Building Stronger Pipelines 00:31:54 - Breaking Gender Narratives in Boardrooms 00:32:27 - Assessing Board Member Competencies 00:35:07 - Strategic Interviewing for Board Positions 00:36:21 - The Importance of Strategic Thinking in Board Interviews 00:38:04 - Embracing Multiple Perspectives in Board Appointments Share this episode with five people in your network who could benefit from the insights and strategies shared in this conversation. Start a conversation with them about leadership and making a difference together. Purchase Dr. Keith D. Dorsey's book The Boardroom Journey to gain valuable insights and strategies for securing a corporate board seat or expanding board opportunities for women. The book provides practical advice and actionable steps for aspiring board members. Connect with us: https://www.aworldofdifferencepodcast.com Linkedin YouTube Substack FaceBook Instagram Threads Patreon (for exclusive episodes just for Difference Makers) Bluesky TikTok Subscribe to the podcast, leave a review, and share this episode with someone who might need to hear it. Your support helps the community grow and keeps these important conversations going. If you need professional help, such as therapy: https://www.betterhelp.com/difference If you are looking for your next opportunity, sign up for Lori's Masterclass on Master the Career Pivot: https://www.loriadamsbrown.com/careerpivot Learn more about your ad choices. Visit megaphone.fm/adchoices

Many of us know Goodwill Industries International as a retailer that accepts and resells donated goods. What the average consumer may not know is that the nonprofit takes in over 5 billion pounds of goods each year — and not all of it can be resold. For those unwanted or unviable items, the organization can either look into recycling or upcycling, and with the help of AI, it's able to efficiently make that determination while also improving its process for sorting and allocating sellable goods for different retail channels. Additionally, Goodwill helps its workforce with career-development skills. Much of this training has been enhanced with AI. Tune in to this episode to hear directly from Goodwill CEO Steve Preston about how the organization is using technology to fulfill a mission that extends beyond the retail store. Read the episode transcript here. Guest bio: As president and CEO of Goodwill Industries International, Steven C. Preston leads a network of 153 local Goodwill organizations with a combined revenue of $8.2 billion. In addition to being a secondhand retail leader, Goodwill is a leading nonprofit provider of workforce training and development in North America. Positioning the organization at the forefront of workforce development has been a top focus for Preston since he joined Goodwill in 2019. He has also forged partnerships with organizations focused on sustainable practices in the secondhand retail marketplace and developed mission-focused marketing efforts to elevate the Goodwill brand. Previously, Preston served in numerous operational and financial leadership positions in both the public and private sectors. After heading the U.S. Department of Housing and Urban Development and the Small Business Administration, he led successful turnarounds as the CEO of Oakleaf Global Holdings and Livingston International. He also served as the CFO of Waste Management and ServiceMaster. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the executive producer is Allison Ryder. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

BEST OF In the face of uncertainty and change, how do you ensure you don’t feel lost and defeated? More importantly, how do you ensure that doesn’t happen to the team you lead? Dr Gabriella Rosen Kellerman is the Chief Innovation Officer at BetterUp and she sees firsthand their cross discipline research into what can be done to help human flourishing. Professionally she advises Fortune 500 CEOs and CHROs and contributes regularly to Harvard Business Review, MIT Sloan Management Review and Scientific American Mind, Her book Tomorrowmind, co-authored by Professor Martin Seligman provides research on how to navigate the never-ending cycles of change and unprecedented uncertainty that we are all facing in the present working climate. In this episode Gabriella shares: Her tricks on how you can bring creativity into your workforce Why you need to help your team develop their own sense of meaning if you want them remain with you long term. How to build resilience and use it to survive uncertain times and challenging times Why prospection is a key skill for every leader who wants to grow their teams trust How to master the stories you tell yourself to turn setbacks into growth Key Quotes: “Prospection, our ability to see and plan for the future is an essential part of what builds peoples trust in leaders today." "Recognition is an antidote and it's almost a vaccine for a crisis of mattering." “Resilience doesn't mean that it doesn’t feel incredibly painful and challenging and you may cry and scream and be furious." Find Gabriella’s book via her website or connect with her on Linkedin. My latest book The Health Habit is out now. You can order a copy here: https://www.amantha.com/the-health-habit/ Connect with me on the socials: Linkedin (https://www.linkedin.com/in/amanthaimber) Instagram (https://www.instagram.com/amanthai) If you are looking for more tips to improve the way you work and live, I write a weekly newsletter where I share practical and simple to apply tips to improve your life. You can sign up for that at https://amantha-imber.ck.page/subscribe Visit https://www.amantha.com/podcast for full show notes from all episodes. Get in touch at amantha@inventium.com.au Credits: Host: Amantha Imber Sound Engineer: Martin ImberSee omnystudio.com/listener for privacy information.

In today's episode, Chandra Kapireddy, head of generative AI, machine learning, and analytics at Truist, delves into the evolving landscape of AI with a particular focus on how GenAI tools reshape the way Truist and similar organizations must navigate model risk management and regulations. GenAI is more versatile than traditional AI, he notes, yet its flexibility introduces new challenges around ensuring model reliability, validating outputs, and making sure that AI-driven decisions don't lead to unfair or opaque outcomes. Chandra's responsible AI approach at Truist is focused on risk mitigation while emphasizing the importance of human oversight in high-stakes decision-making. He points out that while GenAI can vastly improve productivity by handling repetitive or analysis-heavy tasks, it's essential to properly train employees in order to use the tools effectively and not over-rely on their outputs, especially given their tendency to hallucinate or produce inaccurate results. Read the episode transcript here. Guest bio Chandra Kapireddy is head of generative AI, machine learning, and analytics, at Truist. He brings over 27 years of experience building and leading world-class data, analytics, and artificial intelligence teams to the financial services firm. Kapireddy has held key leadership positions at some of the industry's leading companies, including Capital One, Wells Fargo, Bank of America, Oracle, and Amazon Web Services. Most recently, he served as managing director and head of AI/ML products for JPMorgan Chase, where he served on the firm's AI Executive Council, which influences its strategy, products, controls, and governance. Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the executive producer is Allison Ryder. Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.