Let's talk Transformation : The business leaders podcast copertina

Let's talk Transformation : The business leaders podcast

Let's talk Transformation : The business leaders podcast

Di: Suzie Lewis
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A proposito di questo titolo
 "Let's talk Transformation" is a podcast for busy yet curious leaders and executives who want to stay ahead of the curve and relevant in the age of AI. Join strategic yet practical conversations with experienced leaders ready to vulnerably share knowledge & learnings. You will be able to operationalise these insights and immediately apply with your team & peers to drive more inclusive & collaborative environments for sustainable transformation & innovation in the workplace and beyond. Hosted by Suzie Lewis, bilingual & bicultural, holding over 20 years of transformation experience in different sized organisations. Her approach is systemic, working on invisible dynamics to improve the quality & speed of decision making and creating a culture of learning. https://transformforvalue.comCopyright 2026 Suzie Lewis Economia Gestione e leadership Leadership Management
Episodi
  • #195 Who Leads, Us or the Machine? STEM Identity in AI with Dr Jennifer Berry

    #195 Who Leads, Us or the Machine? STEM Identity in AI with Dr Jennifer Berry
    Nov 2 2026
    Who is leading, us or the machine ?Jennifer and I explore why durable skills, hands-on learning, and cross-generational dialogue matter as AI reshapes how we think, work, and lead.We look at case studies where leaders are willing to let AI decide budget, strategy and genuinely anything else that makes their job easier. Nobody had checked the numbers. Nobody had weighed the trade-offs. A piece of human judgment had quietly moved into a software tool, and often leaders don't notice until someone asks the right question.That moment captures the central tension of our time. AI offers speed, scale, and polish. But speed and polish can crowd out the slower work of thinking, questioning, and owning a decision. Skills matter, but identity matters first. Jennifer describes STEM identity as three beliefs: “I belong here. I add value. I can master rigorous challenges.”Those three beliefs shape how people respond to difficult problems. A young person who believes she/he belongs will raise a hand. A professional who believes his/her ideas add value will speak up in a meeting. Without those beliefs, even talented people stay silent.Many current leaders built these beliefs the hard way. They failed, tried again, and earned their seats through persistence. The concern now is what happens when AI takes over the tasks that once built that confidence.Convenience can weaken the very skills it promises to support. SmartLab responds to this risk with a deliberate design choice. Students do not begin with AI. They begin with a problem, a set of materials, and a team. They build something, and it often fails. Students then have to diagnose the problem, talk with teammates, and try again. Those moments build resilience, communication, and critical thinking in ways that a screen cannot replicate.These are what Jennifer calls durable skills. Unlike tactical skills, which change with each new tool, durable skills last. They include communication, systems thinking, computational thinking, collaboration, and the ability to recover from failure. SmartLab measures these skills with a rubric that facilitators complete after each project. The aim is not to reward a correct answer. The aim is to show measurable growth in how a student thinks and works with others.Today’s workplace may include five generations at once. Each one brings different relationships with technology. These differences can become strengths. When generations talk openly about how and when to use AI, each one sharpens the others. Younger workers question shortcuts. Older workers remember the value of struggle, and together, they can build norms for responsible use.Human connection also needs deliberate attention. Many people, especially younger ones, now turn to AI before they turn to a colleague. They avoid looking foolish. They avoid the risk of being wrong in front of others.Organizations cannot afford to wait for schools to produce ready-made talent. Companies that depend on innovation need employees who think critically, collaborate well, and adapt quickly. Those skills take years to develop.Businesses need to act now in three ways. First, they can invest in schools by sending employees to mentor students or sponsoring a SmartLab in a classroom. Second, they can build internal training around durable skills. Third, they can use those same skills as criteria when hiring.Return to the question that started this conversation. Who is leading, us or the machine?The answer depends on choices made every day. Leaders can ask for raw thinking before polished output. Parents can protect time for play. Businesses can invest in young people before they walk through the door. Schools can teach students to build, fail, and try again.AI will keep getting faster. Human judgment, curiosity, and courage will decide how we use it. Those qualities are not automatic. They must be built, practiced, and protected.If you lead a team, a family, or a classroom, start small. Ask one person for their own answer before the screen provides one. Notice what emerges. That moment of effort may be the most valuable thing you do all day.The main insights you'll get from this episode are :STEM identity for children: I belong, I add value, I can master rigorous challenges. Durable skills for the AI age = strong communication, deep distance thinking, computational thinking, critical thinking, flexibility, mastering failure.Soft skills are required to lead in an AI-powered world, but the CEOs of the future born into the digital age have fewer social/human skills.Personal opinion matters even more in an AI environment – the maxim must be ‘think first, then use AI’ because faster doesn’t always mean better.Hands-on, project-based learning is more critical than ever but needs to be ‘manufactured’ these days for children.Generational problem-solving differences are magnified by the speed of AI; gen Alpha will hopefully challenge AI, trust it less, and be more cautious.SmartLab has ways...
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    40 min
  • #194 The Achiever's dilemma in the AI era with Nick Petrie

    #194 The Achiever's dilemma in the AI era with Nick Petrie
    Oct 26 2026
    "They wanted to perform, but they wanted to do it in a healthy way that they could sustain for decades"The modern workplace demands more, faster, and better results every single day, and AI is increasing the speed. Nick and I examine how professionals grapple with overloaded systems that fail to support human flourishing : Relentless workloads, constant change, and blurred boundaries create high levels of stress and burnout.Many organizations treat these pressures as inevitable costs of doing business. Yet, the traditional formula of pushing through no longer serves modern professionals. Sustainable performance requires a new approach to daily work habits.Organizations often define resilience as pushing through exhaustion regardless of the personal cost. Companies reward workers who say yes to every request and maintain zero boundaries. While this strategy works early in a career, it fails to scale over decades. High performers eventually hit a wall where constant grinding leads to physical and mental exhaustion. Evolving the professional approach becomes necessary as job demands and responsibilities increase. Sustainable success requires balancing high output with long-term health and well-being.Studying high performers reveals a tiny group of individuals who combine high output with very low burnout risk and Nick researched their habits, mindsets and perspectives to ascertain how they did this.Thrivers possess a high degree of reflectiveness and self-awareness regarding their working habits. When Nick reached out to these busy executives for research interviews, they responded promptly and made time to talk. They recognize early in their careers that relentless grinding leads to diminishing returns. Instead of reacting to every demand, they design structured rhythms into their daily routines. Their ability to step back and evaluate their operating systems protects them from the heavy toll of chronic stress. We look more closely at :The Power of Pulsing and Daily Rhythms - Nature operates on steady rhythms like breathing, heartbeats, and changing seasons. Human workers often abandon these natural rhythms by locking into a single mode of high intensity for hours. thrivers incorporate pulsing into their daily schedules.Crossing the Karman Line: Transitioning Home : Space shuttles encounter extreme thermal and kinetic pressure during atmospheric reentry. NASA engineers use precise maneuvers to slow the spacecraft down before it crosses the Karman line. Without this deceleration, the shuttle experiences uncontrolled reentry and structural failure. Human workers often behave like the unmitigated spacecraft. They maintain high operational speed throughout the workday, take business calls during the commute, and burst through home doors while still mentally at the office.Shifting From Doer to Grower : Many professionals define their personal worth entirely through individual task execution. Earning recognition and status by doing everything oneself creates a dangerous dependency loop. Plant managers and corporate leaders often find themselves answering emergency calls at three in the morning. This reliance on personal heroics acts as a severe handbrake on long-term professional growth.Navigating the AI Era Without Burning Out : Artificial intelligence promises massive productivity gains for modern organizations. However, the introduction of AI agents often accelerates the workplace treadmill instead of creating breathing room. Professionals face constant context switching as they manage multiple automated workflows simultaneously. Without careful boundaries, AI fills every available gap in the daily schedule.Designing Conditions for Deep Work : Uninterrupted focus remains scarce in organizations dominated by back-to-back meetings and constant notifications. Deep work requires sixty to ninety minutes of intense concentration on complex, high-value tasks. Most professionals crave this focused environment yet struggle to find the necessary time.Burnout rarely stems from a single isolated trigger. It accumulates through heavy workloads, internalized pressure to endure, and minds that refuse to disconnect. The AI era threatens to amplify these exhaustion cycles unless professionals exercise intentional agency. Adopting sustainable habits requires stepping away from the daily dance floor and viewing the system from the balcony. Professionals must evaluate whether their daily routines involve healthy pulsing or destructive grinding.The main insights you'll get from this episode are :Thrivers’ take time (out of their busy schedules) to think, reflect and talk.Long-term performance and success require rest and a more holistic approach.Thriving needs a scalable strategy that evolves with different situations/roles.Intentional ‘pulsing’ – as opposed to the daily grind – is reminiscent of the rhythms of nature. A daily ‘calming line’ is also helpful as a tool to dissipate energy, control re-entry, and ...
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    49 min
  • #193 Scale AI Adoption Safely and sustainably with Denis O'shea

    #193 Scale AI Adoption Safely and sustainably with Denis O'shea
    Oct 19 2026
    Getting your information architecture for AI right is 10 times more important than onboarding the newest, shiniest AI model.Denis and I look at how to bridge the tech and generational gap that is only getting wider as AI scales at incredible speed. We look at the tech gap, the human gap, AI agent governance, and strategies for successful workplace transformation.Back in 2003, people were carrying advanced phones and using them only for basic calls and texts. Today, the exact same gap appears with artificial intelligence. Technology arrives finished and packaged, while people adopt it slowly or not at all. The distance between these two realities determines whether workplace transformation succeeds or fails.Workforce cohorts approach artificial intelligence differently. Younger workers, particularly Gen Z, experiment freely, build agents, and push boundaries and when they encounter friction in the systems they will work around them quite easily.. Older generations tend to stick to basic tasks and follow strict rules. This generational divide creates both friction and opportunity within modern organizations.Organizations often rush into software rollouts without proper preparation. We discuss five essential foundations that companies must establish before scaling their artificial intelligence initiatives. Skipping these foundational steps leads to runaway costs, security breaches, and zero measurable return on investment.Document use cases and workflowssecure and classify dataProvide role specific trainingBuild Agent infrastructure and governanceEstablish financial tracking and ROI measuresThe information architecture acts as a pyramid. At the base sits all unstructured organizational data, including emails, messages, and documents. At the apex sits a control plane that defines security policies, user identities, and data classification labels. Software models sit in the middle, inheriting security controls from the top while reasoning over data at the bottom.Getting this architecture right is far more important than collecting various trendy tools.Technology implementation ultimately comes down to human behaviour, and transformation requires humility from all generations. Older workers possess deep institutional knowledge, strategic context, and governance experience. Younger workers bring natural fluency with modern software and automation techniques. Bridging the tech gap requires genuine collaboration between these groups.Organizations must foster environments where experienced staff listen to digital natives, and digital natives respect structural guardrails. By combining institutional context with modern technical agility, businesses can build a sustainable hybrid workforce. The transformation window is short, and intentional design remains the only path to lasting success.The main insights you'll get from this episode are :2003: investment and advancement in tech racing ahead of the consumer in terms of adoption and use.2026: same happening with AI – younger generations need to lead the older ones in the AI era, which is a first and requires humility.Gen Z will upend data security using shadow AI to find ways around constraints; Gen X are very compliant because they understand the dangers.Gen Z are the first generation in the workforce with no recollection of 9/11 therefore they have a different mindset re security and privacy (social media).Happy path is to have tools for Gen Z to work productively in our organisations, remove friction and provide onboarding assistance.Gen Alpha/Gen A(I) only know work and study with AI; organisations need a combination of institutional knowledge and innovative thinkers.AI agents now with autonomy, capable of morphing, creating other agents, rogue behaviour, behaving like humans (e.g. collaboration, hierarchy, communication).Current designs lack guard rails, governance, and data readiness.AI spend is problematic with charges for tokens and access via APIs; measuring ROI on AI means understanding ‘a day in the life of’ roles to tailor it accordingly.Use case analysis with priorities -> secure data -> training (generic best-practice and role-specific) -> permissions for agents -> ROI calculator for use of tools.Some issues likely to still be problematic in three years’ time, e.g. data security, governance, rogue agents, risk, and spend.Governments are disinclined to regulate AI, giving organisations a brief window in which to create guard rails and governance before it happens anyway.Leaders tend to be infatuated with the latest model instead of questioning the right IA (information architecture) for AI.Dirty data at the bottom of the pyramid, control plane at the top, models in the middle.No safe, sustainable long-term solution will arise from a multi-vendor tech stack.Find out more about Denis and his work here :https://www.linkedin.com/in/denisosheamobilementor/https://www.mobile-mentor.com/https://www.denisoshea.com/For more information on this episode ...
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    43 min
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