Podcast
The Digital Transformation Playbook
Hosted by Kieran Gilmurray · EN
Kieran Gilmurray is an Internationally acclaimed expert in leadership, AI, strategy and transformation.
He helps boards, executive teams and senior leaders make sense of complex technological change and turn it into practical business value.
Most experts make technology feel more complex. Kieran makes complex ideas simple, useful and actionable.
He has worked with leadership teams across the globe to help them understand AI, use data to make better decisions and apply technology in ways that improve performance.
The outcome is clearer thinking, stronger leadership confidence, better adoption and more measurable business benefit from technology.
Kieran and his team bring the practicality many thought leaders lack, the human clarity large consultancies often miss, and the strategic depth that goes beyond standard AI training.
If your organisation is trying to digitally transform and make AI useful, safe and commercially relevant, then connect.
📅 Book a call: https://calendly.com/kierangilmurray/catch-up
🌎 Website: www.KieranGilmurray.com
📘 Kieran Gilmurray | LinkedIn
🌐 Substack: https://kierangilmurray.substack.com
📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK or Audible https://www.audible.com/search?keywords=kieran+gilmurray
Kieran
284episodes
Episodes
Newest firstAll episodes
AI Does Not Scale Through Tools. It Scales Through Work
Jul 700:11:33Tap to summarizeAI adoption is moving quickly, yet enterprise value remains uneven when tools are added without changing how work flows. This episode examines why scalable AI performance depends on workflow redesign, clear ownership, and stronger execution systems. It explores the Work layer of The Human AI Operating System.TLDR / At a Glance• Workflow as the unit of change • Task gains versus enterprise value • End-to-end execution redesign • Ownership, handoffs, and judgement points • Workflow-level success measures • Alignment across decisions, capability, governance, and valueThe key takeaway is that AI scales when organisations redesign how work gets done, measure outcomes across workflows, and connect execution to the wider operating model.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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Discussing AI Is Not the Same as Governing It
Jul 600:12:18Tap to summarizeAI has moved from innovation briefing to board-level responsibility, affecting strategy, risk, disclosure and enterprise value at the same time. This episode examines why directors must shift from discussing AI to actively governing it as regulatory, investor and value pressures converge. It explores the practical tests boards can use to assess real AI oversight.TLDR / At a Glance• Board ownership of AI • Strategy, risk and disclosure alignment • EU AI Act readiness • Ownership, visibility and assurance • Investor expectations on AI governance • Value creation through disciplined oversightThe key takeaway is clear: AI governance is now central to board accountability, confidence and durable business value.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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Reshape the Work Before You Reduce the Workforce
Jul 200:13:41Tap to summarizeAI is forcing leaders to rethink work before they make irreversible workforce decisions. This episode challenges the headcount-first response to automation and explains why value depends on redesigning how work flows.It explores how AI changes roles, judgment, trust and organisational capability.TLDR / At a Glance• Work redesign before workforce reduction • Productivity versus realised value • The Reshape Sequence • Verification as the new bottleneck • Human trust in AI-enabled service • Junior roles and leadership pipelinesThe quickest way to get AI wrong is to make it a headcount story. We keep hearing the same boardroom question surface within minutes: “How many people can we let go?” It feels rational when generative AI is expensive and ROI pressure is high, but it puts the hardest and least reversible decision first, right when the work is still changing shape.We argue that AI’s first and most consequential impact is on workflow design, not workforce size. When machines take on routine drafting, triage, and summarising, the job is not simply smaller. Tasks get rebundled, handoffs move, and new responsibilities appear around prompting, review, correction, and AI governance. That is why productivity is easy to generate but harder to convert into real value: unless the operating model changes, time saved leaks away instead of becoming customer impact, quality, or margin.We share a clear four-step “reshape sequence” for leaders: redesign the workflow, redefine the human role, rebuild the surrounding system (controls, incentives, career paths, measures), and only then resize. Along the way, we dig into why verification becomes the new bottleneck, why customer trust makes skilled human support more valuable, and why cutting junior roles can quietly break the pipeline that produces future judgement.The key takeaway is that leaders should redesign workflows, redefine human roles, rebuild systems and resize only when the new shape of work is clear.If you’re building an AI strategy, use this as a practical guide to redesign work, redeploy people, and avoid capability cuts you will regret. Subscribe, share with a colleague, and leave a review telling us where AI is reshaping your work most right now.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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Middle Management Meltdown: Are They Breaking?
Jul 100:39:00Tap to summarizeMiddle managers get blamed for everything, yet we keep setting them up to fail. Kieran Gilmurray and Laura Lawless promote smart, capable people into leadership roles, then pile on performance management, feedback, meetings, reporting, and “just one more responsibility” without ever teaching the fundamentals or redesigning the job. No wonder even experienced managers admit they avoid the hard conversations until they absolutely have to.TL;DR / At a Glancewhy capable managers avoid performance and feedback conversationsdefining what a manager is responsible for nowreframing “soft skills” as operating skills that make work workwhy “better communication” often means clearer thinking and decisionsAI changing the value of writing versus judgementmoving from one-off workshops to practice loops and habitsHR shifting from process owner to capability builderthe time problem and the case for slowing down to speed upstrategic subtraction using technology to remove low-value workthree practical takeaways for leaders and HR teamsKieran Gilmurray and Laura Lawless unpack what a manager is actually for today: getting work done through other people, developing the team, and removing obstacles rather than being the hero-doer. From there, they dig into the skills that really move performance, engagement and retention. “Better communication” sounds obvious, but we challenge it: more messages do not fix unclear priorities, vague decisions, or inconsistent expectations. As generative AI starts drafting emails and feedback, the human edge becomes clearer thinking, sound judgement, and the courage to be direct.Then Kieran Gilmurray and Laura Lawless get practical about leadership development and HR transformation. They argue for replacing tick-box training with operating standards for meetings, feedback and decision making, plus simple practice loops that build habits in real work. Kieran Gilmurray and Laura Lawless also debate time, coaching culture, and strategic subtraction: if AI can do the admin, managers should not be doing it, and HR should stop being the fixer and start building capability across the business.If you know the pain of meeting overload and constant “more”, this conversation will help you see what to remove, what to standardise, and what to practise so managers can lead well again. Subscribe, share with a manager who needs this, and leave a review with the one task you would subtract first.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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Who Owns AI?
Jun 3000:13:09Tap to summarizeAI ownership often looks clear in meetings, then breaks down when decisions move into real workflows. This episode examines why fragmented authority turns promising pilots into slow, duplicated, and politically complex AI programmes across the enterprise.It explores how decision rights shape AI scale.TLDR / At a Glance• Fragmented AI accountability • Decision rights over job titles • Centralised, federated, and hybrid models • Governance without slow consensus • Executive sponsorship and escalation routes • Ownership maps for enterprise scaleThe key lesson is that AI scales when authority, accountability, and value ownership are explicit.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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Is HR Obsolete?
Jun 3000:31:01Tap to summarize“HR is irrelevant and AI will replace it” is the sort of claim that gets repeated until it feels true. We slow it down and ask a better question: if the admin and compliance bits are automated, what should a modern people function actually do that makes organisations stronger?TL;DR / At A Glanceretiring transactional HR work that technology can automatewhy rebranding HR does not fix purpose, trust, or credibilityemployee trust gaps and the case for advocacy or ombuds rolesshifting people management back to leaders with HR as architectthe leadership capability gap in coaching, feedback and difficult conversationsAI in performance feedback and why AI plus human coaching mattersredesigning jobs for humans and AI, not just adding toolsmoving HR metrics from compliance to organisational capabilityWe pull apart the case for retiring the term HR and the case for keeping it, from the Ulrich model to today’s rebrands like People Ops and employee experience. Then we get into the real issue behind the labels: trust. Many employees assume HR represents the organisation first, which creates a credibility gap. We explore whether advocacy and ethics roles should sit outside HR, and what that means for fairness, transparency, and day-to-day employee experience.From there, we go straight at the uncomfortable fix: leaders must own people management. That only works if we stop promoting accidental managers and start building leadership capability in feedback, coaching, and difficult conversations. Finally, we debate AI and performance feedback. AI can be candid and consistent, but it cannot replace human judgement and empathy, so we argue for “AI plus a human coach” and, crucially, redesigning jobs for humans and AI rather than layering more tech onto broken work.If you want a practical, future-of-work conversation about people strategy, agentic AI, organisational design and leadership development, press play.Subscribe, share with a colleague, leave a review, and tell us in the comments: should we retire HR, or reinvent it?Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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Hiring In The Age Of AI
Jun 2900:44:18Tap to summarizeAI is speeding up work, squeezing budgets, and quietly removing the “starter tasks” that used to train new hires. So the real question is not just whether we should hire graduates, but how anyone builds experience when AI can draft, summarise, and analyse faster than a junior role ever could. We take a hard look at what this means for early careers, recruitment, and long-term workforce planning, especially for organisations chasing quarterly results while trying to stay future-ready.TL;DR / At A Glancebroadening from graduate hiring to workforce diversity and capabilitywhy digital fluency is not determined by ageAI, agency, and the potential mental health impactthe gap between what we say, what is heard, and what we meanadapting to different communication styles beyond picking a channelusing AI as a coaching tool for clearer stakeholder communicationthe real skills gap: onboarding, financial fluency, data and AI literacy, curiosity, resiliency, communicationpsychological safety as the condition for challenge and growthcapability swaps and pairing by strengths rather than ageKieran Gilmurray and Laura Lawless also push back on the lazy comfort of generational stereotypes. “Gen Z are digital natives” sounds neat until you see who is genuinely excited to learn, who is anxious about losing agency to algorithms, and who has the curiosity to keep improving. We talk about mental health risks, why learning agility beats age, and why a multi-generational workplace works best when leaders focus on capability, not labels.From there Kieran Gilmurray and Laura Lawless get practical: how communication breaks down between what we say, what people hear, and what we meant, plus how to adapt to different styles without dumbing anything down. We explore psychological safety as the foundation for healthy challenge, then move into concrete team design ideas like capability swaps and cognitive diversity roles (challenger, translator, integrator). Finally, we unpack why microlearning often fails and how to build continuous learning into the flow of work so skills actually stick.If you care about AI in the workplace, hiring strategy, learning and development, and building high-performing teams, this conversation is your reset. Subscribe, share it with a colleague, and leave a review with one change you are making this month to help your team learn faster and speak up more.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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Why Faster AI Answers Can Make You Learn Less
Jun 2800:19:49Tap to summarizeFrictionless AI feels like a miracle: one prompt, instant answers, spotless work. But when we use large language models for learning, that same “no effort” design can become a trap. Google Notebook LM agents break down the learning performance paradox, where AI can make you look brilliant in the moment while quietly preventing the mental work that builds memory, judgement, and real competence. If you have ever “understood” something with AI help and then blanked the next day, you will recognise what we mean. TL;DR / At a Glancethe learning performance paradox and why speed can mask absent learningcognitive offloading and metacognitive laziness in AI-assisted studyproductive struggle, desirable difficulty, retrieval practice and the generation effectscaffolding done right through hints, worked examples and calibrated challengeConMigo and CodeHelp as contrasting designs for preventing shortcut learningadaptive AI that captures microinteractions to model misconceptions and emotionsshared regulation to protect learner autonomy and avoid black box tutoringresponsible foundations: explainable AI, privacy-by-context and inclusive personasGoogle Notebook LM agents explore what a true AI learning companion should do differently, grounded in learning science: productive struggle, desirable difficulty, retrieval practice, and the generation effect. Instead of handing over solutions, the companion should ask you to explain, apply, and generate answers in your own words. It should also help with metacognitive calibration, so your confidence starts matching your actual understanding, not just the smoothness of the chatbot’s output. From there Google Notebook LM agents get practical, using real case studies. We look at ConMigo’s shift from strict Socratic tutoring to smarter scaffolding with hints and worked examples, and CodeHelp’s “sufficiency check” that trains students to troubleshoot by providing proper context. Google Notebook LM agents also unpack adaptive learning systems that remember your patterns over time, why shared regulation protects autonomy, and what responsible AI in education requires: explainable recommendations, privacy that fits the learner, and inclusive design that reflects diverse classrooms and lived experience. If you care about AI in education, learning how to learn, or building skills that last, listen now.Subscribe, share with a friend who relies on AI to study, and leave a review with the biggest change you are making to your prompts.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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The Human AI Operating System
Jun 2200:22:07Tap to summarizeAI scale depends on more than access to models, pilots, or new tools. This episode examines why enterprise performance comes from designing the organisation around AI, rather than simply deploying technology into existing workflows.It explores the Human AI Operating System as a framework for repeatable AI value.TLDR / At a Glance• Five-layer AI operating model • Workflow redesign for adoption • Decision rights and accountability • Capability beyond basic training • Embedded governance and controls • Value tracking linked to outcomesThe central takeaway is that AI scales when work, decisions, capability, governance, and value operate as one aligned management system.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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The AI Risk Posture Playbook for Boards
Jun 2000:12:01Tap to summarizeArtificial intelligence is now a board level risk with implications across strategy, operations, and reputation. Organisations must move from informal awareness to structured oversight to manage AI responsibly.This episode explores how boards define and operationalise an explicit AI risk posture.TLDR / At a Glance• AI as enterprise level risk category • Risk appetite, tolerance, capacity distinctions • Board versus management responsibilities • Red line AI use cases • Escalation thresholds and governance flows • 30, 60, 90 day implementation roadmapA clear AI risk posture enables controlled innovation while maintaining accountability, resilience, and regulatory readiness.Support the show𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/results-not-excuses✉️ kieran@gilmurray.co.uk 🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn🦉 X / Twitter: https://twitter.com/KieranGilmurray📽 YouTube: https://www.youtube.com/@KieranGilmurray📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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