The Digital Transformation Playbook

Kieran Gilmurray

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+gilmurrayKieran

  1. 1d ago

    The Costly AI Mistake: Chasing Copilots, Not Workflows

    AI is changing management by shifting attention from supervision to orchestration. The real value comes from redesigning workflows, decisions, capabilities, and accountability around AI-enabled work. This episode explores how leaders can redefine management as routine coordination becomes increasingly automated. TLDR / At a Glance • Supervision giving way to orchestration • Workflow redesign as the value driver • Five-part Orchestration Stack • Rising skill demands in junior roles • Governance as a management responsibility • Exception handling and decision ownership Flattening structures without redesigning management risks relocating friction rather than removing it, while deliberate orchestration creates clearer accountability and stronger AI-enabled performance. Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    The Costly AI Mistake: Chasing Copilots, Not Workflows

  2. 4d ago

    Measuring What Actually Matters: The Value Layer of AI Scale

    AI adoption is rising fast, yet many organisations still struggle to prove real business value. This episode examines why activity metrics can create confidence without showing whether AI is improving performance. It explores the Value layer of AI scale. TLDR / At a Glance • Activity versus value  • Stronger AI measurement chains  • Output quality and workflow performance  • Business outcomes and economic impact  • Risk adjusted value metrics  • Workflow level evidence The key takeaway is that AI becomes defensible when leaders can connect usage to measurable performance, financial impact, and controlled risk. Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    Measuring What Actually Matters: The Value Layer of AI Scale

  3. 4d ago

    Finance: Powerful Decision Engine, Not Passive Scorekeeper

    Finance has spent most of its life perfecting the art of looking backwards, but AI is forcing a sharper question: what if the finance function exists to decide what happens next, not just to report what already happened? We make the case that using AI to close faster is only a small win, and often a distraction from the bigger prize: faster, better decisions on pricing, capital allocation, working capital, risk signals, and scenario planning. This episode explores how finance can move from scorekeeper to decision engine. TLDR / At a Glance • Decision speed and quality • Sense, predict, judge, act • Trusted finance data • Human accountability • AI Auditability • Forecast accuracy measurement We break down a simple, practical model for an AI-enabled finance decision engine: sense, predict, judge, act. AI strengthens sensing and prediction by turning live signals into analysis at speed, but we are clear about the boundary: judgement stays human, because accountability cannot be outsourced to a model. That shift changes the skills finance needs, moving the centre of gravity from preparation towards challenge, narrative, and commercial decision-making. We also tackle the hard constraints that stop teams from getting measurable value from AI in finance and FP&A. Trusted data is the bottleneck, not the model, and poor definitions create “confident errors”. We explain how to build a minimum trusted data foundation for a specific decision, then scale from there. Finally, we cover why controls, audit evidence, and decision-quality measurement are not red tape but the mechanisms that create trust and let AI move into material work. If you want practical guidance on how CFOs and finance leaders can redesign the loop, choose the right decisions to rebuild, and measure what matters, listen now. Subscribe, share with a finance leader who’s stuck in pilot mode, and leave a review with the one decision you would want 10% faster or sharper. AI creates the possibility, but leadership design turns finance transformation into measurable business value. Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    Finance: Powerful Decision Engine, Not Passive Scorekeeper

  4. Aug 8

    From Copilots to Workflows: Where AI Value Actually Sits

    Enterprise AI often delivers measurable productivity gains without producing meaningful financial impact. The missing value is usually lost across handoffs, decisions, rework, capacity allocation, and weak measurement. This episode explores why workflow redesign determines whether AI improves organisational performance. TLDR / At a Glance • Task productivity versus enterprise value • Five points of workflow leakage • End-to-end process redesign • Agentic automation and orchestration • Human judgement and decision rights • Outcome-based performance measures AI creates greater value when leaders redesign workflows, clarify accountability, and measure business outcomes instead of adoption.  Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    From Copilots to Workflows: Where AI Value Actually Sits

  5. Aug 5

    The Governance Problem: How AI Scales Without Losing Control

    AI governance becomes critical when experimentation turns into operational scale. This episode examines how organisations can grow AI use while maintaining control, trust, and momentum. It explores governance as execution infrastructure. TLDR / At a Glance • AI scale and operating control  • Weak governance risks and rollback  • Excessive approval friction  • Trust as a deployment constraint  • Runtime monitoring and escalation  • Risk tiering, ownership, and review Effective AI governance gives leaders enough clarity, accountability, and confidence to move into higher value use cases safely.  Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    The Governance Problem: How AI Scales Without Losing Control

  6. Aug 4

    Beyond Rebranding HR: Building People Strategy That Performs

    Job titles are getting a makeover, but most workplaces still feel stuck. We get honest about why renaming HR to People Strategy or People and Culture often backfires: if the work, expectations, and operating model stay the same, the function loses credibility and leaders stay frustrated. What we actually want is a clear signal that the organisation is drawing a line in the sand and redesigning for performance in the era of AI. TL;DR / At A Glance: • rebranding HR as a signal only when behaviours and systems change • people strategy, business strategy and technology strategy as one joined model • future skills that stay constant alongside AI literacy and data judgement • role clarity and updated expectations as the foundation for performance • hiring and managing for outputs rather than clinging to job titles • workflow mapping to decide what to automate and what must stay human • HR business partner model shifting into consulting and diagnosis • limits of self-service and why empathy still matters at work We unpack the future skills people need now, not five years from now. Yes, AI literacy matters, but we also call out the capabilities that never stopped being essential: communication, curiosity, resilience, systems thinking, analytical decision making, and financial literacy. We talk about why AI is “lifting the lid” on gaps that were already there, and why quality control of AI output and critical thinking are becoming non-negotiable human skills as automation expands. Then we get practical: stop starting with a grand HR transformation and start by mapping one real workflow end to end. We explore hiring and managing for outputs rather than titles, what the HR business partner role should look like as a consulting and diagnostic partner, and where self-service and automation should stop so employee experience does not collapse at the moments that matter.  If you care about HR transformation, people strategy, AI at work, and building high-performing teams without overloading your managers, you will leave with a sharper model and clear next steps.  Subscribe, share this with a people leader who needs it, and leave us a review, then reply with your take: what would you rename, and what would you redesign first? Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    Beyond Rebranding HR: Building People Strategy That Performs

  7. Aug 3

    Why Professional Services Need Human-AI Operating Systems

    Professional services firms have moved AI into legal, audit, tax, and advisory workflows, yet most still struggle to convert adoption into measurable value. The central challenge is redesigning how work is produced, reviewed, priced, governed, and learned. This episode explores why a human-AI operating system is becoming a durable source of advantage.  TLDR / At a Glance • Adoption versus firm capability  • Six operating model pressure points  • AI-driven apprenticeship redesign  • The eight-part Delivery Spine  • Governed knowledge and quality controls  • Pricing, measurement, and client trust Sustainable AI value depends on building an integrated operating model around technology, professional judgement, and accountability. Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    Why Professional Services Need Human-AI Operating Systems

  8. Jul 31

    When AI Fails Mental Health

    A chatbot can feel like a kind listener, but that warmth can become a hazard when someone is vulnerable. I’m joined by consultant psychiatrist Dr. Hina Tahseen to look at what it actually looks like when AI gets mental health wrong and why the most dangerous failures are often subtle, confident, and persuasive rather than obviously “broken”. TL;DR / At A Glance • why AI errors in mental health can sound plausible and caring • a suicide related failure pattern and why escalation matters • how mania can be validated by chatbots and why that is dangerous • what clinicians notice beyond words and why history matters • the case for a mandatory human layer for diagnosis, risk, and treatment plans • what to look for in safer tools including regulated medical devices and NHS use • how AI can help clinicians with research, admin, scribes, and medication timelines • why mental health presentations vary and do not match textbook prompts • privacy risks when sharing intimate mental health data and how prompts get “tweaked” • where to seek help in the UK including NHS 111 option 2 and Samaritans We unpack real scenarios, from suicidal thinking to classic mania, where a general purpose LLM may validate and energise the worst possible next step. Dr. Hina Tahseen explains how clinicians assess far more than the text on the screen: behaviour, congruence of mood, intoxication, collateral history, safeguarding, and patterns over time. That leads us to a simple principle for AI in mental healthcare: a human layer is mandatory for diagnosis, risk stratification, and treatment plans, even if AI can help gather information or triage. We also cover the genuine benefits of AI for access and capacity, including support for people facing stigma, isolation, and cost barriers, and the practical upside for clinicians using AI scribes and summaries to regain time and eye contact. Finally, we tackle AI governance, regulation, and privacy, because mental health data is deeply intimate and users often do not realise how exposed it can be. Subscribe, share this with someone who uses chatbots for wellbeing, and leave a review.  What rule do you think should be non negotiable when AI touches mental health? Support the show If you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.   🌎 Website: www.KieranGilmurray.com 📅 Book a call: https://calendly.com/kierangilmurray/catch-up 📘 Kieran Gilmurray | LinkedIn 🌐 Substack: https://kierangilmurray.substack.com 📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK  AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified.

    When AI Fails Mental Health
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About

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+gilmurrayKieran

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