Kieran Gilmurray's Recent LinkedIn Posts

Progress outperforms perfection every time. That is even more true in artificial intelligence. AI creates a new temptation. Because the tools are powerful, we assume the output must be immaculate before it is shared. We tweak prompts, regenerate drafts. Then we refine tone and optimise structure. It feels rigorous, it feels responsible and it feels like leadership. But sometimes it is simply a safer place to stay. Instead of deploying the AI workflow, testing the use case, or putting the prototype in front of a team, we remain in prompt editing mode because it gives us control. In plain terms: refining the prompt can look like progress, but it can delay the moment where the market, the board, or the customer reacts. With AI, value is only created when it is applied. If you are waiting to finish the model properly or get the prompt perfect, you are postponing the only moment that matters: when the tool is used in a real workflow with real constraints. I learned this before AI, running my first weekly leadership meeting. For the first month, I rewrote my meeting notes three times, refined transitions and I replaced words that were already clear. The result was simple. Two dull and delayed sessions and then momentum stalled. Nothing was wrong with the thinking. What was missing was cadence. Everything shifted when I imposed a constraint on myself. Forty five minutes. One draft. Deliver it. The standard did not collapse. My thinking did not degrade but what changed was my throughput. The same principle applies to AI adoption. The teams that win are not those with the most elegant AI strategy decks. They are the ones running live pilots, learning from imperfect outputs, and iterating in the open. Each time you deploy an AI use case, you get feedback faster. You see where the data or code breaks. You understand where human oversight is required. You build confidence and trust as you ship and learn. One applied AI use case leads to the next and momentum builds. Here is what progress over perfection looks like in AI practice: • Deploy the use case that solves 80 percent of the problem • Set a fixed time limit for prompt refinement • Test outputs in a real workflow, not a sandbox forever • Track live experiments each month, not theoretical roadmaps • Treat in production as the standard Leadership in the age of artificial intelligence is not shown by how polished your AI strategy document looks. It is shown by how consistently you move AI from concept to execution. Run this for 30 days. Choose one AI use case you have been discussing. Set a non negotiable deadline. Reduce the scope if needed. Deploy it with guardrails. You will learn more from one imperfect live deployment than from ten flawless internal drafts. The question is not whether the AI output is flawless. The question is whether it is delivering value. What AI initiative are you still refining that should be piloted this month? #ProgressNotPerfection #AILive

I have just released a preview of Chapter 13 of my new book. This is the fourth book in my Masterclass Series on AI. Chapter 13 focuses on the next challenge after pilots: how to scale AI so it consistently delivers business value. AI adoption is widespread, yet meaningful financial impact remains concentrated among a small group of companies running multiple scaled use cases. Many organisations experiment with isolated tools or pilots but struggle to turn them into sustained results. This chapter explains why scaling AI requires an operating model, not just more technology. It outlines how to run AI as a program with clear governance, feedback loops, decision gates, and a roadmap that prioritises the right domains first. The goal is simple: move from scattered pilots to a disciplined system that scales outcomes while keeping risk, cost, and performance under control. The full book is now live on Amazon. You can read the Chapter 13 preview and access free chapters here: https://lnkd.in/ea_Runq3 Repost to help someone in your network ♻️

Most people want to be seen as AI leaders. Yet very few are building other AI leaders. There is a difference. Knowing how to use artificial intelligence well does not make you a leader. It means you are skilled. If you can write effective prompts, test new tools, run pilots, and build a clear strategy deck, that shows you understand the space. But leadership begins when those capabilities no longer depend on you. In many organisations, one person becomes “the AI person”. They attend the courses. They experiment with tools. They present the roadmap. Every question about AI flows back to them. But if everything AI depends on one individual, your AI program will slow or stop the moment they step away. That is not transformation, that is concentration of knowledge. And that is not cool. You are not an AI leader until other people can run pilots without you. Until a manager can identify and shape a use case. Until someone in operations can test a workflow and measure results. Until a team can challenge a vendor proposal with confidence. If every meaningful AI decision still escalates to you, you are the expert. If capability is spreading across teams, you are the leader. That requires a deliberate mental shift. Less time refining your own prompts. More time teaching others how to think with AI. Less focus on showcasing what you built. More focus on building shared standards, guardrails, and confidence. AI leadership is not about being the smartest person in the room. It is about making sure the room does not need you to move forward. Here is a simple test. If you stepped away for 90 days: Would experimentation continue? Would new use cases still be launched? Would someone else step forward and take ownership? If the answer is no, your next priority is not another pilot, it is AI capability transfer. In practice, that means: • Giving others ownership of live AI initiatives • Asking managers to design and present their own AI use cases • Creating simple operating principles that everyone can apply • Rewarding initiative and learning, not just polished prompted outputs • Measuring how many people are actively using AI, not how good your slides look The competitive advantage will not come from one AI champion. It will come from distributed competence. You only become an AI leader when you produce other AI leaders. Who in your organisation can now lead without you? #LeadershipIsHard

At a recent AI Strategy 2030 discussion in Kuala Lumpur I hosted for Stravix Group, one issue kept popping up: If AI capability is compounding every year, should strategic planning cycles shrink? The honest answer is: it depends. Disruption does not hit every sector at the same speed. Energy and infrastructure operate on long asset cycles. Healthcare moves within regulatory guardrails. Financial services and media feel margin pressure almost immediately. So cadence should reflect exposure and risk. But industry is only part of the story. Capability maturity matters more. McKinsey & Company research shows many organisations pilot AI. Few industrialise it. The barrier is rarely model quality. It is operating model design, leadership ownership, and talent integration. This is where CAPs matter. By CAPs, I mean the proprietary capabilities and assets that create durable advantage. Unique data. Embedded workflows. Domain expertise. Decision systems that compound over time. AI is not strategic because it exists. It is strategic when it strengthens your CAPs. That reframes the debate. The real question is not how fast AI is moving. It is whether you are redesigning your capability stack around it. Three disciplines follow: AI must tie directly to economic levers. Revenue, cost, risk, capital efficiency. Business leaders must own outcomes. Technology enables, P&L drives value. Your operating model must match your ambition, whether AI first or fast follower. General Electric understood this decades ago through structured capability building and its Change Acceleration Process. Technical design alone never delivered results. Adoption, leadership alignment, incentives, and reinforcement did. AI is no different. Data governance is non negotiable. Talent models must evolve. Ethical clarity must be explicit. Capital allocation must become more dynamic. By 2030, leaders will not be those who experimented the most. They will be those who aligned ambition, operating model, and capability building into a coherent AI enabled system. AI advantage is not a race. It is a test of internal coherence and disciplined execution over time. Thank you to my exceptional panel members for their challenge, excellent insights and expert knowledge - Dato’ Dr. Munirah Looi, Datin Dr. Ts. Habsah Nordin (CDMP, CSFC, CAITL™) and Dr. Sekar Jaganathan, DBA, PhD (Mgmt), ICDM, Strategy 2030 created a trusted space for that conversation to take place, among leaders actively building what comes next. If you would like me to host your exclusive event in a capital city of your choice, then direct message me and my team will connect us. #AIStrategy #AILeadership #Strategy2030 #DigitalTransformation #OperatingModel #BusinessStrategy

AI alone will not define 2030. Convergence will. This article explores how artificial intelligence is colliding with quantum computing, IoT, and advanced robotics, and why that convergence will reshape industries faster than any single technology wave. It examines the economic scale behind the shift, with AI projected to contribute $15.7 trillion to global GDP by 2030 and IoT enabling trillions more in annual value. It also looks at how AIoT, edge computing, smart factories, and autonomous robotics are already moving from pilot to system level transformation. The piece then addresses the quantum frontier and policy momentum, from the EU’s 2030 quantum strategy to the US CHIPS and Science Act, and what this means for leaders planning across regions. The central message is strategic. Advantage will not sit in isolated tools. It will sit in systems that combine sensing, intelligence, compute, and automation into scaled capability. ♻️ Share this to help someone in your network #ArtificialIntelligence #QuantumComputing #IoT #Robotics #TechStrategy

I have just released a preview of Chapter 11 of my new book on Agentic AI. This is the fourth book in my Masterclass Series on AI. Chapter 11 tackles one of the most critical leadership decisions in AI: build, buy, or adopt a hybrid model for agentic systems. Over 80% of AI projects fail, and abandonment rates for generative AI pilots are rising. Poor data, weak governance, talent gaps, and unclear business value continue to stall initiatives before they reach measurable impact. This chapter reframes the choice. You are not selecting a tool. You are selecting your probability of success. Early architectural decisions shape cost, risk, time to value, and long term competitive advantage. It introduces a practical framework across urgency, capability, budget, and strategy, along with common DIY failure patterns and a phased hybrid path that ships value while building internal capability. The full book is now live on Amazon. You can read the Chapter 11 preview and access free chapters here: https://lnkd.in/ea_Runq3 Repost to help someone in your network ♻️ #ArtificialIntelligence #BuildVsBuy #EnterpriseAI

'Don’t be nice to me. Instead tell me what I need to hear'. That sentence has saved me months of wasted effort over the years. Because 'nice' feedback is usually just social lubrication that keeps the other person happy. It keeps things pleasant but it keeps things very BROKEN. The most valuable people in my career weren’t the ones who cheered. Instead they were the ones who support me fully and said the awkward thing early. Like: 'You’re not being clear.' 'Your deck is clever, but it isn’t convincing.' 'You’re avoiding the hard decision.' 'This is a distraction dressed up as progress.' It usually stings for about ten minutes but then it pays back for years. Brutal honesty isn’t the goal, useful honesty is. If you want people to tell you what you need to hear, you have to make it safe for them to do so and ask them to be specific. A few lines I’ve learned to use (and mean): - What am I pretending not to know? - If you were responsible for this outcome, what would you change? - Where is this weak? - Please don’t soften it for me. I can take it. And when someone does give you the truth don’t debate it. Don’t explain it away. Just say, 'Got it, please tell me more.' Nice is easy but useful takes courage (from both sides). When was the last time someone told you something you didn’t want to hear, but needed to? Ps. If you need AIs help ask it to Act as your contrarian partner. Ask it to act as 5 experts and debate your issue. #Leadership #HighPerformance

Have you seen my new exciting website? https://lnkd.in/e47_4AkJ Today I am launching my new website. Not a redesign but more a reset. Over the past few years my work has evolved. From AI building to board level strategy. From speaking about technology to helping leaders use it properly. The new site reflects that shift. Clearer thinking. Sharper positioning. You will find: • Strategic AI advisory • Executive education for boards and C suites • Practical tools leaders can use immediately • Real case studies, not theory • Interviews and podcasts with leading experts Artificial intelligence is not the story. Competitive advantage is. The website is built around one simple idea: Strategy, artificial intelligence, and capital allocation shape long term value. If you are exploring AI seriously, not just piloting tools but embedding capability, I would value your thoughts. #ArtificialIntelligence #Strategy #Boards #CapitalAllocation #Leadership

Is HR here to manage AI risk or to redesign the business for AI value? Most organisations are still treating AI as a policy issue. Usage guidelines. Acceptable use statements. Risk controls. Important? Yes, of course. Sufficient? Not even close. The real question is not whether AI creates risk - it does. The real question is who is redesigning the operating model to capture value. That is where HR becomes central. Are people less valuable in the age of AI? Or are judgement, oversight, orchestration and accountability now more critical than ever? AI can write, design, code, and prepare at speed.  It can triage and even code itself but it cannot own outcomes. It cannot carry reputational risk. It cannot align work to strategy. That is still human. Unless a business manages AI change properly and ties together talent strategy, technology capability, business and capital allocation strategy, it will stall. AI sitting in isolation inside IT will fail. AI adopted informally by teams without redesign will fragment. AI layered on top of yesterday’s structure will underdeliver. Think of it as a three legged stool. Talent. Technology. Business model. Each leg must be shaped deliberately. Each leg must be aligned. If one is weak, the whole thing tips over. The organisations pulling ahead are not asking “How do we control AI?” They are asking: • Which roles change first? • Where does headcount reduce or redeploy? • How do we measure AI augmented performance? • Who owns AI enabled decisions? That is not a compliance conversation. That is a strategic one. HR has a choice. Be the function that writes the policy or be the function that redesigns the future of work. Which side are you on? #HRStrategy #HRandAI #ExecutiveEducation #BusinessTechTalent

Most organizations are experimenting with AI, very few are getting real business results. That's exactly why I wrote how to Build an Agent, The Leader's Playbook for Coding and Deploying AI that Delivers Real Business Results. This is not a book about prompts. It's not a book about hype. It's a practical playbook for leaders who need AI systems that actually work inside of real organizations. In this book I will explain what Agentic AI is, how it differs from chatbots and simple automation, and how to design digital workers that can plan, act, integrate with CRM and ERP systems and deliver measurable return. You will learn when to build, when to buy, how to govern safely, how, to measure ROI in a way the boards respect, and how to run a four week pilot that produces decision grade evidence. This is about moving from demos to deployment, from experimentation to execution. AI adoption is no longer the challenge. Leading AI is if you're responsible for outcomes, not just ideas. This book is your field manual. How to Build an Agent, The Leader's Playbook for Coding and Deploying AI that Delivers Real Business Results, is now available on #Amazon and #Audible globally. 🌏 https://lnkd.in/eaVSZAMf #AgenticAI #Boards #ROI #NotAIThreatre #Autonomous #Playbook

If AI keeps turning into theatre where you work, this conversation hands you the script for real AI advantage. We go straight to the hard truths: AI only multiplies what already exists. With a clear strategy, AI accelerates outcomes. Without one, it scales confusion, risk, and busywork. My interview with Kristof, a global expert in learning capability strategy and AI enablement, focuses on unpacking what actually drives success. It addresses why AI adoption can lead to decreased judgment, and the tendency for organizations to implement tools before scaling their strategic thinking, which is crucial for effective ai strategy. Together we map the shift from tool chasing to operating models: visible ownership from leaders, crisp problem framing, rigorous verification, and trust built through behaviour. You’ll hear how to turn leaders into customer zero, select champions who influence across silos, and design an engine that translates curiosity into daily workflow gains. We dig into planning that sticks - simple goals, defined decision rights, and communication that lowers fear instead of inflating hype. Expect a practical blueprint, not platitudes. The full interview in now available on my Spotify, Apple Podcasts and YouTube channels. #BuildingCapability

AI won’t fix a messy Microsoft 365 tenant. It will simply scale the mess. CoreView’s research across 500 IT leaders shows: • 81% say managing Microsoft 365 is already a major operational burden • 1 in 3 have faced incidents caused by configuration mistakes • Nearly half lack clear visibility into access and changes Before AI, fix the foundations. • Guardrails. • Least privilege access. • Humans in control. That is how AI actually works in Microsoft 365. Download the 2026 State of AI in Microsoft 365 report to see what IT leaders are doing differently - https://lnkd.in/e5aYVgKq   Delighted to get the opportunity to contribute to this key report. #M365 #Microsoft365 #CoreViewPartner #Ad #Guardrails CoreView

If your brand is not in the answer, you are not in the market. Article 3 of our GEO Series is now live. This article explains how generative search is reshaping brand visibility, SEO, and revenue, and why ranking on page one no longer guarantees you will be seen. AI answers now decide which brands are included at the moment of decision. That choice is based on your reputation across the web, not just your website. We have also released the full 8 part GEO Series to help you adapt, showing how to secure citations, strengthen authority, and protect visibility as search moves to AI-first. Alongside the series, you can access our GEO Self Audit and service to understand where you stand today and what to fix first. Access the full series and GEO audit here: https://lnkd.in/etiDJS8z ♻️ Share this to help someone in your network

Research has shown a negative correlation between frequent AI use and critical thinking abilities, with one study indicating that cognitive outsourcing reduced independent problem-solving by 35%. The sources describe a risk of cognitive atrophy when learners outsource the "intrinsic cognitive work" of learning. Because critical thinking is deeply dependent on a well-organized foundation of domain-specific knowledge stored in long-term memory, bypassing the acquisition of this knowledge leaves students with nothing to think critically about. The "fluency" of AI-generated output, the fact that it is confident, coherent, and articulate, creates an illusion of competence. This leads to "metacognitive laziness," where learners mistake the ease of using the tool for actual understanding and abdicate their own responsibilities for planning, monitoring, and revising their learning. This creates a vicious cycle of dependency: • A learner seeks efficiency and uses AI to complete a task. • The fluent output creates a false sense of mastery. • This triggers laziness, leading to more outsourcing. • The learner's actual knowledge base erodes, making them more dependent on the tool and less capable of judging the accuracy of its future outputs. While a learner might achieve high marks on a specific assignment using AI, their durable learning suffers once the tool is removed, as they have not consolidated the mental structures necessary for expertise and intuitive mastery. So, are you using AI to help you learn and learn deeply (cognitive mirroring)? Or are you using it an as answer oracle mistaking AI-generated output for learning competence? How are you ensuring AI enhances rather than replaces thinking in your organization? #AnswerOracle #MetaCognition #DeepLearning

I’ve felt quietly guilty about one thing for years: my content wasn’t accessible enough to those who have difficulty reading text. Not because I didn’t care but because time kept winning. So over the last lot of weeks, I’ve been training an AI model on my voice. Not a generic “podcast voice” but my actual voice. Now every article I publish will also have an audio version, and it’ll be distributed properly on Spotify, Apple Podcasts, BuzzSprout, plus 10 other podcast channels Two small but important choices: 1) Every article will include a link to the audio version 2) Every audio version will link back to the written article So you can read, listen, switch mid-way, or share whichever format suits you. It’s not me but it’s a huge step towards my desire to be “open by default”. If you’ve made your work more accessible, what’s the one change that made the biggest difference? #Accessibility #ContentStrategy #AI #Podcasting #Accessible

The biggest barrier to AI in Microsoft 365 is not capability. It is trust. CoreView’s research across 500 IT leaders shows: • 51% of organisations have rolled back an AI decision that put their environment at risk • 53% say AI is being pushed on them faster than they can govern it • 55% report a growing divide between leadership ambition and frontline readiness AI adoption is not just a technology rollout. Governance first. Automation second. Download the 2026 State of AI in Microsoft 365 report to see how IT leaders are closing that gap - https://lnkd.in/e5aYVgKq Delighted to get the opportunity to contribute to this key report. #M365 #Microsoft365 #CoreViewPartner #Ad #Guardrails

Most “AI music videos” are slick… and emotionally empty. This one wasn’t. It’s basically a note about self-forgiveness. And that’s the bit that surprised me: the tech didn’t feel like the point. The story did. Not perfect and not “human” but close enough that I stopped analysing and just… watched. Which raises the question I can’t shake: If the human story is real, and the emotion is real, does it matter that the pixels are synthetic? Or do we only call it “real” when we can point to a camera, a set, and a day-rate? Credit where it’s due: source is the very talented Christian Fleischer. Where do you draw the line between “synthetic” and “real” in creative work? #AIVideo #GenerativeAI #CreativeTools #MusicTech #Storytelling

Most AI programmes show no ROI and it is rarely because the AI model is not good enough. The real problem is this: AI is launched as a technology initiative, when it actually needs to be run as an operating change. If you want AI to deliver measurable value, three things must happen. 1. Lock ROI into the design, not the review. Before any build starts, get clarity on: • The process being improved • The single metric that must move • The person who owns that metric A global CEO survey found only around one quarter of AI initiatives met ROI expectations. In many cases, value was never clearly defined upfront. New York Life has spoken publicly about approving AI projects only if they were clearly linked to operational metrics tied to their earnings plan. If the link was weak, the project did not proceed. That discipline filters out noise early. 2. Redesign your workflow(s) so the AI output triggers action. Do not ask whether the model works. Ask what happens differently on Tuesday morning because it exists. Before building anything, answer four practical questions: • Where does the AI output land? • Who is expected to act on it? • Which decision does it change? • What happens when it is uncertain or wrong? Many pilots stall because the output never becomes part of day to day work. In fraud detection, for example, models flag risk but operations teams continue using old triage processes. No workflow change means no value capture. 3. Install short checkpoints with pre-agreed stop rules. AI programmes often fail slowly because no one decides when to stop. A large share of initiatives are abandoned after pilots, often after months of drift and sunk cost. Time box the work. Define success upfront. Review early. Be willing to pause or reshape if the numbers do not move. Palo Alto Networks has described applying this discipline in internal IT automation. • Narrow pilots. • Defined checkpoints. • Scale only when adoption and resolution time improve. • Miss the threshold, and funding stops. The biggest long term risk is not wasted spend. It is training the organisation to believe AI never delivers. If that belief sets in, your next initiative fails before it starts. If you need my help starting or rebooting your AI program, then leave a message and my team will connect us. #AI #AIAdoption #DigitalTransformation #Leadership #Strategy

Most organizations are experimenting with AI, very few are getting real business results. That's exactly why I wrote how to Build an Agent, The Leader's Playbook for Coding and Deploying AI that Delivers Real Business Results. This is not a book about prompts. It's not a book about hype. It's a practical playbook for leaders who need AI systems that actually work inside of real organizations. In this book I will explain what Agentic AI is, how it differs from chatbots and simple automation, and how to design digital workers that can plan, act, integrate with CRM and ERP systems and deliver measurable return. You will learn when to build, when to buy, how to govern safely, how, to measure ROI in a way the boards respect, and how to run a four week pilot that produces decision grade evidence. This is about moving from demos to deployment, from experimentation to execution. AI adoption is no longer the challenge. Leading AI is if you're responsible for outcomes, not just ideas. This book is your field manual. How to Build an Agent, The Leader's Playbook for Coding and Deploying AI that Delivers Real Business Results, is now available on #Amazon and #Audible globally. 🌏 https://lnkd.in/eaVSZAMf #AgenticAI #Boards #ROI #NotAIThreatre #Autonomous #Playbook

AI budgets are rising but executive fluency is not. That gap is becoming one of the biggest strategic risks I see in boardrooms all over the world. Across sectors, leaders are approving AI investments without a clear view of how AI reshapes competitive advantage, cost structure, or capital allocation. The conversation often sits at the level of tools. It rarely reaches operating model design or economic impact. The research is remarkably consistent. McKinsey & Company highlights that scaling failure is rarely about model performance. It is about leadership ownership, governance, and integration into core processes. Bain & Company has emphasised that AI advantage accrues to firms that systematically strengthen their distinctive capabilities, not those running isolated pilots. In other words, AI must reinforce what you already do uniquely well, or deliberately redefine it. Boston Consulting Group has shown that only a small minority of companies generate material value from AI at scale. The differentiator is not experimentation volume. It is disciplined execution, talent transformation, and operating model redesign. Accenture consistently points to the same conclusion. Technology is a fraction of the transformation equation. Leadership, culture, and change architecture drive the majority of realised value. The pattern is clear and simple. AI success is less about algorithms and more about executive capability. That is why executive AI education is a strategic priority. Not prompt workshops. Not vendor showcases. But structured, rigorous education around five areas: • Economic impact and margin structure • Competitive advantage and capability building • Operating model redesign and decision rights • Governance, risk, and board oversight • Change acceleration and adoption discipline Without this level of fluency, AI remains a side initiative. With it, AI becomes embedded into performance systems and capital allocation decisions. Many executive teams are funding AI at scale while still learning what it fundamentally means for their business model. By 2030, the advantage will sit with leadership teams who treated AI literacy as seriously as financial literacy. Because AI is not an IT topic, it is a board level economic lever. But is your leadership team prepared to use it as one? ----------------- One of the most rewarding parts of my work is partnering with leaders globally to turn their organisations into genuine AI powerhouses. Not by adding more tools, but by reshaping strategy, governance, and operating rhythm so AI compounds in value year after year. If you would like me to work with your executive team to build that level of fluency and translate AI into measurable strategic impact, feel free to reach out. #AILeadership #BoardStrategy #AIStrategy #ExecutiveEducation #DigitalTransformation

Last week I had the pleasure of delivering the Leading AI Strategy and Execution programme at the Irish Management Institute in Dublin, Ireland. It was a fantastic group of senior leaders and managers from a wide range of sectors, all exploring the same question: How do we move from AI curiosity to real organisational impact? Over the course of the programme we focused on the practical side of AI adoption. We explored how leaders can make better data driven decisions, identify the AI opportunities that actually create value, and navigate the governance and ethical considerations that come with deploying AI at scale. A key outcome of the programme is that every participant leaves with something tangible. Each leader developed a tailored AI implementation plan for their department or organisation, shaped through workshop exercises, peer discussion, and structured guidance. The goal is simple. Not just understanding AI, but knowing how to implement it responsibly and effectively. It was great to see leaders from sectors including financial services, healthcare, financial services, farming, software engineering, manufacturing, retail and construction engaging deeply with the opportunities and challenges ahead. Thank you to the Irish Management Institute and to everyone who participated for the thoughtful discussions and energy throughout the programme. AI strategy is no longer a future conversation, it is a leadership capability today. ----------- Interested in an AI programme or other AI and leadership courses? Contact the Irish Management Institute or message me and lets get your in person training organised. #AILeadership #AIStrategy #ExecutiveEducation #ArtificialIntelligence #Leadership

Most people are using 2026 AI with 2022 habits. This article explores how quickly AI capability has accelerated, why progress feels invisible until it suddenly feels overwhelming, and what practical shifts matter if you want to master AI rather than casually experiment with it. It examines the data behind the acceleration, including benchmark leaps, falling inference costs, and research showing capability growth nearly doubling since 2024. It also explains why tools like ChatGPT have changed more under the surface than most users realise, with reasoning, memory, projects, and workflow features quietly redefining what is possible. The core argument is simple. Prompt tricks are no longer the edge. Systems, context, consistent daily use, and workflow design now determine who pulls ahead. AI progress is compounding. Mastery must compound too. ♻️ Share this to help someone in your network #ArtificialIntelligence #AI2026 #Productivity #FutureOfWork #DigitalStrategy

You blinked and AI market moved again. Are you already behind and now rushing to catch up? My new book - How to Build an Agent: The Leader's Playbook for Coding and Deploying Al That Delivers Real Business Results - is available globally on #Amazon and #Audible This is not a book about experimenting with AI. Instead, it is a practical playbook for leaders who need AI systems that work in the real world. Most organisations use generative AI but few see meaningful business results and this book explains why. Written for executives, senior managers, consultants, and technical leaders, it shows how to move beyond chatbots and prompts to autonomous, outcome-driven AI systems that plan, act, integrate with enterprise software, and deliver measurable ROI. This is an easy to read guide to building digital workers inside real organisations. Inside the book, you will learn: • What agentic AI is, and why most companies get it wrong • Chatbots vs workflows vs autonomous agents • Designing agents across CRM, ERP, email, and data platforms • Build vs buy vs hybrid, and how to choose • Governance with auditability, controls, and human oversight • Measuring ROI that boards and finance teams respect • Running a four-week pilot that produces decision-grade evidence • Scaling from one agent to coordinated multi-agent systems You do not need to be a software engineer. You do need to be responsible for outcomes. You will learn how agents work, how they differ from automation, and how to design them safely, economically, and at scale, with a focus on decisions, architecture, governance, and execution. AI adoption is no longer the challenge but owning and leading AI is. How to Build an Agent is the field manual for doing exactly that. As a gift to you, I am offering two free chapters to allow you to try before you buy https://lnkd.in/ea_Runq3 🕵️‍♂️ Find all my books on Amazon - https://lnkd.in/eaVSZAMf Kieran Gilmurray MBA MSc. PG. Dip. BSc (Hons)

Have you seen my new exciting website? https://lnkd.in/e47_4AkJ Today I am launching my new website. Not a redesign but more a reset. Over the past few years my work has evolved. From AI experimentation to board level strategy. From speaking about technology to helping leaders use it properly. The new site reflects that shift. You will find: • Strategic AI advisory • Executive education for boards and C suites • Practical tools leaders can use immediately • Real case studies, not theory • Interviews and podcasts with leading experts Artificial intelligence is not the story. Competitive advantage is. The website is built around one simple idea: Strategy, artificial intelligence, and capital allocation shape long term value. If you are exploring AI seriously, not just piloting tools but embedding capability, I would value your thoughts. #ArtificialIntelligence #Strategy #Boards #CapitalAllocation #Leadership

On the 1st of Jan I launched my 2026 action plan and 7 step Misogi adventure. Well, we are 8 weeks into the year and you are due a progress update, so here we go: • Create and deliver at least 6 new executive education courses. I have designed and delivered 4 news courses: 1. AI course for 'Sales, Advertising and Sponsorship, Events Marketing, Marketing, B2C and B2B Subscriptions' teams. This course is squarely focused on business outcomes i.e., revenue growth, efficiency, prioritisation, and commercial decision-making. 2. Generative AI for Environment, Health, and Safety (EHS) - How to use AI to protect people, workplaces and the environment. 3. AI for strategic planning - Understand how AI strengthens strategic positioning and competitive advantage, and use generative AI to improve analysis, clarity, executive decision making, and scenario planning. 4. How AI Forms Bias and What Educators Can Do About It - Spot the bias. fix the output in education (e.g., teachers, professors). • Publish 2 new books and draft the 3rd before the end of 2026 - Book one is live on Amazon and Audible. I have written the 9 chapters of book 2 but I am stuck on chapter 10 - aghhhhhh. This is a mind melt moment - help. • Travel to at least 14 countries / cities - I have been to Edinburgh, London, Dublin, Galway, Mayo and Kuala Lumpur Malaysia with Saudi, Abu Dhabi planned for later in the year. • Publish 100+ thought leading articles - across my LinkedIn, website, Substack, and Medium channels I have now published 21 articles. So, on track. • Record 40+ podcasts - 20 podcasts delivered, 4 planned. And excitedly I got to 5000 downloads to date! • Present at 5 conferences - Two talks delivered (biggest was to 506 people) and another planned in March and June. Who might you be able to point me to in order to go talk somewhere fun? • Launch a new business website - Soft launched http://KieranGilmurray.com • Glow up on YouTube, Spotify, Substack and Instagram - YouTube and Spotify strategists hired. More to come. • Launch 5 new business services and 3 AI products - 5 AI products now available via my new website; and two partnerships in place. • Launch a community - who wants to join? - TBD • Experiment and kill things that don't work fast - Ongoing • Join two new boards - Specialist Board Adviser for the Virtual Operations started. • Doing something every single week that genuinely scares me - On it! • Take forward every lesson learned on the journey - Every day is a school day. • Practice the Misogi - 6 adventures, I have been to an amazing candle light Hans Zimmer classical music evening in Belfast for date night but more to do. • Regret nothing - naturally! How am I doing? #GoLargeOrStayHome -------------------------------------- 🔔 Follow me for the last AI, analytics and leadership updates! #2026 #Businessshtag #ExecutiveEducation #BusinessResults #ROIfromAI

Kuala Lumpur reminded me why “strategy” can’t be a slide deck. At Strategy 2030, the Stravix Group and I brought together a small, invitation-only group of Malaysia’s senior AI and business leaders for an executive dinner. The point wasn’t about optics, it was to get honest about what AI is changing in Malaysian enterprise right now. I opened with a strategic outlook on AI, then moved into a fantastic panel that didn’t dodge the hard bits with Datin Dr. Ts. Habsah Nordin CDMP CSFC CAITL, Dato’ Dr. Munirah Looi, and Dr. Sekar Jaganathan, DBA, PhD (Mgmt), ICDM. What stood out wasn’t a shiny “AI roadmap”. It was the reality-check conversations that carried on over dinner: - Where AI is genuinely creating advantage vs. creating noise - What leaders are doing about capability gaps (not just hiring slogans) - How governance is being handled without killing momentum - What’s different about adopting AI in Malaysia’s operating context (and why copy/paste from elsewhere fails) I left with one clear takeaway: the best strategy work happens when senior people speak plainly, compare notes, and admit what’s not working yet. Thank you to the speakers and every leader who brought depth and openness to the room. What’s the most practical AI decision your leadership team has made in the last 90 days? #ArtificialIntelligence #Leadership #Strategy #Malaysia #ExecutiveLeadership

Most companies say “AI-first.” They are not. They are just adding AI on top. Take invoicing. AI enabled: You apply AI to manual invoice entry. Data capture improves and processing time falls modestly. Headcount dependency remains largely intact. The process is faster, but structurally unchanged. AI first: You remove manual entry as the primary control point. AI reads inbound emails and attachments. It validates against purchase orders and then it generates and routes invoices. It flags anomalies such as duplicate amounts, unusual bank details, or VAT inconsistencies and humans intervene only on exceptions. Now the conversation shifts from keystroke reduction to working capital velocity, fraud risk mitigation, audit traceability, and cost to serve. That is not optimisation. That is operating model redesign. The same pattern appears across other functions. Internal reporting: AI enabled: dashboards refresh more quickly. AI first: systems surface daily anomalies, generate plain language explanations of variance drivers, and propose decision options. Management time reallocates from data assembly to capital allocation. Vendor management: AI enabled: reminder emails drafted faster. AI first: response patterns tracked, delay probability modelled, escalation triggered only when financial risk thresholds are breached. Procurement becomes risk managed rather than reactive. Customer feedback: AI enabled: sentiment tagging. AI first: theme clustering, early warning detection, churn probability signals, and recommended corrective actions. Insight feeds directly into pricing, product, and retention strategy. The underlying shift is architectural. In AI enabled models, AI sits at the edge of the workflow. In AI first models, AI sits in the control flow. Humans move from process operators to exception handlers and decision owners. The result is not just productivity gain. It is a change in cost structure, cycle time, risk profile, and ultimately margin resilience. For leaders in operations, finance, product, and customer experience, the question is not whether to deploy AI tools. It is whether you are incrementally enhancing legacy workflows, or redesigning them so that human judgment is applied where it compounds value rather than where it compensates for process friction. If you were to rebuild one core workflow in your organisation with AI, which would it be, and what would that do to your unit economics? --------- ☎️ Need help? DM. #ArtificialIntelligence #OperatingModelRedesign

Why most AI projects collapse and how to build one that works with CEO, AI expert and author Andy Hayler. Lots of AI projects are failing at a rate that should make any leadership team pause, and the uncomfortable truth is that the model is rarely the real problem. I sat down with Andy Hayler, president and CEO of the Software Industry Authority and a long time data strategist, to explain why organisations keep shipping AI initiatives that look impressive but deliver zero measurable value. Listen to the full interview on my Spotify, Apple Podcasts and YouTube channels. Andy's excellent book Beyond the Hype: A Realist's Guide To AI is now available on Amazon. Where is your organisation most likely to be “confidently wrong” with AI? #AI #ConfidentlyWrong #AIMyth #Data

Search engines do not rank your content anymore, they decide whether to use it. Article 2 in our 8 part GEO Series is now live. This article breaks down how generative search actually works, from how AI understands a question to how it selects, validates, and cites sources inside an answer. If you want to be visible, you need to understand the pipeline. AI does not just scan your website. It pulls from across the web, evaluates trust, and selects content it can clearly extract and verify. Alongside the series, you can access our GEO Self Audit and service to assess your current visibility and identify what to fix first. Access the full series and GEO audit here: https://lnkd.in/etiDJS8z ♻️ Share this to help someone in your network

#SEO got you traffic but #GEO (Generative Engine Optimisation) decides whether you still exist. AI search is already rewriting the rules. Brands that keep playing by old #SEO logic might well quietly disappear in 2026. If you rely on organic traffic, not reading this guide is a mistake. My new 8 part Generative Engine Optimisation (#GEO) download shows what is changing, what is breaking, and what actually works when AI systems decide who gets seen. No hype. No theory. Just survival level clarity for you business. Get the guide before your traffic becomes someone else’s https://lnkd.in/etiDJS8z #GEO #GenerativeEngineOptimisation

SEO got you traffic. But GEO decides whether you still exist. AI search is already rewriting the rules. Brands that keep playing by old SEO logic might well quietly disappear in 2026. If you rely on organic traffic, not reading this guide is a mistake. My new 8 part Generative Engine Optimisation (GEO) download shows what is changing, what is breaking, and what actually works when AI systems decide who gets seen. No hype. No theory. Just survival level clarity for you business. Get the guide before your traffic becomes someone else’s https://lnkd.in/etiDJS8z #GEO #GenerativeEngineOptimisation

According to the HBR ‘Firms are incentivizing employees to build and oversee complex teams of agents—for example, by measuring and rewarding token consumption as a proxy for performance. Meta, for one, includes the number of lines of code generated by AI as a performance metric for engineers.’ Yet ‘As enterprises use more multi-agent systems, employees find themselves toggling between more tools. Contrary to the promise of having more time to focus on meaningful work, juggling and multitasking can become the definitive features of working with AI.’ There is mixed signals in literature as to whether AI and worker burnout is a thing as opossed to it being a productive multiplier. ‘Some studies suggest that using AI to replace tiring tasks alleviates exhaustion; other studies, sometimes on the same populations, show AI use worsening burnout outcomes.’ In my experience it can be both. The heady heights of using a great tool to do more sometimes results in my blurring home and work life even more than I currently do. Other times I get crazy amounts done in no time and I am mentally free to excel at what I adore - writing, consulting and executive education. Which is true in your experience? #burnouttool #productivemultiplier

AI is moving incredibly fast. You’ve seen how much can change in just 60 days. New capabilities appear, performance improves, and what felt advanced suddenly becomes standard. At the same time, your organisation cannot spend 18 months debating what to do next. The real question has shifted. It is not “will AI create value?” It clearly can. The question is, why are we finding it so hard to keep up? Comment below 👇🏼

Many companies are failing at AI simply because they are not managing their AI investments like a cross functional business portfolio. How should companies operate their AI investment portfolio? • Select a portfolio based on business needs NOT by rolling the dice on a collection of shiny moon shots. Test of strategic fit and technical feasibility. • Remember to follow a disciplined step-by-step portfolio approach that is managed by applying coherent, repeatable principles. • Allocate scarce resources strategically across functions. • Secure and maintain executive sponsorship across multiple initiatives. • Sequence the right projects at the right time rather than chasing disconnected proofs of concept. • Then introduce tightly defined go/no-go gates known as “stage gates” to increase the likelihood of worthy innovations reaching the market – test feasibility and strategic fit. • Now every candidate project is judged not only on its standalone merits but also in relation to competing opportunities, enterprise priorities, and cross-initiative dependencies. • Regular reviews rebalance your entire AI portfolio by adding promising initiatives, scaling successful pilots, redirecting struggling efforts, retiring misaligned projects, and recalibrating objective scoring criteria. These reviews assess both individual project health and overall portfolio coverage and include questions such as: • Are we maintaining appropriate balance across time horizons? • Do we have sufficient investment in foundational capabilities? • Do early-warning triggers, such as schedule slippage, cost overruns, or performance shortfalls suggest that intervention is needed? Viciously and rapidly remove what no longer creates real value rather than cutting blindly. How do you manage you AI investment portfolio? #Portfolio #AIInvestmentOrCost #AITheatreOrValueAdd

Search has changed. Most brands have not. Article 1 is now live to help you learn more about GEO. This article explains what Generative Engine Optimisation (GEO) actually is and why visibility is shifting from ranking on Google to being cited inside AI generated answers. If your brand is not referenced by tools like ChatGPT, Bing Copilot, or Google SGE, you are increasingly invisible at the point where decisions are made. We have also launched the full 8 part GEO Series alongside this, designed to give you a clear, practical path to improve your AI visibility. Alongside the series, you can access our GEO Self Audit and service, helping you assess where you stand today and what to fix first. Access the full series and GEO audit here: https://lnkd.in/etiDJS8z ♻️ Share this to help someone in your network

Imagine asking your assistant to “cut costs by 10%,” then learning it quietly hired five bots, switched your insurance, and exposed you to a lawsuit. That’s the new reality of agentic AI: software that doesn’t just talk, it acts, spends, negotiates, signs, and delegates at machine speed. Let's take you inside this shift and show how to keep control when intelligent delegation gets real. Listen into Google DeepMind's excellent article on Intelligence AI Delegation as podcast by two Google NotebookLM agents - https://lnkd.in/enmcCvHs #AgenticAI #KieranGilmurray

A room full of leaders leaning in beats any “leadership” buzzwords. Yesterday 30 amazing leaders from the Invest NI Leading within a Group Programme 2026 came together for the next stage of their development journey. And the focus was practical: AI-enabled leadership, building influence, and navigating complexity across group structures without getting lost in noise. I kicked off with a high-energy masterclass. No hype. No “AI will replace you” theatre. Just real tools, real examples, and a clear message: used well, AI and automation can give leaders time back, sharpen decisions, and improve how work actually moves through an organisation. A few things I saw in the room that made me smile: - Leaders comparing ideas and prompts - People sharing without defensiveness - Notes being taken like it mattered… because it did The best bit? The energy. Participants left with actionable next steps, not just a nice folder and a group photo. Huge credit to every leader who showed up, made the time, and properly engaged. That’s what makes development stick. Thank you to Invest Northern Ireland's exceptional team - Catherine McGuigan, Nancy B., Phil Bonar, and Irish Management Institute's Nora Duggan for setting this up. If you’re leading a team or business then this program is meant for you. To explore how to start your strategic leadership for growth journey through Invest Northern Ireland click here: 👉 https://lnkd.in/enDD9Sxw to view the range of specialist CEO, top team and senior leadership solutions on offer for 2026-27 #LeadershipDevelopment #InvestNI #AILeadership #OrganisationalEffectiveness #LeadingThroughChange

Delighted to get to kick off my Insight Jam with a keynote talk as part of their "The Soft Side of AI: Education, Empathy & Human Readiness," program featuring exclusive keynote presentations from Solutions Review Experts and industry-leading voices. These 30-minute sessions deliver actionable strategies, visionary insights, and cutting-edge approaches, equipping you with the knowledge to drive meaningful AI impact within your organization. My talk advocates for EVERY generation getting AI training starting with AI natives. Don’t miss these high-impact presentations! https://lnkd.in/eT2kW_kH

Everyone said it. “My job is too creative.” “My role is too human.” “My skill cannot be replicated.” That was the comfort story. But AI does not need to outperform you at your best. It only needs to be good enough, fast enough, and cheap enough. Markets reward efficiency before perfection. If an AI system can produce 70 percent of the output at 10 percent of the cost, the economic pressure is obvious. Over time, that 70 becomes 80, then 85. Meanwhile the cost of AI continues to fall. The real risk is not that AI replaces excellence. It replaces average. So the question is not whether your role is creative or human. It is this: • Are you doing work that cannot be standardised? • Are you using AI to get more done with the same effort? • Are you moving up the value chain faster than automation is moving up behind you? AI will not remove the need for judgment, taste, trust, and leadership. But it will remove the need for expensive repetition. If you are not redesigning your work around that reality, someone else is. #AIReplace #StandardisedWork #EconomicsWillWin

If AI cannot extract your content, it will not use it. Article 4 of our GEO Series is now live. This article shows how to actually optimise your content so AI systems can interpret, verify, and reuse it inside answers. Visibility now depends on structure, clarity, and credibility. Answer-first writing, strong evidence, schema, and consistent authority signals determine whether your content gets cited or skipped. We have also released the full 8 part GEO Series to help you apply this in practice, with clear steps to improve your AI visibility and get referenced where it matters. Alongside the series, you can access our GEO Self Audit and service to understand your current position and what to fix first. Access the full series and GEO audit here: https://lnkd.in/etiDJS8z ♻️ Share this to help someone in your network #GEO #GenerativeEngineOptimisation #AIAudit #GEOSeries #AISEO

AI is moving faster than most organisations can absorb. Every week new models launch, new regulations appear, and new use cases promise productivity gains but most leaders still ask the same question: What actually matters for my business? That is exactly why I created my monthly newsletter. Each edition breaks down what leaders really need to know about AI right now, including: 1. The most important AI developments explained in plain English 2. Real business applications that go beyond experimentation 3. Strategic risks leaders should understand early 4. Practical ideas you can apply inside your organisation No hype. No technical jargon. Just clear insight on how AI is shaping business strategy. If you want to stay ahead of where AI is going and what it means for your organisation then join over 7000 other subscribers who read this newsletter. What topics should I cover in the next issue? #AI #ArtificialIntelligence #AILeadership #DigitalTransformation #AIstrategy

Everyone wants the visible AI. Chatbots that close deals. Models that predict customer churn. Automated customer support. It looks strategic and it sounds innovative. It even plays well in board slides. Meanwhile, inside the company, sales teams are spending hours updating CRM fields. Finance is still struggling to reconcile invoices manually. Marketing is copying content between tools that do not speak to each other. How do you solve for this? First, sort out the internal inefficiencies. Give employees the tools and training that they need to solve real problems not theoretical use cases i.e., the work that keeps them online late on a Friday. Second, let teams experiment. That operations manager who built a rough GPT workflow to save her time is not a hobbyist. They are an insightful futurist. Internal builders are often your most practical product designers. Third, go external. When your team has seen AI save them five hours a week, they will advocate for customer facing solutions that help them win too. Large technology firms have done this deliberately. Internal AI tools are built and adopted by employees first, driving thousands of real use cases before being pushed outward. It’s simple from a business point of view. When your team becomes more productive, the gains build on themselves over time. It improves margins, decision speed, and execution quality. External AI layered on top of weak internal processes rarely delivers sustainable returns. If your own people do not trust the technology, your customers will sense that. The order matters more than the ambition. Do you have an AI strategy that is actually delivering results, or are you still experimenting without impact? ---------- If you need expert guidance then message and my team will connect us. #Strategy #GuidanceWithOutDrama #ResultsNotAITheatre

I have just released a preview of Chapter 12 of my new book. This is the fourth book in my Masterclass Series on AI. Chapter 12 answers a practical question: how to run an AI pilot that actually proves something. Most pilots fail. Around 95% of generative AI pilots never deliver meaningful business results, usually because objectives are vague, metrics are unclear, prototypes are fragile, and there is no plan beyond the pilot. This chapter shows how to run a four week pilot that produces decision grade evidence: choose a narrow use case, define measurable outcomes, build on production ready foundations, and transfer knowledge to the internal team that will run the system. It also sets the operating cadence for whichever path you chose in Chapter 11, build, buy, or hybrid, helping you determine within one month whether the initiative can realistically scale. The full book is now live on Amazon. You can read the Chapter 12 preview and access free chapters here: https://lnkd.in/ea_Runq3 Repost to help someone in your network ♻️

AI adoption is accelerating. Workforce capability is not. This article explores why the global reskilling challenge is becoming a major leadership issue as AI use rises faster than structured training and capability building. Gallup data shows workplace AI use nearly doubling in two years, while the World Economic Forum estimates 23% of jobs will change by 2027 and 44% of workers’ skills will be disrupted within five years, yet many employees still lack formal training or clear guidance. The message for leaders is simple. The real AI constraint is no longer technology. It is skills, systems, and the ability to build capability at scale. ♻️ Share this to help someone in your network #ArtificialIntelligence #FutureOfWork #Leadership

Your next hire might be digital but at what cost? Is our global economic model is ready for it? Are you? For decades we treated growth and job creation as inseparable. Expand output, create employment. Increase employment, increase spending. Increase spending, reinforce growth. That assumption is now under a huge deal of pressure. Artificial intelligence is beginning to decouple productivity from headcount. When systems automate tasks once performed by people, the gains tend to accrue first to margins and shareholders, not wages. Corporate profits compound on balance sheets but it is wages that circulate through communities. That distinction matters. You can have a “healthy” economy on paper while the underlying resilience quietly erodes. The labour market has historically acted as a recession shock absorber: Jobs → income → consumption → business revenue → jobs. That loop is how we absorb shocks. It’s how families keep going when interest rates jump, rents rise, or a customer disappears. But before anyone pictures an automated future where we all sip piña coladas and write poetry that is not, in practice, how the transition tends to play out. If output keeps increasing but companies are not creating enough new jobs, that safety buffer starts to break down. The economy can look strong on paper, with rising GDP, higher profits, and climbing stock markets, while many households are quietly becoming more financially fragile. We often cite the World Economic Forum’s projection that 65 percent of children today will work in jobs that do not yet exist. I have referenced it myself. However, the real strategic question is not whether new roles eventually emerge. It is whether they emerge at sufficient scale and speed to replace what is displaced. If they do not, we face a structural shift in how economic stability is maintained. So what becomes the new stabiliser? • Broader ownership of productive assets? • Reallocation of productivity gains into wages? • Reduced working hours with maintained income? • New forms of labour participation? Boards and policymakers need to treat this as a capital allocation and governance issue, not a technology debate. If “jobs → paycheques → spending” weakens, what replaces it as the shock absorber in an AI driven economy? #FutureOfWork #AI #CapitalAllocation #Productivity #EconomicStrategy

Everyone is talking about AI but very few are talking about what happens when AI starts acting on its own. That is why I wrote Agentic AI and the Future of Work: How Intelligent Agents Will Redefine Roles, Skills, and Value. Agentic AI is not just automation. It plans. It decides. It takes action. It collaborates with systems and with people. And it is already reshaping how work gets done across industries. In this book, I explain what agentic AI really is, how intelligent agents operate, and what this means for roles, skills, leadership, and competitive advantage. You will see real world examples of how digital workers are increasing efficiency, improving decision making, and scaling operations in ways traditional tools simply cannot. But this is not a technical manual. It is a strategic guide for managers, executives, consultants, and leaders who want to understand what is coming next and how to lead it responsibly. The future of work is not about humans versus AI. It is about humans working with intelligent agents. Those who understand that shift will define the next era of value creation. If you want to be one of them, this book is for you. 🌏 https://lnkd.in/eaVSZAMf #AgenticAI #FutureOfWorkToday #DigitalAndHuman

Why do so many transformation initiatives start with momentum… and then quietly stall? Join us in Dublin for “From Interest to Inertia”, where industry leaders will explore what really happens between the excitement of a new initiative and the moment progress slows down. This event brings together experts with real-world experience in finance transformation, AI adoption, and operational change to share practical insights on keeping initiatives moving forward. You’ll hear from: 🔹 Kieran Gilmurray– Global Keynote Speaker on finance transformation and AI adoption 🔹 Lee Oosthuizen – Head of Finance Transformation at Pat The Baker 🔹 Shane McMahon – Director at Kefron 🔹 Sarah Kelleher – Head of Accounts Payable at Trinity College Dublin If you’re responsible for driving change in finance or operations, this conversation will offer valuable perspectives on what makes transformation succeed or fail. 📍 Dublin 🎟 Register here: https://lnkd.in/dUZbTDfS #FinanceLeadership #FinanceTransformation #ArtificialIntelligence #AccountsPayable #AIinFinance #CFO #DublinEvents Nicole B.

Everyone is talking about AI but very few are talking about what happens when AI starts acting on its own. That is why I wrote Agentic AI and the Future of Work: How Intelligent Agents Will Redefine Roles, Skills, and Value. Agentic AI is not just automation. It plans. It decides. It takes action. It collaborates with systems and with people. And it is already reshaping how work gets done across industries. In this book, I explain what agentic AI really is, how intelligent agents operate, and what this means for roles, skills, leadership, and competitive advantage. You will see real world examples of how digital workers are increasing efficiency, improving decision making, and scaling operations in ways traditional tools simply cannot. But this is not a technical manual. It is a strategic guide for managers, executives, consultants, and leaders who want to understand what is coming next and how to lead it responsibly. The future of work is not about humans versus AI. It is about humans working with intelligent agents. Those who understand that shift will define the next era of value creation. If you want to be one of them, this book is for you. 🌏 https://lnkd.in/eaVSZAMf #AgenticAI #FutureOfWorkToday #DigitalAndHuman

Have you ever wondered how your business shows up within GEO search? Get the free #GEO self audit and guide here: here https://lnkd.in/etiDJS8z #GenerativeEngineOptimisation #GEO #AEO #SelfAudit #FreeGuide

Google used to decide if you got seen but now AI decides if you get cited and most brands are invisible where it matters most. What is GEO? In simple terms Generative Engine Optimisation (#GEO) means making your content easy for AI systems to find, understand, and use in their answers. How is GEO different from SEO? Search Engine Optimisation (#SEO) is about ranking web pages in Google results. GEO is about being referenced inside AI-generated answers on tools like ChatGPT, Bing Chat, or Google SGE. Why should marketers care about GEO now? AI-driven search is growing fast. Traffic from traditional search is falling, and users increasingly trust AI answers. Brands need to be visible where audiences are looking. What practical steps can I take to improve my GEO standing? Use Q&A structures, provide clear statistics and citations, write in a conversational style, and track mentions across AI platforms. Is GEO replacing SEO? No. GEO builds on SEO. You still need strong technical SEO and user-focused content, but you also need to prepare for AI-first discovery How do I find out more about GEO? Download our free GEO Self Audit and 8 Part GEO Series. Both offer practical, evidence advice showing how you can get cited in AI answers, protect brand visibility, and adapt SEO for an answer first internet. Where do I go to get those? Here https://lnkd.in/etiDJS8z #GEO #GenerativeEngineOptimisation #AIAudit #GEOSelfAudit