The Digital Transformation Playbook

Kieran Gilmurray

Kieran Gilmurray is a globally recognised authority on Artificial Intelligence, intelligent automation, data analytics, agentic AI, leadership development and digital transformation. He has authored four influential books and hundreds of articles that have shaped industry perspectives on digital transformation, data analytics, intelligent automation, agentic AI, leadership and artificial intelligence. 𝗪𝗵𝗮𝘁 does Kieran do❓When Kieran is not chairing international conferences, serving as a fractional CTO or Chief AI Officer, he is  delivering AI, leadership, and strategy masterclasses to governments and industry leaders.  His team global businesses drive AI, agentic ai, digital transformation, leadership and innovation programs that deliver tangible business results.🏆 𝐀𝐰𝐚𝐫𝐝𝐬: 🔹Top 25 Thought Leader Generative AI 2025  🔹Top 25 Thought Leader Companies on Generative AI 2025  🔹Top 50 Global Thought Leaders and Influencers on Agentic AI 2025🔹Top 100 Thought Leader Agentic AI 2025 🔹Top 100 Thought Leader Legal AI 2025🔹Team of the Year at the UK IT Industry Awards🔹Top 50 Global Thought Leaders and Influencers on Generative AI 2024 🔹Top 50 Global Thought Leaders and Influencers on Manufacturing 2024🔹Best LinkedIn Influencers Artificial Intelligence and Marketing 2024🔹Seven-time LinkedIn Top Voice.🔹Top 14 people to follow in data in 2023.🔹World's Top 200 Business and Technology Innovators. 🔹Top 50 Intelligent Automation Influencers. 🔹Top 50 Brand Ambassadors. 🔹Global Intelligent Automation Award Winner.🔹Top 20 Data Pros you NEED to follow. 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 Kieran's team to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/30min ✉️ kieran@gilmurray.co.uk  🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn

  1. Agents At Work

    VOR 1 TAG

    Agents At Work

    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. We take you inside this shift and show how to keep control when intelligent delegation gets real. TLDR / At A Glance principal–agent misalignment and span of controlauthority gradients, sycophancy, and zones of indifferencecontract-first task decomposition and verifiable outcomesopen agent marketplaces, negotiation, and Pareto trade-offsverifiable credentials, process monitoring, and privacyzero-knowledge proofs and homomorphic encryptionresilience, failover, escrow, and recursive liabilitythreat models and the confused deputy problemmoral crumple zones, meaningful oversight, and de-skillingcurriculum-aware routing and socially intelligent agentsWe start with the human blueprint that still applies: the principal–agent problem, misaligned incentives, span-of-control limits, and authority gradients that make smaller models defer to larger ones. From there, we get practical. Contract-first task decomposition turns fuzzy goals into verifiable promises, enabling open marketplaces where agents bid on work with capability proofs, not just price tags. The delegator must juggle speed, cost, quality, privacy, and safety, seeking Pareto-efficient choices while escalating only when red lines are at stake. To make this safe, we trade flimsy star ratings for verifiable credentials, and we show why outcome checks aren’t enough without process-level monitoring. Trust and privacy take centre stage with zero-knowledge proofs and homomorphic encryption—tools that let agents prove correct work without ever seeing or leaking your secrets. Resilience gets engineered in: smart contracts that define kill switches, instant failover, and escrow that slashes bad actors. Recursive liability pushes accountability up the chain so no one can hide behind a subagent three layers down. We also map today’s threat landscape—from model extraction to the confused deputy problem—and outline practical defences built on least privilege and robust input hygiene. The ethical frontier matters just as much. We unpack moral crumple zones that turn humans into liability shields, and we argue for meaningful oversight with time and authority to intervene. To prevent de-skilling, we explore curriculum-aware routing that intentionally sends tasks to people to preserve judgement.  The destination is clear: an ecosystem of specialised agents governed by provable contracts, strong credentials, cryptographic trust, and responsibility that actually sticks. Subscribe, share with a colleague who runs ops or risk, and tell us: where should we draw the first guardrails? Source:  Intelligent AI Delegation  Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    22 Min.
  2. From Guardrails To Growth: Building Trustworthy AI At Scale

    VOR 1 TAG

    From Guardrails To Growth: Building Trustworthy AI At Scale

    What separates a celebrated AI launch from a brand‑damaging crisis is not a smarter model, but smarter governance. We pull back the curtain on how top performers turn guardrails into a growth engine, showing the concrete steps that keep innovation flowing while risk stays inside appetite. From defining decision rights to knowing exactly when to hit pause, we make governance practical, testable, and fast. TLDR / At A Glance: treating governance as the AI operating systemrising risk and regulatory context with quantified costssafety guardrails across input, output, and processinghuman in the loop approval gates and escalation rulesfail safes, circuit breakers, rollback and incident tiersbrand voice definition, disclosure and consistencycompliance by design mapped to NIST and ISOmetrics for performance, quality and business impacttesting culture with red teaming and canary releasesWe start with the real stakes: escalating breach costs, a crowded regulatory landscape spanning the EU AI Act, GDPR, and state laws, and a board‑level demand for evidence that AI meets enterprise standards. Then we get hands‑on with a three‑pillar framework. You’ll hear how to design input, output, and processing controls that block toxic content, defend against prompt injection, enforce least privilege, and preserve immutable audit trails. We outline human‑in‑the‑loop approvals for high‑stakes actions, plus circuit breakers, blue‑green rollbacks, and incident tiers that compress time to recovery and align with reporting clocks. Brand and compliance take centre stage next. We show how to lock a consistent voice across channels, disclose AI use, and translate legal duties into a living checklist for data governance, consent, explainability, auditability, and the right to contest. With NIST AIRMF, ISO IEC 42001, and COBIT as scaffolding, your controls become systematic and auditable across global operations. We tie it together with quality metrics, observability, and a test culture of red teaming, regression suites, canaries, and A/Bs so you can measure accuracy, satisfaction, and cost without chasing vanity dashboards. Finally, we share an operating model that scales: an executive‑led AI Governance Council, clear day‑to‑day roles in security and ethics, and a maturity path from ad hoc fixes to optimised practice. Real‑world cases in healthcare, banking, and e‑commerce reveal how governance unlocks adoption and ROI, not just risk reduction. If you’re ready to move fast without breaking what matters, press play, take the checklist, and share it with your team. Subscribe, leave a review, and tell us which guardrail you’ll implement first. Like some free book chapters?  Then go here How to build an agent - Kieran Gilmurray Want to buy the complete book? Then go to Amazon or  Audible today. Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    27 Min.
  3. From Demo To Durable Asset

    26. FEB.

    From Demo To Durable Asset

    A flashy prototype is easy; keeping value online, secure, and affordable is the real test. We walk through a practical path from demo to durable asset, showing how reliability, scalability, security, and maintainability turn experiments into systems executives can trust.  The conversation connects architecture choices to financial outcomes, making the case that every decision about serverless, containers, data, and integration is really a budgeting and risk move in disguise. At A Glance / TLDR: • framing demo-to-asset mindset and executive concerns • four pillars reliability, scalability, security, maintainability • market gaps, governance and CEO oversight • architecture as financial strategy for speed and cost • serverless for bursty loads, containers for control • move from static data to streaming pipelines • integration as platform, not project • zero trust identity, encryption, audit trails • cost tiers pilot, department, enterprise • timelines, sequencing ambition, FinOps discipline • reusable integrations and compliance by design • portfolio governance, scale what works We break down the four pillars of production readiness and why they map so closely to CFO and CISO priorities.  You will hear a clear comparison of serverless versus containers, with workload patterns that determine cost, speed to market, and lock-in risk.  We then shift from static documents to real-time streaming, explaining schema governance, observability, and replay, and why faster data loops enable customer service, fraud, inventory, and risk use cases where minutes matter.  Integration takes centre stage as the last mile that decides both timeline and ROI; we outline permissions, backlogs, and reuse strategies that convert brittle pilots into repeatable wins. Security moves from lab shortcuts to a zero trust posture grounded in identity, encryption, and continuous monitoring. We discuss the breach economics that justify early investment and the practical controls that keep secrets out of prompts and logs while preserving auditability.  To anchor planning, we map three cost tiers—pilot, departmental solution, and enterprise platform—with realistic one-time and run-rate ranges, plus timelines that reflect integration maturity and governance.  By sequencing ambition, aligning workloads to the right compute model, adopting FinOps discipline, and treating integrations as products, you build a platform that compounds value quarter after quarter. If this lens helps you steer from hype to durable outcomes, follow the show, share it with a teammate who owns the roadmap, and leave a quick review so others can find it. Like some free book chapters?  Then go here How to build an agent - Kieran Gilmurray Want to buy the complete book? Then go to Amazon or  Audible today. Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    23 Min.
  4. From Solo Agent To Swarm Mastery

    24. FEB.

    From Solo Agent To Swarm Mastery

    When adoption dips, renewals wobble, and compliance blocks progress, a lone AI agent won’t save the quarter. We explore how multi‑agent swarms replace silos with coordinated specialists, turning scattered signals into decisive action across billing, support, product, and finance.  Drawing on proven patterns, we walk through four collaboration modes - sequential handoffs, parallel processing, hierarchical coordination, and peer collaboration - and show how to combine them for speed, accuracy, and clear ownership. At a Glance / TLDR the problem with single‑agent silos and concurrent enterprise issuesfour coordination patterns and when to use eachevent‑driven communication and layered context for coherenceconflict resolution, enforcement agents, and safety protocolsfive specialist roles for customer success swarmsthe coordinator’s dynamic routing, load balancing, and escalationmicroservices, service mesh, and state management patternsmessaging backbones, retries, and dead‑letter handlingcaching, auto‑scaling, and circuit breakers for resiliencestrategic rollout, ROI discipline, and cultural alignmentWe break down the roles that make customer success swarms work: triage as the front door, knowledge as corporate memory with retrieval‑augmented generation, research as the external lens, action as executor across live systems, and follow‑up as quality control.  At the centre sits the coordinator, acting as conductor rather than soloist - dynamically activating agents, balancing capacity, predicting the best route, and enforcing a single source of truth, audit trails, and human escalation. That governance turns autonomy into accountability and reduces risk while improving outcomes. For leaders shipping these systems, architecture matters. Microservices and a service mesh keep services scalable and secure. Event‑driven messaging builds decoupled, high‑throughput collaboration; event sourcing and CQRS maintain consistent state without bottlenecks. Enterprise message buses handle ordering, retries, and dead letters, while caching, auto‑scaling on coordination load, and circuit breakers protect performance and resilience.  We close with the strategic lens: why orchestration will become baseline across enterprise apps, how coordination intelligence compounds over time, and what disciplines - measurement, governance, phased rollout, and cultural alignment - separate lasting value from hype. If this helped you think beyond chatbots toward orchestration, follow the show, share it with a teammate who owns customer retention, and leave a quick review so others can find it. Like some free book chapters?  Then go here How to build an agent - Kieran Gilmurray Want to buy the complete book? Then go to Amazon or  Audible today. Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    21 Min.
  5. Can AI Tackle Learning Poverty In The Global South

    23. FEB.

    Can AI Tackle Learning Poverty In The Global South

    A stark number sets the stakes: seven in ten 10-year-olds in low and middle income countries cannot read a simple sentence. We take that reality out of the abstract and into a crowded classroom, following Saad, who is lost in long division, and Fatima, who is bored because the pace is too slow. F rom there we explore whether AI can truly help systems leapfrog toward quality education, or whether it risks becoming a shiny diversion that deepens inequality. TLDR / At A Glance: • learning poverty at 70 percent among 10-year-olds in low and middle income countries • web of exclusions across gender, disability, conflict, language and culture • access success but quality failure in crowded classrooms • personalised AI tutoring that diagnoses gaps and adapts tasks • high-dosage tutoring gains in Edo State, Nigeria • teacher workload relief through planning and grading automation • Nova Sola WhatsApp chatbot saving one hour per lesson plan • local language content generation to counter colonial curricula • universal AI literacy for critical, ethical use • co-intelligence as a design goal and last-mile inclusion We dig into concrete, on-the-ground examples. An after-school pilot in Edo State, Nigeria used an AI tutor to deliver learning gains equal to one-and-a-half to two years in only six weeks, showing what high-dosage, one-on-one support can do when cost barriers fall. We look at teacher-centred tools too: a WhatsApp-based lesson planning assistant in Brazil that saves an hour per plan, turning automation into time for rest, feedback, or one-on-one care. And because connectivity is the fault line, we unpack “AI unplugged”: paper tests photographed on a single phone, uploaded later, analysed in the cloud, and returned as simple, actionable diagnostics that guide tomorrow’s lesson. We also spotlight the urgent need for culturally relevant content, highlighting rapid generation of children’s books in local languages to replace decades-long shortages. But speed without equity is a trap. We name the Matthew effect at play when solutions assume electricity and broadband that most schools do not have.  We weigh innovation against transformation, asking not only how to teach but what to prioritise when labour markets shift and community knowledge matters.  Alongside sobering OECD futures like “education outsourced,” we argue for universal AI literacy so every child can question sources, spot bias, and understand how recommendations are made. The north star is co-intelligence: humans leading, AI extending reach, with system design that includes infrastructure, teacher training, governance, and language. If you care about closing the learning gap without creating a permanent underclass, this conversation is for you.  Listen, share with a colleague who works in education or development, and leave a review telling us one low-tech idea that could scale in your context.  Your feedback helps more people find the show and keeps this work moving forward. Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    14 Min.
  6. How 12 Percent Turn AI Into Growth

    19. FEB.

    How 12 Percent Turn AI Into Growth

    The hype is loud, but the scoreboard is quiet. We dig into a global study of 1,200 companies and reveal why only 12 percent qualify as true AI achievers - firms that turn models into money, scale beyond pilots, and reshape how they build, price, and deliver products. Instead of vague talk, we map a clear route from ambition to results and show how strategy, culture, and plumbing work together. TLDR / At A Glance: • McCarthy’s definition set against today’s reality • The four AI maturity archetypes and what they miss • Why experimenters fall behind as the gap compounds • Strategy and sponsorship as a board-level mandate • Upskilling domain experts to create hybrid talent • Escaping pilot purgatory with MLOps and trust • Explainable models in R&D and operations • Responsible AI frameworks that reduce risk • Investment shifts toward data hygiene and cloud • Orchestrating all five factors in parallel We start with the four archetypes - achievers, builders, innovators, and experimenters - and explain the traps each group falls into. From there, we unpack the five factors that consistently predict outperformance.  You’ll hear how executive sponsorship turns AI into a board-level priority and why a construction leader bet on generative design to create thousands of viable blueprints, shifting from incremental gains to a new way of making buildings.  We then show how upskilling domain experts beats hiring for code alone, with a frontline engineer-turned-analyst saving seven figures by pairing machine knowledge with data tools. Next, we tackle the hard work of industrialising the AI core moving from demos to production. A consumer goods giant earned scientist trust with explainable models for product formulation, cutting lab cycles and costs, while a century-old metro layered analytics onto legacy assets to trim energy use by 25 percent.  We also dig into responsible AI as scale accelerates: fairness, explainability, human-in-the-loop checks, and audit trails that satisfy regulators and protect customers.  Finally, we follow the money. Achievers invest more in AI, but the edge comes from allocation—funding data hygiene and cloud migration to unlock dozens of high-value use cases instead of one-off wins. The thread running through it all is orchestration. Strategy without data is theater, models without culture are shelfware, and spend without governance is a lawsuit waiting to happen.  We lay out a practical playbook: choose use cases tied to business goals, build the data backbone, upskill the experts closest to the work, embed MLOps and guardrails, and measure adoption and ROI relentlessly.  If you’re ready to move from experiments to enduring advantage, follow along and if this resonated, subscribe, share with your team, and leave a review so others can find it. Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    15 Min.
  7. Building A Knowledge Agent That Remembers

    17. FEB.

    Building A Knowledge Agent That Remembers

    Knowledge without memory is guesswork. We take a hard look at why most workflow agents stall at triage and show how to turn them into knowledge agents that deliver trusted, context-rich answers drawn from your organisation’s best thinking.  Starting with the real cost of lost information and context switching, we map the path from scattered wikis and chat threads to a reliable institutional memory powered by retrieval augmented generation and hybrid search. At a Glance / TLDR: the memory gap between task routing and problem solvingwhy hybrid retrieval outperforms pure vector in enterprise settingspractical chunking strategies and metadata fields for authority and recencyarchitecture choices across vector stores, hybrid search, and connectorsgovernance, citations, accuracy monitoring, and freshness controlscase studies: hours saved, quality gains, and revenue impactfailure patterns: infra overruns, integration debt, and weak curationfour principles: exec sponsorship, domain experts, user focus, workflow redesignWe break down the decisions that matter: how to chunk documents so the agent can both recall facts and reason across context, how to enrich content with metadata that signals authority and freshness, and how to fuse vector semantics with keyword precision for queries that mix intent with exact terms like product codes and financial acronyms.  On the engineering side, we cover architecture trade‑offs between vector databases and native hybrid search, secure connectors into CRM and ERP systems, and the governance needed for citations, audits, accuracy monitoring, and content freshness.  You’ll hear where teams slip - capacity spikes, weak document prep, brittle identity integrations - and how to design for elasticity and compliance from day one. The proof is in production. Uber’s engineering co‑pilot reclaimed thousands of hours and raised answer quality; JP Morgan Chase scaled insights to more than two hundred thousand employees and unlocked major business value; Goldman Sachs is pushing beyond retrieval to application, where the agent drafts, analyses, and accelerates financial workflows.  Across these stories, a shared blueprint emerges: executive sponsorship, domain expert curation, user‑centred iteration, and workflow redesign that embeds the agent into daily decisions. If you’re ready to turn proprietary knowledge into a real moat and to build a platform that compounds value across use cases this conversation offers the playbook. Enjoyed the episode? Follow, rate, and share with a colleague who’s building AI into their workflow, and leave a review with the biggest knowledge challenge you want us to tackle next. Like some free book chapters?  Then go here How to build an agent - Kieran Gilmurray Want to buy the complete book? Then go to Amazon or  Audible today. Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    21 Min.
  8. Congrats, You Trained The Bot That Took Your Job

    16. FEB.

    Congrats, You Trained The Bot That Took Your Job

    Stop asking what AI can do and start asking what it can’t. We dig into fresh MIT Sloan research that maps the human edge with EPOCH - empathy, presence, opinion, creativity, and hope - and show why these capabilities predict safer, more meaningful careers as automation spreads.  Along the way, we dismantle the “junior trap,” where digital natives get handed AI strategy without the system fluency to manage risk, and we lay out a pragmatic playbook for leaders who need to design guardrails that scale. At A Glance / TLDR: • reframing the job worry to human‑intensive skills • EPOCH explained: empathy, presence, opinion, creativity, hope • empathy as connection not detection • presence for physical work and serendipity • accountable judgment over probabilistic answers • creativity through humour and improvisation • hope and subjective belief beating status‑quo data • why the junior trap misallocates AI strategy • task‑level fixes versus system‑level risk design • citations over explanations for trustworthy outputs • clearing the data bottleneck with royalties for expertise • safe augmentation with fatigue‑aware use cases • J&J skills inference and career lattices • equity risks, unions, freelancers, and burnout We get specific about how to match use cases to model reliability, why experts ask for citations instead of explanations, and how to treat a model like a brilliant yet untrustworthy database.  Then we tackle the data bottleneck blocking real enterprise value: your best people hold the patterns your AI needs, but sharing that craft can devalue their advantage. The fix is economic, not technical. Think royalties and residuals for employee‑generated training data, turning knowledge transfer into an asset instead of a threat. If a salesperson’s workflows lift model close rates, a share of that lift should flow back to the source. You’ll also hear how Johnson & Johnson used skills inference to surface hidden strengths from everyday work, moving from rigid ladders to flexible career lattices. We balance the promise of augmentation - like fatigue‑aware support for radiologists - with the reality of equity and burnout, spotlighting why unions won protections while freelancers face steep declines.  The throughline is simple: models predict the future from the past; humans create futures that never existed. Keep empathy at the centre, design for serendipity, hold judgment where accountability lives, cultivate real creativity, and defend hope as a strategic asset.  If this conversation helps you rethink your AI strategy or your own career moat, follow the show, share with a friend, and leave a quick review - what’s your strongest EPOCH skill? Support the show 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 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

    17 Min.
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Info

Kieran Gilmurray is a globally recognised authority on Artificial Intelligence, intelligent automation, data analytics, agentic AI, leadership development and digital transformation. He has authored four influential books and hundreds of articles that have shaped industry perspectives on digital transformation, data analytics, intelligent automation, agentic AI, leadership and artificial intelligence. 𝗪𝗵𝗮𝘁 does Kieran do❓When Kieran is not chairing international conferences, serving as a fractional CTO or Chief AI Officer, he is  delivering AI, leadership, and strategy masterclasses to governments and industry leaders.  His team global businesses drive AI, agentic ai, digital transformation, leadership and innovation programs that deliver tangible business results.🏆 𝐀𝐰𝐚𝐫𝐝𝐬: 🔹Top 25 Thought Leader Generative AI 2025  🔹Top 25 Thought Leader Companies on Generative AI 2025  🔹Top 50 Global Thought Leaders and Influencers on Agentic AI 2025🔹Top 100 Thought Leader Agentic AI 2025 🔹Top 100 Thought Leader Legal AI 2025🔹Team of the Year at the UK IT Industry Awards🔹Top 50 Global Thought Leaders and Influencers on Generative AI 2024 🔹Top 50 Global Thought Leaders and Influencers on Manufacturing 2024🔹Best LinkedIn Influencers Artificial Intelligence and Marketing 2024🔹Seven-time LinkedIn Top Voice.🔹Top 14 people to follow in data in 2023.🔹World's Top 200 Business and Technology Innovators. 🔹Top 50 Intelligent Automation Influencers. 🔹Top 50 Brand Ambassadors. 🔹Global Intelligent Automation Award Winner.🔹Top 20 Data Pros you NEED to follow. 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 Kieran's team to get business results, not excuses.☎️ https://calendly.com/kierangilmurray/30min ✉️ kieran@gilmurray.co.uk  🌍 www.KieranGilmurray.com📘 Kieran Gilmurray | LinkedIn

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  • Erstellt von
    Kieran Gilmurray
  • Jahre aktiv
    2022 - 2026
  • Folgen
    195
  • Bewertung
    Unbedenklich
  • Copyright
    © 2026 The Digital Transformation Playbook
  • Sendungswebsite
    The Digital Transformation Playbook

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