How The Next Workforce Will Redefine Business With Everyday AI
The Digital Transformation Playbook
Forget “early adopters.” A new cohort arrives at work expecting intelligent tools by default. We unpack what it means to hire and lead AI natives—the people who open ChatGPT before Google, who treat Grammarly and Canva as standard kit, and who view AI not as innovation but as basic competence. Their expectations are clear: recruitment that feels intelligent rather than bureaucratic, internal tools that run as smoothly as their favourite apps, and leaders who understand how AI works and use it responsibly.
TL;DR:
- AI natives start work with intelligent tools
- using AI framed as baseline competence
- Expectations for mature, AI-ready organisations
- Recruitment that feels intelligent, not bureaucratic
- Internal tools that are fast, intuitive, personalised
- Purpose, psychological safety, visible leadership
- Well-being and flexibility as expectations
- Leaders who understand and use AI responsibly
- Growth over hierarchy with coaching and mentoring
- Upskilling across all generations
- Redesigning workflows with measurable impact
- Reverse mentoring for faster leadership learning
- Continuous learning at the core of culture
We walk through the practical shifts that help any organisation catch up. First, build digital confidence at every level with targeted upskilling and prompt craft, not just one-off workshops. Then redesign workflows to remove toil and add intelligence, measuring impact in time saved, quality lifted, and happier customers. Reverse mentoring helps senior leaders learn from younger colleagues, while clear guardrails for data, privacy, and ethics keep experiments safe. We talk purpose and psychological safety too, because teams need room to try, fail, refine, and learn without fear.
Customers already expect Amazon-like personalisation and Netflix-level relevance; employees now expect the same inside their workplace. That means faster onboarding, smarter internal search, AI-assisted drafting, and decision support that keeps humans accountable. We share how to move from scattered tools to integrated intelligence: playbooks, prompt libraries, coaching, and visible leadership that models responsible use. If you want to attract and retain AI-native talent—and help everyone else thrive alongside them—this is your roadmap to a learning-first, human-led, AI-augmented culture.
If this resonates, follow the show, share it with a colleague, and leave a quick review to help more leaders find it. What’s the first workflow you’ll redesign with AI?
Read the full article here: What AI Natives Mean for the Future of Your Business & Work
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
Agentic AI, Explained Simply
The Digital Transformation Playbook
The day starts with pings, alerts, and an inbox that won’t quit—yet nothing meaningful moves. We set out to change that by exploring agentic AI: systems that don’t wait for prompts, but act within clear boundaries to learn your preferences, anticipate needs, and take initiative on the work that drains your focus.
TL;DR:
- Agentic AI defined as autonomous, bounded collaborators
- Reclaiming time via email triage, scheduling, and data hygiene
- Personalised curation to cut information overload
- AI as creative partner for writing, design, and music
- Proactive wellness insights and mental health support
- Accessibility through speech-to-text, vision aids, and tailored UIs
We break down real wins at work and home. Think email agents that prioritise and draft in your tone, schedulers that protect deep work, and project managers that adapt plans as priorities shift. Then we zoom into personal growth: adaptive learning that meets you where you are, creative partners that spark ideas without flattening your voice, and curated leisure that replaces choice overload with experiences that fit your mood.
Along the way, we share concrete examples—from research curation to travel planning and price tracking—that show how autonomous AI turns chaos into clarity.
Well-being and inclusion are centre stage. We look at proactive health insights powered by wearables, mental health support that responds in the moment, and accessibility agents that translate speech, describe scenes, and tailor interfaces to individual needs.
Smart homes round out the picture, coordinating energy use, comfort, and safety for seniors and busy families alike. Throughout, we emphasise trust: privacy by design, transparency about limits, and human override to keep you in control.
If you want fewer shallow tasks and more meaningful progress, this is a roadmap for working with AI as a responsible partner. Subscribe, share with a friend who needs their time back, and leave a review telling us which agent you’d deploy first.
Why not buy the book on Amazon or the audio book from Audible.com?
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
Lead AI by Leading People
The Digital Transformation Playbook
The loudest voices say AI will fix everything; the quieter truth is that behaviour, incentives, and trust decide whether it works at all. We sit down with CPO Brian Parkes to get past the noise and talk about what actually moves an organisation from AI theatre to real outcomes.
Fear, imposter syndrome, and quarterly pressure make leaders cling to control, yet value shows up only when teams collaborate across silos and redesign workflows end to end.
TL;DR:
- Hype versus behavioural reality of AI
- Executive fear, imposter syndrome, and incentives
- Gap between C-suite intent and frontline capacity
- Reverse mentoring and small experiments
- Board-level questions on mission, analysts, and ethics
- Reframing AI as augmentation, not replacement
We dig into the gap between C-suite intent and frontline reality—where overloaded teams are asked to learn a “second job” just to keep up. Instead of rolling out tech first and patching people later, we map a different path: start with a precise problem, anchor it to mission, and assemble a cross-functional owner group with shared accountability.
Reverse mentoring becomes a zero-budget unlock that lets senior leaders learn from practitioners already using AI. Small, time-boxed experiments replace 18-month slide decks. And partner selection shifts from brand comfort to proven speed and scars, because the right three-month pilot often beats the wrong long programme.
Brian also offers three board-level questions to stop “faster crap” before it starts: What problem are we solving and how does it align to mission? Which analyst concerns or customer pains does this address? What are the ethical and risk implications?
The throughline is culture: trust enables decentralised decisions, and decentralised decisions let AI cut through politics and deliver across workflows.
The final nudge is a reframe—treat AI like the jump from dial-up to broadband. It felt awkward until it didn’t. Respect the risks, invest in people as much as platforms, and let human intelligence amplify artificial intelligence.
If this resonated, follow the show, share it with a colleague who’s wrestling with AI adoption, and leave a review to help others find it.
And if you need help implementing AI in your business then lets chat about getting you the help you need - https://calendly.com/kierangilmurray/executive-leadership-and-development
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
From hype to habits: making AI safe, useful, and fair at work
The Digital Transformation Playbook
Everyone wants the upside of AI; few talk plainly about the downside. We open the box and lay out the real risks HR and L&D teams face—data security, access control, vendor exposure, algorithmic bias, and the slippery problem of hallucinations—then build the guardrails that let you ship with confidence. Governance isn’t a brake pedal; it’s the seatbelt that keeps your organisation moving fast without flying through the windscreen.
TL;DR:
- AI governance as enablement, not bureaucracy
- Vendor risk, GDPR and EU AI Act awareness
- Identifying and reducing algorithmic bias in hiring
- HR and L&D as ethical gatekeepers and trainers
- Risk registers, documentation, and stakeholder alignment
- Incident readiness: response plans and communication
- Skills building through structured training and repeatable patterns
We start with the essentials: mapping data flows, enforcing least privilege, pressure-testing vendors, and keeping GDPR and the EU AI Act firmly in view. From there, we tackle bias with concrete steps—fairness metrics, pre-deployment testing, debiasing techniques, and human-in-the-loop controls—anchored by a candid look at high-profile failures and what they teach us. Hallucinations get the scrutiny they deserve as we turn critical thinking into a repeatable practice: tighter prompts, grounded answers, and validation workflows that prevent confident nonsense from slipping into policy or hiring decisions.
Throughout, we position HR and L&D as ethical gatekeepers and capability builders, the people best placed to train models responsibly and teach the business to use them well. That means a living risk register, clear roles, practical training, and a tested incident plan—because resilience is won on quiet days, not crisis days. If you want AI that is safe, fair, and actually useful, this conversation gives you the blueprint and the language to lead.
If this resonated, follow the show, share it with a colleague who’s wrestling with AI adoption, and leave a review telling us the one risk you want help tackling next.
Exciting New HI for HR and L&D Professionals Course:
Ready to move beyond theory and develop practical AI skills for your HR or L&D role? We're excited to announce our upcoming two-day workshop specifically designed for HR and L&D professionals who want to confidently lead AI implementation in their organizations.
Join us in November at the beautiful MCS Group offices in Belfast for hands-on learning that will transform how you approach AI strategy.
Check here details on how to register for this limited-capacity event - https://kierangilmurray.com/hrevent/ or chat https://calendly.com/kierangilmurray/hrldai-leadership-and-development
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
Inside Uber’s Machine-Managed Workforce And What It Means For Work
The Digital Transformation Playbook
Your boss might already be a line of code. We dive into the world of algorithmic management through the lens of Uber, where software now assigns rides, sets prices, monitors performance, and effectively manages millions of drivers at once.
The draw is obvious: lightning-fast decisions, tighter demand–supply balance, and shorter passenger wait times.
But beneath the efficiency lies a deeper story about power, agency, and the human cost of being directed by systems you can’t question.
TL;DR:
- How Uber’s app allocates rides, tracks behaviour, and sets pay
- Ratings and GPS data as continuous performance control
- Efficiency gains versus worker agency and appeal rights
- Spread to Amazon, Deliveroo, Lyft, and autonomous fleets
- Documented stress, surveillance, and lower job satisfaction
- Bias risks, transparency gaps, and regulatory scrutiny
- proposals for audits, explainability, and hybrid human review
We walk through how the app governs every step of work, from GPS tracking to five-star ratings that shape access to future jobs. Then we pull the camera back to examine how the same approach runs through Amazon warehouses, Deliveroo deliveries, Lyft dispatch, and autonomous fleets like Waymo.
Along the way, we surface the trade-offs: frictionless routing and pricing on one hand; opaque metrics, sudden income swings, and limited appeal rights on the other.
Research points to rising stress and lower job satisfaction under constant monitoring, while bias in training data can scale inequalities when left unchecked.
Rather than accept a false choice between speed and fairness, we explore what a better model could look like. Think hybrid management that pairs machine efficiency with timely human review, transparent pay formulas, clear dashboards that flag errors, and regulations that demand explainability, independent audits, and portable worker data.
If algorithmic management is becoming a defining feature of modern work, the challenge is to shape it with dignity, accountability, and trust. If this conversation resonates, follow the show, share it with a friend, and leave a review to help more curious listeners find us.
Read my article here: 8 Proven Ways Agentic AI Delivers Business Value
Photo by Charles Forerunner on Unsplash
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
The $5 Trillion Shift To AI-Driven Buying
The Digital Transformation Playbook
Imagine never opening twenty tabs to compare flights, hotels or warranties again. Instead, an AI agent that understands your budget, tastes and timing quietly negotiates on your behalf, bundles the best options and asks for approval only when it truly matters. That’s the leap from automation to delegation—and it’s poised to reshape retail at global scale.
TL;DR:
- Delegation beyond automation and the end of shopping friction
- Real-world orchestration example of a full-family move
- Three buying models: agent-to-site, agent-to-agent, brokered
- How ads and SEO lose power to agent optimisation
With Google NoteBook LM agents assistance we dive into the mechanics and implications of agentic commerce, where autonomous systems anticipate needs, transact across competing platforms and coordinate complex outcomes.
You’ll hear how three models—agent-to-site, agent-to-agent and brokered interactions—power everything from simple bookings to full-life projects like moving house.
Underneath it all sit the protocols that make agents interoperable: Model Context Protocol for shared meaning, Agent-to-Agent for coordination and AP2 for secure, auditable payments across card networks, wallets and even crypto.
As agents optimise for outcomes rather than aesthetics, the economics of discovery flip. Ads and SEO tricks lose sway, while structured data, reliability and machine-verifiable value rise.
We outline six upgrades retailers must make to stay visible to agents: machine-readable discovery, personalisation that proves itself, A2A-ready commerce platforms, autonomous-safe payments and fraud, connected stores with real-time inventory and maps, and logistics that are fast and predictable.
New revenue streams emerge through multi-brand bundles with revenue sharing, success fees on negotiated value and contextual sponsorships where brands become the default inside devices and planning flows.
Trust is the cornerstone. We map five pillars—agent verification, human-in-the-loop controls, transparent reasoning, rigorous data security and responsible governance—and examine the risks of systemic cascades, unclear liability and cross-border data rules.
The takeaway is clear: commerce is shifting from clicks to intent, and the question isn’t how to find customers, but how to become agent-discoverable and earn an algorithm’s loyalty. If that future excites or worries you, subscribe, share this episode and leave a review with the one task you’d delegate to an AI first.
Link to full article: Agentic commerce: How agents are ushering in a new era | McKinsey
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
What happens when HR stops guessing and starts predicting with AI and analytics
The Digital Transformation Playbook
Guesswork is expensive. We dig into how HR and L&D can turn everyday signals—surveys, onboarding chats, training feedback, and attrition patterns—into reliable foresight with the help of AI. The goal isn’t flashy dashboards; it’s fewer surprises, smarter hiring, clearer development paths, and decisions that hold up under pressure.
TL;DR:
- Why HR data is underused and how AI compresses time to insight
- The difference between insight and foresight in people analytics
- When agentic AI helps and when it harms trust
- Lifecycle touchpoints to capture meaningful signals
- Asking better questions leads to better decisions
- Building analytics confidence and skills inside HR and L&D functions
We break down the difference between insight and foresight in plain language, then show how to move from reactive firefighting to proactive planning. You’ll hear a concrete turnover example where simple analytics smoothed recruitment cycles, reduced cost spikes, and protected onboarding quality. We also explore where AI earns its keep: structuring messy qualitative feedback, highlighting hidden drivers across teams and seasons, and shaping the same truth for very different audiences—executives who want scenarios and risk, managers who need timing and actions, and employees who want relevance and growth.
Along the way, we look at agentic AI and digital labour with nuance. Some tasks are perfect for automation; others demand a human touch. We unpack why exit interviews shouldn’t be your only listening point and make the case for onboarding interviews that capture expectations when they’re fresh—and influence the week‑one decision that often sets retention. Finally, we push on the skill that changes everything: asking better questions. When questions improve, data quality rises, insights sharpen, and the organisation gains a calmer operating rhythm.
If you’re ready to trade gut feel for grounded foresight, tune in and take notes. Subscribe for more practical people analytics, share this with a colleague who lives in spreadsheets, and leave a quick review telling us what question you’ll ask your team next.
Exciting New HI for HR and L&D Professionals Course:
Ready to move beyond theory and develop practical AI skills for your HR or L&D role? We're excited to announce our upcoming two-day workshop specifically designed for HR and L&D professionals who want to confidently lead AI implementation in their organizations.
Join us in November at the beautiful MCS Group offices in Belfast for hands-on learning that will transform how you approach AI strategy.
Check here details on how to register for this limited-capacity event - https://kierangilmurray.com/hrevent/ or chat https://calendly.com/kierangilmurray/hrldai-leadership-and-development
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
AI, Explained Simply
The Digital Transformation Playbook
Curiosity meets clarity as we unpack what AI really is, why it matters today, and how it quietly powers so much of modern life. From the messages you send to the movies you stream and the scans your doctor reads, we trace the path from decades of research to the tools now shaping daily choices.
TL;DR:
- Foundations of machine learning and deep learning
- How language models power chatbots and support teams
- Speech recognition and intent with voice assistants
- Computer vision in healthcare and safety use cases
- Generative text, images, and music with open questions on ownership
- Autonomy on the road and why oversight is needed
- Personalisation, data tracking, and fairness risks
- Multimodal models and unsupervised learning trends
- Regulation, deepfakes, and responsible deployment
We start by demystifying learning from data: how models train on text, images, and audio, and why feedback loops make them sharper over time. Then we dive into large language models and the chatbots built on them—how they handle context, summarise information, and scale support across banking, education, and customer service. Voice takes the spotlight next, with natural language processing turning speech into intent so assistants can check weather, move money, or manage reminders with surprising accuracy.
Vision changes the game in healthcare and safety, where systems detect tumours, fractures, and hazards at speed, supporting clinicians rather than replacing them. Creativity gets a boost with generative AI that drafts articles, composes music, and renders images from plain prompts. That power sparks new questions about copyright, consent, and compensation—issues creators and lawmakers are racing to resolve. We also look at autonomy on the road, where self-driving features rely on real-time perception and strict oversight to navigate messy, human streets.
Personalisation brings both convenience and concerns. By analysing searches, clicks, and purchases, AI predicts preferences to serve recommendations and ads, raising tough questions about privacy, fairness, and control. Finally, we explore the frontier: multimodal models that understand text, images, and speech together, and unsupervised learning that uncovers patterns without human labels. With benefits come risks—bias, misinformation, deepfakes—and emerging rules like the EU AI Act aim to keep innovation accountable and transparent.
If this guide sharpened your understanding, follow the show, share it with a friend who’s AI-curious, and leave a quick review to help others find it.
Your questions shape future episodes—what should we dig into next?
Why not read the full article here: AI for Beginners: Understand the Basics Fast
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
AI for HR and L&D: Start Small, Think Big
The Digital Transformation Playbook
Forget the hype around massive AI transformations and budget-busting implementations. What HR and L&D professionals truly need are practical, accessible solutions that address everyday challenges without requiring a computer science degree or extensive resources.
TL;DR:
- Start with simple AI applications focusing on employment lifecycle pain points
- Job descriptions can be enhanced with AI while maintaining your organizational voice
- Technical terms and fear of the unknown often create barriers to AI adoption
- Map your team's activities to identify where AI can add most value
- The goal isn't just efficiency but reinvesting saved time into meaningful work
- Developing good prompting skills is essential for quality AI outputs
- With minimal training, you can save significant time while improving work quality
This candid conversation cuts through the noise to reveal how AI can enhance the entire employment lifecycle with minimal investment. From crafting more engaging job descriptions to revolutionizing performance management, we explore tangible applications that save time while improving quality. Imagine having an AI assistant that helps generate meaningful performance metrics or provides real-time feedback during difficult conversations – these aren't futuristic concepts but accessible tools available right now.
We tackle the elephant in the room: the fear factor that prevents many HR professionals from embracing AI. Technical jargon and constant innovation can be intimidating, but the solution lies in focusing on specific business problems rather than the technology itself. By mapping team activities and identifying bottlenecks, you can pinpoint where AI delivers genuine value. Most importantly, we emphasize that successful implementation isn't just about efficiency – it's about what you do with the time you save. Instead of piling on more tasks, reinvest those hours into meaningful work that leverages uniquely human skills.
Ready to start your AI journey? Begin with accessible tools like ChatGPT or Microsoft Copilot, focus on developing strong prompting skills, and apply critical thinking to the results. With our approach of "start small, think big," you'll quickly develop the confidence to transform your HR and L&D practices. Join our upcoming course where you'll gain practical skills guaranteed to save at least 10 hours monthly – because AI adoption doesn't need to be complicated to be revolutionary.
Exciting New HI for HR and L&D Professionals Course:
Ready to move beyond theory and develop practical AI skills for your HR or L&D role? We're excited to announce our upcoming two-day workshop specifically designed for HR and L&D professionals who want to confidently lead AI implementation in their organizations.
Join us in November at the beautiful MCS Group offices in Belfast for hands-on learning that will transform how you approach AI strategy.
Check here details on how to register for this limited-capacity event - https://kierangilmurray.com/hrevent/ or chat https://calendly.com/kierangilmurray/hrldai-leadership-and-development
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
Exciting New HI for HR and L&D Professionals Course
The Digital Transformation Playbook
Exciting New HI for HR and L&D Professionals Course:
Ready to move beyond theory and develop practical AI skills for your HR or L&D role? We're excited to announce our upcoming two-day workshop specifically designed for HR and L&D professionals who want to confidently lead AI implementation in their organizations.
Join us in November at the beautiful MCS Group offices in Belfast for hands-on learning that will transform how you approach AI strategy.
Check here details on how to register for this limited-capacity event - https://kierangilmurray.com/hrevent/ or chat https://calendly.com/kierangilmurray/hrldai-leadership-and-development
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
Coding the Future: How to Build AI Agents That Actually Work
The Digital Transformation Playbook
Artificial intelligence has entered a transformative era with autonomous agents now handling everything from customer service to supply chain optimization without human intervention. These AI systems represent a fascinating middle ground between rigid programming and emergent intelligence—and building them effectively requires understanding the full spectrum of development approaches.
TL;DR:
- Low-code platforms like Langchain and Lama Index provide pre-built components and visual interfaces for rapid development
- Customer service autoresponders built with low-code tools can quickly process inquiries and deliver contextually relevant responses
- Low-code solutions have limitations in customization and may be affected by changes in third-party services
- Hybrid approaches leverage low-code for routine tasks while using custom code for specialized functionality
- Best practices for hybrid systems include modular design, clear interfaces, robust testing, and scalability planning
The journey from conceptualizing an AI agent to deploying it spans a continuum from accessible low-code solutions to sophisticated custom development. Low-code platforms like Langchain and Lama Index democratize AI development through visual interfaces and pre-built components, making them ideal for rapid prototyping and straightforward use cases. A customer service autoresponder, for instance, can be quickly assembled by connecting CRM systems with language model APIs. However, these solutions often trade customization for convenience, limiting their applicability for specialized or high-performance requirements.
For organizations seeking both speed and specificity, hybrid approaches offer compelling advantages. By combining low-code efficiency for routine operations with custom code for critical components, teams can achieve the perfect balance of rapid deployment and tailored functionality. Full-code development, while requiring greater technical expertise and time investment, provides unmatched control and performance for complex applications.
Well-designed agents built from scratch incorporate sophisticated memory systems, advanced reasoning capabilities, and precise action mechanisms—with Python emerging as the language of choice for these bespoke solutions.
As AI technology evolves, the boundaries between development approaches continue to blur, suggesting a future where natural language instructions can scaffold sophisticated agent architectures. What approach will you choose for your organization's AI journey?
📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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
AI and Humans: The Future of Hybrid Work
The Digital Transformation Playbook
Navigating the complexities of hybrid work remains a significant challenge for organizations worldwide. Four years into this working model, many still struggle with burnout, disengagement, and unclear policies. Employees come to the office only to continue remote working behaviours – like video conferencing with colleagues sitting just two desks away. As these challenges persist, could artificial intelligence offer meaningful solutions?
TL;DR:
- The EU AI Act requires companies to train employees on workplace AI tools, highlighting the importance of proper implementation
- L&D professionals are key to successful hybrid work models
- Most AI implementation failures stem from poor planning, lack of strategic alignment, or trying to replace rather than augment human capabilities
- Successful AI integration in HR requires identifying specific pain points and measuring outcomes against clear metrics
This thought-provoking discussion explores the intersection of AI, human resources, and learning development in the hybrid workplace. We examine how sentiment analysis can provide valuable insights into employee wellbeing when implemented transparently and ethically. The conversation emphasizes that while technology creates efficiencies, it cannot solve fundamental people management issues. Success requires balancing AI capabilities with human touch and proper training.
The discussion highlights a critical but often overlooked aspect of technology implementation – training. As one compelling example reveals, some organizations invest millions in technology only to discover employees aren't using it effectively because no budget remained for proper training. We explore how L&D professionals can leverage AI to create personalized, role-specific training that addresses the unique challenges of hybrid environments while freeing HR teams from administrative burdens to focus on strategic human interaction. Additionally, we delve into how AI-powered analytics can transform existing human capital data into predictive insights, enabling truly data-driven HR decisions.
The potential for AI to enhance workplace productivity and engagement is enormous, but success depends on strategic implementation. With proper planning, clear alignment to business objectives, and realistic expectations, organizations can avoid becoming part of the estimated 90% of bespoke AI applications that fail to deliver ROI. The exciting reality is that AI implementation doesn't require massive budgets – accessible tools exist for organizations of all sizes. Join us as we unpack how to successfully blend human expertise with AI capabilities to create more effective, engaging hybrid workplaces.
Exciting New HI for HR and L&D Professionals Course:
Ready to move beyond theory and develop practical AI skills for your HR or L&D role? Then join us in November at the beautiful MCS Group offices in Belfast for hands-on learning that will transform how you approach AI.
Check here details on how to register for this limited-capacity event - https://kierangilmurray.com/hrevent/ or chat https://calendly.com/kierangilmurray/hrldai-leadership-and-development
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
Navigating the Future: Inside the Explosive Growth of Agentic AI
The Digital Transformation Playbook
The AI agent revolution is here, transforming how businesses operate and compete in ways that were once confined to science fiction. From virtual assistants scheduling your meetings to sophisticated systems analyzing medical images with superhuman accuracy, these technologies are no longer experimental—they're driving real business value across industries.
TL;DR:
- AI agents perceive environments, process information, and act to achieve specific goals
- Modern AI agents use machine learning to continuously refine responses and adapt strategies
- The global AI market is projected to grow from $214.6 billion in 2024 to $1,339.1 billion by 2030
Our deep dive into the agentic AI ecosystem reveals a market exploding with potential, projected to grow from $214.6 billion in 2024 to over $1.3 trillion by 2030. This isn't just incremental growth; it represents a fundamental reimagining of how work gets done and value is created in the digital economy.
The competitive landscape tells a fascinating story of innovation and strategic positioning. Tech giants like Google, Microsoft, and Amazon leverage their vast resources and ecosystems to dominate, while specialized players like IBM Watson focus on high-value enterprise applications. Meanwhile, companies like Pega Systems are differentiating through responsible AI governance—their Agent X platform tackles the industry-wide challenge of unreliable AI agents by embedding governance directly into workflows, making them the preferred choice for regulated sectors.
Regional dynamics add another layer of complexity. North America maintains its innovation lead through strategic export controls on critical semiconductor technologies, while European firms balance regulatory rigor with technological advancement. In Asia, disruptive innovators like DeepSeq are challenging established players with localized, cost-effective solutions.
The real-world impact is already profound. Healthcare institutions use AI to analyze medical images, accelerating diagnoses and reducing errors. Financial firms deploy autonomous agents to detect fraud and assess risk in real-time. Retailers use conversational AI to deliver personalized recommendations, boosting engagement and sales.
Looking ahead, we see enhanced personalization, edge computing integration, and increased focus on explainable AI shaping the next wave of innovation. The organizations that will thrive are those investing now in robust data governance, continuous innovation, and ethical AI practices—creating solutions that are not just powerful, but transparent, accountable, and aligned with broader organizational values.
Ready to leverage AI agents as catalysts for innovation and competitive advantage?
Subscribe to our podcast for regular insights on navigating the AI revolution.
📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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
The Future is Now: How HR and L&D Professionals Can Master AI
The Digital Transformation Playbook
The rapid acceleration of AI adoption has created a turning point for HR and Learning & Development professionals. No longer can they afford to simply observe from the side lines – they must now actively lead their organizations through this technological revolution with confidence and strategic insight.
TL;DR:
- HR and L&D practitioners need to be viewed as strategic influencers who must guide AI adoption across businesses
- Fear of AI stems from lack of knowledge – developing deeper understanding builds confidence
- Human and digital workforces will collaborate, requiring rethinking of organizational structures
- Change management and stakeholder engagement are critical for successful AI implementation
- AI should augment human capabilities rather than replace them entirely
- HR and L&D professionals must develop practical skills to lead AI transformation
What makes this moment particularly challenging is the complexity surrounding AI implementation. HR leaders are suddenly expected to understand not just the technology itself, but also navigate the ethical considerations, governance frameworks, and change management strategies required for successful integration.
Without developing these capabilities, they risk losing their seat at the table when critical decisions about organizational transformation are being made.
Throughout our conversation, we explore how fear often stems from lack of knowledge, and why developing practical AI skills is essential for HR professionals who want to maintain strategic influence.
We discuss the delicate balance between embracing automation while preserving the uniquely human aspects of work, and why transparent communication is crucial when implementing new technologies.
Rather than seeing AI as a threat to jobs, we position it as an opportunity to elevate HR work by automating administrative tasks while creating space for more complex, relationship-driven activities that machines cannot replicate.
Exciting New HI for HR and L&D Professionals Course:
Ready to move beyond theory and develop practical AI skills for your HR or L&D role? We're excited to announce our upcoming two-day workshop specifically designed for HR and L&D professionals who want to confidently lead AI implementation in their organizations.
Join us in November at the beautiful MCS Group offices in Belfast for hands-on learning that will transform how you approach AI strategy.
Check here details on how to register for this limited-capacity event - https://kierangilmurray.com/hrevent/ or chat https://calendly.com/kierangilmurray/hrldai-leadership-and-development
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
The $3 Trillion Question: Can AI Match Human Experts?
The Digital Transformation Playbook
What happens when AI attempts the same complex work as human experts with 14 years of experience? The answer might reshape our understanding of the economic future.
TL;DR:
- GDP Val tests AI on complex, multimodal tasks requiring handling of CAD designs, spreadsheets, and presentations
- Tasks are created from actual professional work products that take humans an average of 7 hours to complete
- Claude Opus performed best with 47.6% of its deliverables rated as good as or better than human experts
- AI shows potential to make workflows 40% faster and 63% cheaper when paired with human oversight
- 3% of AI failures were classified as "catastrophic," including incorrect medical diagnoses and suggestions of financial fraud
- Simple prompt improvements like asking models to self-check their work significantly reduced formatting errors
- Current models still struggle with ambiguity and tasks requiring tacit knowledge or complex human interaction
GDP Val represents a fundamental shift in how we evaluate artificial intelligence. Rather than abstract academic metrics, this new benchmark from OpenAI measures how well frontier AI models handle real-world economic tasks across nine major sectors worth $3 trillion annually.
The methodology is ruthlessly practical—AI models must complete complex assignments that typically take human experts seven hours, handling everything from CAD designs to financial spreadsheets while synthesizing information from up to 38 reference documents.
The results are both promising and sobering. Claude Opus led the evaluation with 47.6% of its outputs rated equal to or better than work from professionals at organizations like Apple, Goldman Sachs, and Boeing. When integrated into realistic workflows with human oversight, these models demonstrated potential to make knowledge work 40% faster and 63% cheaper.
Yet failures remain significant—3% were classified as "catastrophic," including incorrect medical diagnoses and recommendations of financial fraud.
Perhaps most valuable is GDP Val's illumination of where AI currently excels (document formatting, data analysis) and where it falters (following complex instructions, handling ambiguity).
This economic lens offers businesses and policymakers unprecedented clarity about AI's near-term impact on knowledge work, while highlighting that the highest-value human skills—tacit knowledge, real-time collaboration, and complex communication—remain beyond current AI capabilities.
How quickly will that gap close? That's the trillion-dollar question worth pondering.
Listen into a audio version of this report created using Google Notebook LM for your listening pleasure.
Link to research: GDPval.pdf
𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.
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✉️ 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
AI Agents: Tomorrow's Business Revolution
The Digital Transformation Playbook
The business world stands at the precipice of an AI revolution. This episode explores how AI agents - software programs that understand, reason, act, and learn autonomously - are transforming industries and creating unprecedented opportunities.
TLDR:
- • AI agents like AutoGPT demonstrate how AI can break tasks into steps and work independently
- • Healthcare applications include AI systems from Hippocratic AI that handle routine tasks while freeing human doctors for complex cases
- • Retail applications feature AI personal shoppers that consider individual preferences, dietary restrictions, and even local weather
- • Financial AI systems like Wealthfront and Betterment manage investments and are evolving toward real-time market analysis
- • Creative AI collaborates with humans as demonstrated by the band Yacht's AI-assisted album "Chain Tripping"
Far beyond the narrow AI systems of yesterday, today's AI agents demonstrate remarkable adaptability and collaborative potential. When multiple agents work together in compound-agentic systems, they tackle challenges no single AI could manage alone - creating what we might call a symphony of intelligences.
Across healthcare, retail, finance, and creative industries, these technologies are already making their mark. Hippocratic AI assists healthcare professionals with routine tasks, allowing doctors to focus on complex cases. Amazon's Alexa evolves toward managing entire processes like dinner party planning. Financial platforms like Wealthfront optimize investments around the clock. Even artists are finding AI to be valuable collaborators, as demonstrated by the band Yacht's AI-assisted album "Chain Tripping."
The business opportunities are extraordinary—from hyper-personalized services to intelligent process automation. In Singapore, AI optimizes traffic flow in real-time, reducing travel times by 15% and emissions by 20%. Drug discovery companies like Insilico Medicine have used AI to identify promising compounds in weeks rather than years. These capabilities are enabling entirely new business models, from AI-as-a-Service platforms to outcome-based pricing that aligns incentives between providers and customers.
Yet challenges remain. Organizations must navigate ethical concerns about bias, regulatory questions about liability, and potential economic disruption as jobs evolve. As we move forward, success will belong to those who can adapt, innovate, and collaborate - not just with humans, but with the intelligent agents becoming our partners in progress.
Ready to explore how AI agents might transform your industry? Subscribe now and join the conversation about the future of business in the age of agentic AI.
📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK
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
Gen Z, AI, and the Mindset Shift Every Leader Needs
The Digital Transformation Playbook
You know what really frustrates me?
When I hear these endless statistics about young people being the most negatively impacted at work.
Because if we keep repeating that story, we’ll start believing it. And then suddenly, no one hires them.
Let me give you an example. My son’s 18. He works with me now. I handed him a task I thought would take days. A few hours later, he came back and said, “Done.”
I was shocked. But here’s the kicker. He said, “I used Make.com, I pulled in Lovable, I set up Replit, threw in Zapier, wrote a few prompts — now the boring part is automated. I’m moving on to the work that actually adds value.”
And that’s the mindset shift we need.
This is why reverse mentorship is on the rise. Older leaders are learning from younger people. Because this generation? They’re already fluent in GPT, Claude, Replit, Make.com, N8N — tools that many companies don’t even allow yet.
The companies that invest in this young talent — instead of believing the doom narrative — will see the biggest returns.
With AI as the amplifier, this generation isn’t a risk. They’re our greatest asset.
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
The Death of Organizational Charts in the AI Age
The Digital Transformation Playbook
Traditional organizational charts are strangling AI adoption. Ruslan Tovbulatov, CMO of Gloat, makes a compelling case for why companies must radically rethink their approach to work structures if they want their AI strategies to succeed.
TLDR:
- The org chart was built for the industrial revolution's command-and-control management style
- AI implementation requires looking beyond job titles to focus on tasks and workflows
- Retitling roles (e.g., content manager to content orchestration) creates the right mindset shift
- AI removes limiting beliefs about capabilities – anyone can design, write, or code with AI assistance
- Internal talent marketplaces allow work to be organized around outcomes rather than job descriptions
The fundamental problem? We're attempting to force cutting-edge AI capabilities into organizational models designed during the railroad era. These 19th-century hierarchies, with their rigid job titles and siloed departments, simply can't accommodate the fluid, task-oriented nature of effective AI implementation. When companies focus on what job titles they're replacing rather than what tasks need technological support, AI initiatives inevitably falter.
Ruslan advocates for a shift from traditional management to work orchestration. This means moving beyond static job descriptions to dynamic roles where employees coordinate between human capabilities and AI tools. Content managers become content orchestrators. Designers become design orchestrators. These aren't mere semantic changes but fundamental mindset shifts that empower employees to leverage AI as an amplifier of their talents.
Perhaps most excitingly, this approach democratizes previously specialized skills. No longer must someone say "I'm not a designer" or "I can't code." With AI assistance, these capabilities become accessible to anyone with the right orchestration mindset. This creates unprecedented opportunities for employee growth and organizational agility.
Companies like Standard Chartered and Schneider Electric are already demonstrating the power of this approach, using internal talent marketplaces to assemble teams based on skills and interests rather than job titles. Projects that once took years now complete in weeks. And as AI agents become increasingly capable teammates, even smaller organizations can benefit from this work orchestration approach.
Ready to reimagine your organization for the AI era? Start by questioning your assumptions about hierarchy, empowering your teams to orchestrate rather than just execute, and focusing relentlessly on work outcomes rather than organizational structure. Your AI strategy and your company's future may depend on it.
Read - The Death of the Org Chart: Why AI Will Fail Without This One Change
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
AI Agents: Build, Deploy, Scale
The Digital Transformation Playbook
The landscape of artificial intelligence is rapidly evolving from systems that handle specific tasks to agentic AI capable of making decisions, acting on complex objectives, and continuously learning. This shift presents extraordinary opportunities for organisations seeking to enhance efficiency and drive innovation – yet a striking gap exists between aspiration and execution.
TLDR:
- Establishing robust governance frameworks with strategic oversight, operational management, and technical implementation layers
- Creating clear accountability systems with executive sponsors, program managers, technical leads, and ethics committees
- Implementing transparent documentation practices and audit trails to build trust
- Developing ethical AI guidelines that ensure fairness, non-discrimination, and privacy protection
- Aligning AI transformation with business goals through comprehensive strategic planning
- Reimagining workflows rather than simply adding AI to existing processes
- Upskilling employees and creating new roles like AI operations specialists and ethics officers
While 97% of organisations feel increased urgency to adopt AI, only 14% are fully prepared according to the Cisco AI Readiness Index. This disconnect stems from uncertainties around governance, organisational readiness, and scaling complexities. Successful implementation requires a comprehensive framework addressing these challenges head-on.
At the foundation lies robust governance with clear accountability systems. Executive sponsors align AI with business goals, program managers oversee implementation, technical leads refine algorithms, and ethics committees guard against bias. Consider UPS's Orion system, which optimised delivery routes while supporting sustainability objectives, or Tesla's continuous Autopilot updates using real-time data from millions of vehicles.
Transformation extends beyond technology to people and processes. DHL reimagined warehouse operations around AI capabilities, increasing fulfillment rates by 180%. The NHS overcame clinician skepticism when deploying AI for cancer detection through transparent communication and celebrating quick wins. New roles are emerging – from AI operations specialists to ethics officers – reflecting the growing need for specialised expertise.
Scaling requires strategic alignment with measurable outcomes, robust infrastructure, continuous monitoring, and leadership commitment. Amazon's fulfillment centres demonstrate how scalable infrastructure handles global operations, while General Electric's struggles with its Predix platform serve as a cautionary tale about insufficient alignment with business goals.
Ready to transform your organisation with agentic AI? Start with governance, reimagine processes, prepare your people, and build scalable systems. The future belongs to those who act decisively and responsibly today.
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
AI Agents: The New Workplace Partners
The Digital Transformation Playbook
Artificial intelligence has undergone a remarkable evolution, but agentic AI represents something truly transformative – autonomous systems that make decisions and take actions with minimal human oversight. This technology goes far beyond traditional automation to deliver something more akin to a collaborative partner than a simple tool.
TLDR:
- Agentic AI operates autonomously, making decisions without direct human control while adapting to new information in real-time
- Traditional RPA follows pre-programmed rules while agentic AI makes independent decisions based on goals
- Some agentic systems incorporate "humans in the loop" for critical decisions, while others function completely autonomously
- Applications span industries including healthcare (diagnosis assistance), finance (fraud detection), HR (recruitment), and customer support (advanced chatbots)
What makes agentic AI revolutionary is its ability to adapt to unforeseen circumstances while pursuing defined goals.
Unlike Robotic Process Automation (RPA) which follows strict rules, or generative AI which creates content, agentic systems actively engage with their environment, anticipate needs, and independently navigate complex scenarios.
The distinction becomes clear when examining practical applications: an AI-driven investment advisor autonomously adjusting portfolios based on market predictions, or an underwater exploration vehicle making real-time navigation decisions in extreme environments where human intervention isn't possible.
The business implications are profound across sectors. For example,
- Healthcare organizations implement AI that analyzes patient data while keeping doctors in the decision loop.
- Financial institutions deploy systems that continuously monitor for fraud patterns.
- HR departments leverage AI agents to transform recruitment, while customer support teams employ advanced conversational bots that learn from every interaction.
Companies including Oracle, Workday, and Salesforce are already deploying these capabilities to drive competitive advantage. However, successful implementation requires more than technology adoption – it demands fundamentally rethinking business processes and addressing important ethical considerations around data privacy, bias, and accountability.
For organizations willing to embrace this transformation thoughtfully, agentic AI offers unprecedented opportunities to enhance human capabilities, drive efficiency, and lead innovation in a rapidly evolving landscape. How will your organization harness this powerful new technology?
If you enjoyed this chapter then why not buy the book on Amazon or the audio book on Audible.com?
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
Leaders must evolve or risk talent exodus in the AI revolution
The Digital Transformation Playbook
The technological landscape is rapidly evolving, and nowhere is this more evident than in the emergence of AI agents as integral team members across industries. This transformation demands a new breed of leader – one who can navigate the delicate interplay between human creativity and AI efficiency while fostering trust and collaboration.
TLDR:
- AI agents fundamentally alter workplace dynamics, allowing humans to focus on creative tasks while AI handles repetitive functions
- Successful implementation across sectors shows significant benefits: 47% reduced overstock in retail, 25% fewer diagnostic errors in healthcare, 360,000 work hours saved in finance
- Leaders must clearly define roles and set expectations for both human and AI contributions
- Transparent communication and reskilling initiatives help build trust during AI adoption
- By 2030, AI agents will be as integral as human employees, requiring leaders who can foster collaboration between both
Across sectors, we're witnessing remarkable success stories when leadership gets this balance right. In retail, AI-driven inventory management has reduced overstock by 47%. Healthcare organizations have decreased diagnostic errors by 25% through AI integration. Financial institutions like JPMorgan Chase have saved hundreds of thousands of work hours with AI-powered document processing. But these gains don't materialize automatically – they come through proactive leadership that addresses team concerns about job displacement while implementing robust training programs.
The most effective leaders in this new paradigm possess both technical literacy and emotional intelligence. They understand AI's capabilities and limitations while skillfully navigating the fears and anxieties that often accompany technological change. They create environments where roles are clearly defined, expectations are set, and both human and AI contributions are valued. These leaders recognize that the journey of AI integration isn't a one-time transformation but an ongoing evolution requiring continuous learning and adaptation.
Looking ahead to 2030, leaders will oversee increasingly blended teams where AI agents are as essential as human employees. The ability to foster genuine collaboration between these different types of intelligence, drive innovation at their intersection, and navigate complex ethical considerations will define successful leadership. Are you prepared to lead in the era of human-AI collaboration? The future belongs to those who can harness this powerful partnership while ensuring technology and humanity thrive together.
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
From Chatbots to Digital Teammates: The Evolution and Future of AI Agents
The Digital Transformation Playbook
Artificial Intelligence has reached a pivotal turning point. Gone are the days when robotic process automation simply followed rigid, predefined paths.
Today's AI agents represent a quantum leap forward - autonomous systems capable of reasoning, making decisions, and taking action without constant human guidance.
TLDR:
- RPA 1.0 was never enough—we need both "clickety-click" automation and "thinkety-think" intelligence
- AI agents have evolved from early symbolic systems to today's sophisticated LLM-powered autonomous systems
- Unlike chatbots or generative AI, agents can reason about which tools to use and take action accordingly
- Multi-agent systems enable collaboration between specialized agents for complex problem-solving
This deep dive explores why traditional automation approaches fall short and how AI agents are revolutionizing business processes across industries.
We trace the remarkable evolution of these systems from their early beginnings in the 1950s to today's sophisticated LLM-powered agents, explaining why they've become what we call "an 80-year overnight success story."
Unlike chatbots limited by their training data or generative AI that creates content but can't act, agents demonstrate true agency by dynamically adapting to situations and executing complex workflows.
The discussion covers essential frameworks and best practices for building effective AI agents, from code-heavy solutions like Langchain to democratized no-code platforms making agent development accessible to everyone.
We explore the critical role of memory management in creating personalized experiences, detailing how vector databases, key-value stores, and knowledge graphs enable agents to remember context and learn from interactions.
The RAG (Retrieval Augmented Generation) architecture emerges as a powerful approach for enhancing agents with external knowledge while maintaining accuracy.
Looking toward the future, we examine multi-agent collaboration systems and envision integrated ecosystems combining specialized agents with user preference models.
Throughout, we emphasize that creating truly valuable AI agents requires more than technical expertise—it demands user-centric design, robust evaluation methods, and a commitment to ethics, privacy, and trust.
The message is clear: AI agents aren't science fiction or tomorrow's technology—they're transforming businesses today, opening new possibilities for automation and intelligence that were previously unimaginable.
If you enjoyed this chapter then why not buy the book on Amazon or the audio book on Audible.com?
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
Would you trade five years of your life for the perfect look?
The Digital Transformation Playbook
What would you sacrifice for beauty? A year of your life? Your dream job? For millions worldwide, these aren't hypothetical questions.
TLDR:
- 61% of women believe being beautiful provides better opportunities in life, up from 46% in 2004
- Nearly 2 in 5 women would sacrifice a year or more of their lives to achieve their ideal appearance
- $305 billion estimated annual cost to US economy from low body esteem
- 45% of young girls believe there's "no excuse not to be beautiful" with today's available products
- Social media creates constant comparison, with AI threatening to establish even more unrealistic standards
- Men increasingly struggle with appearance anxiety - 79% feel they aren't muscular enough
Drawing from a ground breaking global report spanning two decades and 33,000 voices across 20 countries, Google Notebook LM's agents uncover the true weight of beauty standards in 2024. The findings are both illuminating and disturbing – beauty isn't merely a personal concern but a profound social justice, economic, and public health issue with measurable costs.
While 43% of women feel better represented in media today than in 2004, a troubling 66% believe only the most physically attractive women are shown – a significant increase from 50% twenty years ago. The concept of "pretty privilege" has gained undeniable recognition, with 61% of women now believing beauty provides better life opportunities, compared to 46% in 2004.
The digital revolution has transformed how we see ourselves. With over 5 billion social media users globally, we're navigating constant comparison, enhanced by filters that blur reality. Most concerning is the psychological shift: 45% of young girls now believe there's "no excuse not to be beautiful" with today's available products and procedures. As AI threatens to establish even more unrealistic standards, the gap between reality and digital perfection may widen further.
Beauty pressures don't impact everyone equally. LGBTQ+ individuals, people in larger bodies, and communities of color face intensified judgment and systemic barriers. The report also includes men for the first time, revealing 68% feel pressure to be physically attractive, with nearly 80% believing they aren't muscular enough.
Despite these challenges, there are promising signs of change. Younger generations increasingly demand authentic representation and embrace more flexible definitions of beauty. Join us as we explore how we can collectively foster self-esteem and challenge the relentless cycle of impossible standards to redefine beauty on our own terms.
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
The Gift of Slack: Why Less Busy Means More Productive
The Digital Transformation Playbook
Finding balance in today's workplace is like solving a complex riddle. Leaders are caught in a constant tug-of-war between urgent short-term demands and the need for sustainable growth that empowers people. This tension defines the modern work environment, yet only 6% of organizations have mastered it.
TLDR:
- Only 6% of organizations are making significant progress establishing human sustainability as a guiding business strategy
- High-performing organizations are 22 times more likely to openly discuss their decision-making strategies
- Workers spend a staggering 41% of their time on tasks that don't contribute real value
- AI often makes work harder by automating routine tasks and leaving humans with more complex problems
Drawing from Deloitte's 2025 Global Human Capital Trends Report, Google NoteBook LMs AI agents uncover how high-performing organizations transform these tensions into competitive advantage. They're 22 times more likely to openly discuss decision-making strategies, involving diverse stakeholders while avoiding consensus paralysis. The most successful leaders don't choose between business outcomes and human outcomes—they recognize how deeply intertwined these elements truly are.
We explore "stagility"—the delicate balance between worker stability and organizational agility. With three-quarters of workers craving security while 85% of leaders feel pressure for adaptability, companies must create new anchors beyond traditional job descriptions and career paths. The solution lies in reimagined structures, intentional work design, and understanding workers as individuals rather than job titles.
The podcast tackles surprising challenges like the 41% of time workers spend on low-value tasks, AI's hidden impacts on work complexity and isolation, the persistent experience gap, and the evolution of technology value cases beyond simple ROI calculations. We examine how hyper-personalization at the "unit of one" motivates individuals uniquely and why performance management systems need holistic reinvention.
Rather than eliminating managers, forward-thinking organizations are reinventing their roles, emphasizing judgment as the essential capability for navigating complex, unprecedented situations. The future isn't about choosing sides in workplace tensions—it's about finding profound balance that unlocks both human potential and business success.
How might you transform workplace tensions into triumph in your organization? The answer lies not in adaptation, but transformation.
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
The Rise of Agentic AI: Meet Your New Digital Workforce
The Digital Transformation Playbook
Kieran Gilmurray brings three decades of technology expertise to this fascinating exploration of AI's rapid evolution and its profound impact on business and society. With characteristic clarity, he cuts through the hype to deliver practical insights on how organizations and individuals can harness AI's transformative potential.
tldr:
- Exploring agentic AI as digital teammates that can handle complex tasks with minimal human intervention
- The measurable business impacts: 30% productivity improvements, 7-15% sales growth, reduced operational costs
- Why AI implementation requires a top-down approach with clear executive sponsorship
- How today's workforce expects AI-powered tools, creating a "digital Darwinism" that companies must navigate
- The importance of creating a three-legged stool of business strategy, people strategy, and digital strategy
The conversation begins with a historical perspective that contextualizes today's AI revolution. "AI is an 85-year-old overnight success story," Kiran explains, tracing the journey from early computing through various technological inflection points to today's sophisticated AI systems. This historical grounding helps listeners understand why current developments represent something genuinely revolutionary rather than merely incremental change.
Most compelling is Kieran's discussion of agentic AI – digital workers that function as teammates rather than tools. Unlike previous automation technologies that required explicit programming for every scenario, these AI agents can be assigned missions and accomplish them with remarkable flexibility and resilience. From managing emails to conducting research, creating content, and even booking travel, these digital teammates are already transforming productivity for early adopters. The business benefits are substantial: 30% productivity improvements, 20-40% innovation increases, and 7-15% sales growth.
For business leaders, Kiran offers pragmatic guidance on implementation, advocating for a top-down approach with clear executive sponsorship. He warns against the pitfall of endless pilots that never reach production – what he calls "proofs of cost" rather than "proofs of concept." The key is aligning AI initiatives with tangible business outcomes: revenue growth, cost reduction, improved customer experience, or risk mitigation.
What makes this conversation particularly valuable is Kieran's ability to balance technological optimism with practical realism. His message is clear: AI adoption isn't optional but strategic implementation is essential. As he puts it, "Spend more time prepping so that your execution is seamless."
Wondering how to navigate this technological revolution?
Listen now to gain invaluable insights from one of the world's foremost AI strategists, and discover how you can position yourself and your organization to thrive in an AI-powered future.
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
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The Rise of Agentic AI: Meet Your New Digital Workforce
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