Open Source AI’s Quiet Revolution
The Digital Transformation Playbook
The ground under AI has shifted, and the tremor came from the open. What started as a niche movement exploded into a global surge of community models that now challenge the tight grip of the biggest labs.
We trace how open weights, permissive licences, and fast‑moving collaboration pushed open source AI from scrappy experiments to frontier‑level performance and why that matters for builders, researchers, and anyone who cares about power and progress.
TLDR / At A Glance:
- AI’s Linux moment and why it matters
- The Llama leak and Stable Diffusion as catalysts
- How Vicuna, Alpaca, and DeepSeek R1 closed the gap
- Costs, access, and the new builder economy
- Big Tech pivots from secrecy to selective openness
- Ethics and safety trade‑offs in open models
- Governance, licences, and transparency practices
- Geopolitics of openness and national capacity
- Key takeaways on power, participation, and progress
We unpack the sparks that lit the fuse: Meta’s Llama catalysed thousands of forks, Stable Diffusion brought high‑quality image generation to everyday hardware, and a leaked Google memo admitted what many suspected open communities iterate faster.
From there, the story accelerates: Vicuna and Alpaca showed near‑ChatGPT quality for hundreds of dollars; DeepSeek R1 stunned the field with strong reasoning at a fraction of historic training costs; and even once‑guarded players shifted, with OpenAI releasing open‑weight models and Meta deepening its transparent approach.
Along the way, we explore how Hugging Face ecosystems, BigScience, and BLOOM channeled global volunteer energy into rigorously documented, multilingual models that can be audited, improved, and redeployed.
The conversation turns to the hard questions. Openness brings accountability, reproducibility, and shared progress, but also real risks from deepfakes to targeted cyber misuse.
We discuss the emerging toolkit of governance for open models: clear usage licences, dataset transparency, safety evaluations, and public training reports that help regulators and civil society assess risks without freezing innovation.
At a geopolitical level, open models broaden national capacity, decentralise influence, and align with democratic values by dispersing expertise beyond a few corporate or state centres.
If you care about where intelligence lives and who gets to build it, this is a roadmap to the new terrain.
Subscribe, share with a friend who loves (or fears) AI, and leave a quick review to tell us where you stand on the open versus closed debate.
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
Why Digital Workers Can Finally Handle The Boring Stuff So You Can Do The Valuable Work
The Digital Transformation Playbook
Forget brittle rules that collapse on the first exception. We dive into agentic AI for HR and L&D and show how goal‑driven digital workers can process CVs, update HRIS records, draft communications, and handle follow‑ups while staying within clear guardrails and audit trails.
Instead of chasing speed for its own sake, we make the case for redesigning work: orchestrating multiple agents for recruiting, learning operations, and compliance, with a monitoring agent watching everything 24/7 and a human stepping in for judgment calls.
TLDR / At A Glance:
• clear definition of agentic AI for office work
• contrast between RPA rules and goal‑based agents
• HR and L&D use cases across inbox, HRIS and comms
• human‑in‑the‑loop approvals and escalation points
• multi‑agent orchestration with risk and governance oversight
• redesigning processes instead of speeding old workflows
• adoption mindset, access control and data security
• start‑small pilots and simple agent examples
• time savings redirected to strategic HR and L&D work
• upcoming two‑day Belfast event for HR and L&D
Kieran Gilmurray joins us to break down the practical difference between RPA and agentic systems, why resilience matters, and how HR teams can sequence adoption without risking data or trust.
We talk through real use cases across inbox triage, data entry, onboarding, and scheduling, then show how to layer approvals, role‑based access, and digital footprints that actually improve governance.
The result is not a “robot takeover,” but a credible way to give people leaders back 10–30 hours a week for strategic work: workforce planning, skills frameworks, leadership pipelines, and culture.
You’ll hear a simple route to get started: map a day‑in‑the‑life, target the 50–80 percent repeatable tasks, build one agent that delivers measurable time savings, and expand to a multi‑agent system once the value is clear.
With modern point‑and‑click tools, you don’t need to be a developer to build useful assistants; you need clarity on outcomes, sensible safeguards, and a plan to scale what works.
If you’re ready to earn a stronger seat at the table where people, tech, and business strategy meet, this conversation gives you the playbook. If it resonates, subscribe, share with a colleague, and leave a review telling us the first HR task you’d hand to a digital worker.
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
If AI Eats The Routine, What Human Skills Survive?
The Digital Transformation Playbook
The hype cycle is over; the accountability era has arrived. We unpack how gen AI has moved from pilots to proof, with daily use now common among senior leaders and measurable ROI becoming the standard.
Pulling from the Wharton GBK Collective’s year‑three findings, Google Notebook LMs agents trace the three waves of adoption and show why “accountable acceleration” is the defining theme for late 2025.
TLDR / At A Glance:
- Gen AI Usage Is Mainstream
- 82% use Gen AI weekly (+10pp YoY)
- 46% use it daily (+17pp YoY)
- ChatGPT (67%), Copilot (58%), Gemini (49%) dominate
- Interesting note: Gemini grew fastest (+9% YoY)
- 𝗥𝗢𝗜 𝗜s Now Table Stakes for Businesses
- 72% formally track ROI metrics
- 74% report positive returns
- 88% expect budget increases in next 12 months
- 60% now have Chief AI Officers - strategy has moved to the C-suite
- 30% of Gen AI technology spending now goes to internal R&D - enterprises are building custom solutions, not just buying off-the-shelf tools
Across functions, the story is clear: practical, repeatable work is getting faster. Data analysis, meeting and document summarisation, and everyday writing see the broadest gains, while legal and operations post surprising leaps in self‑reported expertise as tools slot into structured workflows.
Google NotebookLMs agents examine the sector split too — tech, telecoms, finance, and professional services are far ahead, while retail and complex physical operations navigate slower integration and tougher data constraints.
ROI is rising, budgets are expanding, and the spend is changing shape. With 88% planning to increase investment and many allocating £5m+ to gen AI, enterprises are shifting 30% of their budgets into internal R&D to build custom capabilities on top of sanctioned platforms like ChatGPT, Copilot, and Gemini.
That move, from generic efficiency to defensible differentiation, raises the stakes on governance, data, and talent.
The toughest challenges now centre on people. Leadership is consolidating responsibility with CAIO roles, access is broadening under tighter guardrails, and AI is increasingly used to manage risk. Yet a training paradox persists: lack of training is a top barrier even as training investment softens.
Google Notebook LMs agents dig into augmentation vs skill atrophy, the scramble for advanced talent, and why many leaders expect to hire more interns for AI‑enabled entry roles.
Our closing challenge: if automation eats the routine, which human skills will you invest in to drive the next wave of return?
Full study by The Wharton School and GBK Collective here: https://knowledge.wharton.upenn.edu/special-report/2025-ai-adoption-report/
Enjoy the conversation?
Follow the show, share it, and leave a review to help more people find it.
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 Tools To Teammates: How Agentic AI Rewrites Work And Society
The Digital Transformation Playbook
The promise of autonomy just got practical. We explore how agentic AI moves beyond passive automation to become a goal-driven collaborator that plans, adapts, and coordinates at human and machine scale. From UPS’s ORION saving millions of miles to smart factories reducing downtime and energy use, we lay out the concrete ways agents optimise complex systems while staying aligned with human oversight.
TL;DR;
- Defining agentic AI through goals, autonomy, learning, reasoning, and collaboration
- Manufacturing shifts to predictive, dynamic operations
- Precision agriculture and resource-efficient inputs
- Smart grids balancing renewables, storage, and demand
- Labour market change and reskilling needs
- Ethics, transparency, and the EU AI Act
- A phased, governed roadmap for adoption
Across sectors, the patterns repeat: precision agriculture uses sensors and imaging to fine-tune inputs in real time; smart grids balance renewables, storage, and demand to keep power stable; research teams accelerate discovery by screening vast chemical spaces and designing better experiments; creatives partner with agents that riff on styles, structure ideas, and expand the canvas without replacing human taste. We unpack the five pillars that make this possible—goal orientation, autonomous decisions, learning and adaptation, complex reasoning, and collaboration—so you can recognise genuine capability and spot hype.
We also confront the tough trade-offs. Jobs will change, which makes reskilling and mobility essential. Governance must keep pace, with risk-based rules, transparency, and strong safety cases for high-impact deployments. Privacy and data sovereignty demand encryption, auditability, and clear accountability. And for those worried about cost or complexity, we show how cloud platforms, pre-trained models, and no-code tools lower barriers so even lean teams can run meaningful pilots and prove ROI.
If you want a pragmatic path into autonomy—one that pairs ambition with control—this conversation maps the milestones: pick outcome-centric use cases, start small, build human-in-the-loop guardrails, measure impact, and scale responsibly. Subscribe, share with a colleague who’s planning an AI pilot, and leave a review with the one question you want us to tackle next.
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
From Hype To Habit: How Leaders Turn AI Into 30% Productivity Gains
The Digital Transformation Playbook
The ground just shifted under every boardroom and team room: AI isn’t a side experiment anymore, it’s a core business tool changing how work gets done. We trace the acceleration in adoption and show why hands-on leadership—not memos—separates winners from watchers. From marketing and legal to operations and customer support, we walk through concrete examples of where AI already delivers results: real‑time personalisation, faster contract review, earlier demand forecasts, and sharper executive briefings. Along the way, we unpack how small, repeated wins create measurable ROI, lift revenue and profit, and compress decision cycles without sacrificing judgment.
TL;DR:
- AI moves from IT to every function
- Executives use AI for analysis and communication
- Productivity gains reshape project cycles and models
- Proof points across quality, consulting, and support
- Risks of delay and scattered pilots
- Governance, safety, and human-in-the-loop design
- Upskilling leaders to set strategy and build trust
We also address the hard truth about timing. Most tech leaders see a near-term deadline for adoption, and the opportunity cost of waiting is rising: lost market share, slower innovation, and a tougher fight for top talent. But speed without understanding leads to scattered pilots and weak governance. We share a practical path to disciplined speed—pick high-signal workflows, define safety guardrails, and measure outcomes that matter. Expect a clear case for human-in-the-loop review, data security, and transparent audit trails that reduce risk while raising confidence.
Finally, we confront the leadership gap. Many senior teams haven’t received formal AI training and lack confidence in safe use. That’s solvable. When leaders learn the tools, they can spot real use cases, set strategy, and model the behaviour that drives adoption across the organisation. The message is simple: those who lead from the front will turn AI into lasting advantage; those who wait will be managed by it. If this helps you lead the change, follow the show, share it with a colleague, and leave a review so more leaders can find it.
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
Practical AI Governance For HR
The Digital Transformation Playbook
AI is already inside your organisation, whether leadership has a plan or not. We unpack how HR and L&D can turn quiet workarounds into safe, transparent practice by pairing thoughtful governance with practical training.
From the dangers of Shadow AI to the nuance of enterprise copilots, we share a clear, humane path that protects people while unlocking real productivity gains.
TLDR / At a Glance:
• duty of care for AI adoption in HR and L&D
• why blanket bans fail and fuel Shadow AI
• understanding data flows, privacy, and GDPR
• identifying and mitigating bias in models and outputs
• transparency, disclosure, and human oversight for decisions
• culture change to reward openness not secrecy
• choosing enterprise tools and setting guardrails
We dig into bias with concrete examples and current legal cases, showing how historical data and cultural blind spots distort outcomes in recruitment and learning.
Rather than treating AI as a black box, we explain how to map data flows, set boundaries for sensitive information, and publish plain-language guidance that staff can actually follow.
You’ll hear why disclosure must be rewarded, how managers can credit judgment as well as output, and what it takes to create a culture where people feel safe to say “AI helped here.”
Hallucinations and overconfidence get their own spotlight. We outline simple verification habits - ask for sources, cross-check claims, and consult a human for consequential decisions - so teams stop mistaking fluent text for facts.
We also clarify the difference between public tools and enterprise deployments, highlight GDPR and subject access exposure, and show how small process changes prevent large penalties.
The result is a compact playbook: acceptable use policy, clear guardrails, training on prompting and bias, periodic audits, and a commitment to job enrichment rather than workload creep.
If you’re ready to move beyond fear and bans, this conversation offers the structure and language you can use tomorrow. Subscribe, share with a colleague in HR or L&D, and leave a review with your biggest AI governance question-we’ll tackle it in a future show.
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
Leading AI Starts With Behaviour, Not Code
The Digital Transformation Playbook
The promise of AI isn’t stalling because the models are weak; it’s stalling because our leadership habits are.
We open the hood on why executives talk about stewardship and enterprise health while managers feel like they’re juggling a second job just to keep up, then add AI on top.
The tension isn’t about tools. It’s about incentives, silos, and the courage to share ownership for outcomes that cut across the org chart.
TLDR:
- AI framed as a leadership and behavioural challenge
- Disconnect between C‑suite aspirations and operational reality
- Managers feeling AI as a “second job” without role redesign
- Need for shared executive ownership across functional boundaries
- Team coaching to move from polite alignment to joint accountability
- Incentives driving individual attainment over enterprise outcomes
- Governance and KPIs that reward cross‑functional results
- AI as an accelerant of existing misalignment if behaviours do not change
Across a candid, practical conversation, we explore how automation refuses to respect functional boundaries and what that means for the C‑suite. If rewards are tied to individual attainment and quarterly optics, leaders will say “collaborate” while behaving in ways that block end‑to‑end value.
We dig into team coaching as a lever for change shifting executive teams from polite alignment to genuine joint accountability, setting shared KPIs, and making decisions that trade local optimisation for enterprise results.
We also get real about the strain on middle managers who hear the AI mandate but lack redesigned roles, budgets, and guardrails to make it work.
You’ll hear clear steps for turning intent into impact: name the vision–reality gap, sponsor value streams that span functions, co-own outcomes at the top, and create short learning cycles where cross-functional teams can test, measure, and adapt.
We talk governance that empowers rather than slows, incentives that reward cross-boundary wins, and behaviours that build psychological safety so constraints surface early. If you want AI to be a force multiplier instead of a stress multiplier, start by rewiring how leaders lead together.
If this conversation resonates, follow the show, share it with a colleague who’s navigating AI at scale, and leave a review to help more leaders find it.
Are you struggling with AI or do you need fractional executive help implementing AI in your business?
If the answer is yes, 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
Fractional Power For Growing SMEs
The Digital Transformation Playbook
What if you could borrow a battle-tested executive exactly when you need them and only for as long as it takes to move the needle? We pull back the curtain on fractional leadership for SMEs, focusing on the people side of change where complexity lives and value compounds.
TLDR / AT A Glance:
• What fractional leadership is and why it matters for SMEs
• Complexity of people versus utility of technology
• Why “digital transformation” distracts from systems and culture
• How empowerment beats command and control
• Common SME patterns and how to fix them
• Product thinking for HR and quick, measurable wins
• What makes a great fractional leader
• How to choose and work with a fractional chief
Across a fast-moving conversation, we define what a fractional C‑suite leader actually does and why it’s not a cheaper helpdesk. Think senior judgment on tap: diagnosing root causes, running smart experiments, and owning outcomes.
We challenge the myth of “digital transformation” by reframing technology as a utility and putting human systems front and centre. AI and automation clear the noise; empowered teams create the signal. That means unlearning command and control, pushing decisions closer to the market, and building lightweight structures that turn information into action.
You’ll hear concrete patterns from the SME trenches: overcontrol driven by tight budgets, underused tech, and fads that burn cash without impact.
We share how product thinking applies to HR - test, measure, iterate and what early proof points look like when you are fixing retention, engagement, and capability. For practitioners eyeing fractional work, we cover the mindset shift from corporate to owner-led businesses, the breadth required across HR disciplines, and why emotional intelligence is as critical as technical depth.
For founders choosing a fractional chief, we offer a simple playbook: verify track record, align on outcomes, insist on execution, and value a partner who can challenge without breaking trust.
If you want senior expertise without the full-time price tag and you’re ready to trade decks for delivery this conversation maps the path.
Subscribe, share with a fellow leader who needs this lens, and leave a review with the one capability you’d rent first.
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
Why Executive Fear, Not Technology, Holds Back AI Success
The Digital Transformation Playbook
Fear rarely announces itself; it hides behind control, certainty, and the urge to delay.
We sit down with expert CPO Brian Parks to unpack why artificial intelligence stalls in boardrooms not because of model limits, but because of leadership habits shaped by pressure, incentives, and ambiguity.
Rather than chasing the newest tool, we explore how fear of failure, public scrutiny, and quarterly cycles push executives to avoid the very experiments that build competence and how that choice quietly taxes performance across the organisation.
TLDR:
- Reframing AI as a leadership and behaviour issue
- Executive fear of failure and loss of control
- Pressure from short time frames and forecasts
- Incentives that favour speed over learning
- The role of AI literacy for leaders and teams
- Creating safe, small, reversible experiments
- Retaining AI fluent talent through clarity and trust
Across this fast-paced conversation, we reframe AI as a human and behavioural challenge. Brian breaks down the real dynamics at the top: shrinking time frames, harder forecasts, and compensation structures that reward visible delivery over exploration.
We dig into practical ways leaders can replace anxiety with clarity, from building shared AI literacy and setting simple guardrails to running small, reversible pilots that deliver measurable wins.
You’ll hear how to structure incentives that value time saved and quality improved, pair domain experts with AI specialists, and normalise transparent learning with blameless reviews and demo rituals.
The talent stakes are high. Your best people are already AI fluent, and if your culture blocks them, they’ll move to teams that welcome their skills. We outline concrete steps to keep them: sponsored learning pathways, clear approved tools, and public recognition for applied outcomes.
By treating AI initiatives like a portfolio of options rather than a single bet, leaders can manage risk, compound insight, and make it safe to change course as evidence emerges.
If you’re ready to turn uncertainty into momentum and lead with confidence, tune in, take notes, and start the next small experiment today.
Subscribe, share with a colleague who needs this, and leave a review to help more leaders find practical, human-centred AI guidance.
Listen in as CPO Brian Parkes explains why AI is often resisted by executives but they should learn to embrace it to reap AI's many rewards.
Are you struggling with AI or do you need fractional executive help implementing AI in your business?
If the answer is yes, 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
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.
☎️ 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: 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
Open Source AI’s Quiet Revolution
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Why Digital Workers Can Finally Handle The Boring Stuff So You Can Do The Valuable Work
12:51
If AI Eats The Routine, What Human Skills Survive?
16:42
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From Tools To Teammates: How Agentic AI Rewrites Work And Society
20:01
From Hype To Habit: How Leaders Turn AI Into 30% Productivity Gains
4:13
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Practical AI Governance For HR
16:59
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Leading AI Starts With Behaviour, Not Code
2:59
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Fractional Power For Growing SMEs
17:34
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Why Executive Fear, Not Technology, Holds Back AI Success
2:22
How The Next Workforce Will Redefine Business With Everyday AI
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Agentic AI, Explained Simply
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Lead AI by Leading People
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From hype to habits: making AI safe, useful, and fair at work
13:31
Inside Uber’s Machine-Managed Workforce And What It Means For Work
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The $5 Trillion Shift To AI-Driven Buying
16:23
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What happens when HR stops guessing and starts predicting with AI and analytics
17:30
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AI, Explained Simply
4:10
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AI for HR and L&D: Start Small, Think Big
15:49
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Exciting New HI for HR and L&D Professionals Course
1:49
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Coding the Future: How to Build AI Agents That Actually Work
18:47
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AI and Humans: The Future of Hybrid Work
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Navigating the Future: Inside the Explosive Growth of Agentic AI
43:52
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The Future is Now: How HR and L&D Professionals Can Master AI
23:15
The $3 Trillion Question: Can AI Match Human Experts?
14:36
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AI Agents: Tomorrow's Business Revolution
30:17