Imagine accessing board-level talent only when you truly need it no bloated overhead, no inventing tasks to fill a calendar.

That’s the promise of fractional leadership, and it’s reshaping how ambitious companies scale. We sit down with Kevin Steele, founder of Clarendon Financial and Strategy, to unpack how a fractional CFO links finance to strategy and builds the financial engine that powers growth.

TLDR / At A Glance:

• What a fractional executive is and is not
• Why growing firms choose fractional over full-time
• Cost, flexibility, and scaling engagement up or down
• CFO focus on linking finance to strategy
• Clean data as the non-negotiable foundation
• The 30-60-90 plan and engagement stages
• When and how to hand over to a full-time hire
• How to vet credibility, sector fit, and references
• Managing fractionals for outcomes, not hours
• The future of fractional work and the credibility gap

Kevin lays out a clear operating model: start with discovery, fix the data, then install budgets, forecasts, and non-financial KPIs that tie your commercial story to cash. He explains why clean data is non-negotiable garbage in, garbage out and how a focused 30-60-90 plan drives measurable results fast.

We dig into the moments when fractional support creates the most leverage, from due diligence and acquisitions to board reporting and scenario planning, and how engagements flex up or down based on need.

The conversation also gets practical about selection and trust. Not all “fractionals” are equal. We outline a simple due diligence checklist: proven C-suite experience, sector specialism aligned to your model, and live client references.

Kevin shares why he specialises in B2B services and why, at scale, a fractional CFO should help you graduate to a part-time or full-time hire with clean systems that a new leader can run with.

Along the way, we talk about the credibility gap in a world where anyone can claim expertise, and why the real value often looks like “another adult at the table” a steady, independent voice that challenges assumptions and keeps strategy honest.

If you’re weighing full-time versus fractional, or wondering how to get real ROI from rented expertise, this conversation gives you the playbook to decide with confidence.

Subscribe for more deep dives on leadership, finance, AI, and the operating systems that help founders grow. If this helped clarify your next move, share it with a colleague and leave a review what role would you rent first?

Need a fractional executive in your business? Then let's chat - https://calendly.com/kierangilmurray/next-steps-fractional

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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

Machines that wait for our prompts are giving way to systems that plan, decide, and act. We unpack the three waves of AI predictive, generative, and agentic and explore how the newest wave is redefining work by turning software into autonomous collaborators. From forecasting to content creation to coordinated action across tools and networks, we trace what changes, what stays, and what leaders must do next.

TLDR / At a Glance:

• defining predictive, generative, and agentic AI
• why agency matters for decisions and actions
• the tech stack enabling autonomous agents
• where agents fit in real workflows
• trust, ethics, and safety guardrails
• workforce shifts, reskilling, and new roles
• staged autonomy from observe to execute
• the move from apps to agents
• leadership playbook for the agentic age

I walk through the tech convergence making agency real: large language models for reasoning and dialogue, cloud scale for memory and orchestration, and machine learning for perception and optimisation. We look at how agents break down complex goals, call APIs, coordinate with other agents, and adapt to feedback, delivering speed and quality that manual handoffs cannot match. Along the way, we surface hard truths about trust, safety, and ethics why guardrails, auditability, and clear accountability are non-negotiable when machines act on your behalf.

The conversation turns practical with a leadership playbook: map processes by risk and value, start with narrow pilots, use staged autonomy from suggest to execute, and measure outcomes you care about latency, quality, cost, and satisfaction.

We dig into workforce transformation as the value of memorising and repeating knowledge declines, and highlight emerging roles like agent wranglers, policy designers, evaluators, and workflow architects.

Expect frank talk on displacement, reskilling, and how to build an agent registry, permissions, and incident response so your digital workforce behaves like a reliable product, not a risky experiment.

If you’re ready to move from “there’s an app for that” to “there’s an agent for that,” this deep dive will help you design, supervise, and scale agents responsibly.

Subscribe for more research-backed guides, share with a colleague who’s rethinking their operating model, and leave a review to tell us how you’re preparing your team for the agentic age.

Want to buy the full book or audio copy? This excellent book is now available globally on Amazon and Audible.

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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 you’re asked to keep an iconic music video exactly as fans remember it except the singer must perform a different song, in perfect sync, for four minutes straight?

We brought Joyrider Films founder and executive producer Spencer Friend into the studio to unpack the creative calls, the technical stack, and the leadership habits that make a moment like that possible.

TLDR / At a Glance

• why Joyrider built in-house production and post
• what defines fast, visual, cinematic storytelling
• how to choose between practical, CG, virtual, and AI
• where consumer AI breaks and pro pipelines start
• the Coldplay and Idols “Grace” lip sync workflow
• training, slap comps, and iterative refinement
• ethical guardrails and likeness consent in AI
• testing methods before committing to a pipeline
• why storytelling and continuity still lead hiring
• skills young directors need to thrive

Spencer walks us through Joyrider’s hybrid approach across commercials, entertainment, and music videos: when to shoot practically for authentic performance, when CG delivers the impossible, and where AI or virtual production creates real value rather than novelty.

The Coldplay x Idols “Grace” project becomes our living lab: a model trained on Chris Martin’s face, an iterative cycle of training and slap comps, and the fine-grain compositing choices that made an overcranked, front-facing close-up hold up under scrutiny.

We explore why consumer AI tools fall down on continuity and how a nodal workflow like ComfyUI supports professional control over look, lip sync, and consistency at scale.

We also get practical about responsible AI. Consent-driven likeness capture, clear data provenance, and ethical standards keep talent protected while improving results.

Spencer argues AI won’t erase jobs; it expands them, demanding directors who think in shots and systems, VFX artists fluent in light and latency, and AI artists who can code while protecting performance.

Story remains the north star: every tool decision ladders up to narrative clarity, emotional truth, and deliverable quality under deadline pressure.

If you care about how cutting-edge production actually ships—across branded content, music videos, and beyond this conversation maps the choices, pitfalls, and wins.

Subscribe for more deep dives, share with a producer or creative who needs a modern toolkit, and leave a review with one question you want us to tackle next.

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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

Growth stalls when complexity outruns capability. We brought on award-winning HR leader Barry Flack to show how fractional executives give SMEs enterprise-grade judgement without the full-time overhead, and why that mix of strategy and sleeves-rolled-up execution delivers results that stick. Barry explains what “fractional” really means, how it differs from part-time advice, and why outcomes matter more than hours.

Together we challenge the myth of digital transformation, reframing technology as a powerful utility that frees people to do the thinking, collaborating and market sensing that actually moves the needle.

TLDR / At A Glance:

• Definition and value of fractional leadership for SMEs
• Complexity vs cost: why outcomes beat hours
• Technology as utility, people as the engine
• •Ditching command and control for empowerment
• Common SME pitfalls and how to avoid them
• Moving fast with proofs of value and product thinking
• What makes a great fractional: breadth, EQ, track record
• How to select and work with a fractional leader

Across a candid, practical conversation, we map the shift from command and control to empowerment, with clear examples of how SMEs can invert the pyramid, place insight closer to customers, and use automation to remove toil rather than replace judgement.

Barry shares patterns he sees in smaller firms—over-control, underuse of tools, and “just good enough” compromises—and how fractional leaders help reset ambition while respecting budget reality.

We dig into product thinking for HR, fast proofs of value, and the emotional intelligence required to coach executive teams through uncomfortable change.

If you’re considering going fractional, you’ll hear what breadth of skills and mindset you need to thrive. If you’re hiring a fractional leader, you’ll learn the selection criteria that matter: track record across disciplines, evidence of shipped outcomes, and the ability to challenge respectfully while executing.

Want access to elite expertise at a sensible price point and cadence?

Then let's chat - https://calendly.com/kierangilmurray/executive-leadership-and-development-meeting

Subscribe, share this with a founder or operator who needs it, and leave a review with the one capability you’d fractionalise first.

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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 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.

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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

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

Support the show

𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.

☎️ https://calendly.com/kierangilmurray/results-not-excuses
✉️ kieran@gilmurray.co.uk
🌍 www.KieranGilmurray.com
📘 Kieran Gilmurray | LinkedIn
🦉 X / Twitter: https://twitter.com/KieranGilmurray
📽 YouTube: https://www.youtube.com/@KieranGilmurray

📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK

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/

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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 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?

Support the show

𝗖𝗼𝗻𝘁𝗮𝗰𝘁 my team and I to get business results, not excuses.

☎️ https://calendly.com/kierangilmurray/results-not-excuses
✉️ kieran@gilmurray.co.uk
🌍 www.KieranGilmurray.com
📘 Kieran Gilmurray | LinkedIn
🦉 X / Twitter: https://twitter.com/KieranGilmurray
📽 YouTube: https://www.youtube.com/@KieranGilmurray

📕 Want to learn more about agentic AI then read my new book on Agentic AI and the Future of Work https://tinyurl.com/MyBooksOnAmazonUK