The AI Risk Posture Playbook for Boards

The AI Risk Posture Playbook for Boards

Artificial intelligence is now a board level risk with implications across strategy, operations, and reputation. Organisations must move from informal awareness to structured oversight to manage AI responsibly. This episode explores how boards define and operationalise an explicit AI risk posture. TLDR / At a Glance • AI as enterprise level risk category  • Risk appetite, tolerance, capacity distinctions  • Board versus management responsibilities  • Red line AI use cases  • Escalation thresholds and governance flows  • 30, 60, 90 day implementation roadmap A clear AI risk posture enables controlled innovation while maintaining accountability, resilience, and regulatory readiness. Support the show [https://www.buymeacoffee.com/KGilmurray] 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 [https://www.linkedin.com/in/kierangilmurray/] 🦉 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 [https://tinyurl.com/MyBooksOnAmazonUK]

PegaWorld 2026: The Year Agentic AI Had To Prove Itself

Enterprise AI has entered a more demanding phase, where agentic systems must prove they can deliver predictable outcomes in real business operations. PegaWorld 2026 framed that shift around workflow discipline, cost control, governance, and enterprise readiness. This episode explores six lessons for leaders scaling AI beyond pilots. TLDR / At a Glance • Predictable AI and governed execution • Outcome based AI cost control • Closing the strategy to execution gap • Orchestrating agents through approved workflows • Legacy modernisation as AI readiness • Enterprise discipline in AI assisted development AI agents have had years to impress us. PegaWorld 2026 forces a tougher standard: prove you can run inside complex enterprises without cost surprises, compliance gaps, inconsistent decisions or another layer of fragmented tech. That shift matters if you own regulated operations, customer outcomes, technology risk, or a budget that has to hold up when usage scales from a pilot to millions of interactions.   We dig into six takeaways that keep agentic AI trustworthy. The big one is predictable AI: do the heavier reasoning upfront when redesigning workflows and operating models, then keep live execution tight by using lighter AI to understand intent, select an approved workflow, and follow it consistently. We also unpack why ambiguity is the real project risk, and how tools like Pega Blueprint aim to turn business intent into build-ready workflow designs that can be governed, reused and audited.   Cost becomes a board-level conversation when token-based pricing meets long context windows and multi-step processes. We argue for measuring AI economics by outcomes such as cost per completed case, not prompts, tokens or model calls, and explain how deterministic workflows can narrow agent scope to reduce spend and risk. From orchestration and Model Context Protocol through to legacy COBOL modernisation with AWS Transform, we connect the dots between workflow automation, AI governance, and true AI readiness.  If you care about enterprise AI that lasts, subscribe, share this with a colleague, and leave a review with the one workflow you would redesign first. #PegaPartner Support the show [https://www.buymeacoffee.com/KGilmurray] 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 [https://www.linkedin.com/in/kierangilmurray/] 🦉 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 [https://tinyurl.com/MyBooksOnAmazonUK]

Why AI Strategies Fail Before They Scale

AI strategies often lose momentum when organisations move from pilots into real operating environments. Early progress can look convincing until ownership, governance, capability, workflow design, and value measurement are tested at scale. This episode explores why AI scale depends on organisational absorption. TLDR / At a Glance • Pilot to scale gap  • Organisational absorption  • Workflow redesign  • Decision ownership  • Governance and monitoring  • Value measurement The key takeaway is that AI scales when leaders redesign the operating model around trusted, repeatable execution. Support the show [https://www.buymeacoffee.com/KGilmurray] 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 [https://www.linkedin.com/in/kierangilmurray/] 🦉 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 [https://tinyurl.com/MyBooksOnAmazonUK]

Why Your AI Focus Group Keeps Saying Three

You spend years building a product, polish the packaging, nail the pitch… then you hit the terrifying question: is anyone actually going to buy it? We dig into a 2025 research result from PyMC Labs and Colgate-Palmolive that aims straight at that fear with AI market research, synthetic consumers, and large language models that can simulate purchase intent at scale. TL;DR / At A Glance * the core problem with direct Likert ratings and why LLMs collapse to neutral threes * how semantic similarity rating converts free-text responses into numerical scores using embeddings and cosine similarity * why follow-up AI grading helps but still trails the embedding-based approach * what 57 real product surveys and 9,300 human responses reveal about accuracy and distribution matching * how persona prompting reproduces real demographic patterns across age and income constraints * why zero-shot LLM methods can beat supervised machine learning models trained on the same domain The shocker is that the first attempt fails badly. When you make models like GPT-4 or Gemini answer a classic Likert scale with a single number, they hedge and pile up on neutral “3” ratings. The fix is not “better AI”, it is better questioning.  Google Notebook LM Agents help us unpack semantic similarity rating: let the model respond in natural language, convert that text into embeddings, and map it to five anchor statements using cosine similarity. You get fast, automated scoring without stripping away the model’s reasoning. From there, we pressure-test the method against thousands of real survey responses across dozens of personal care product concepts, then look at whether AI personas actually reflect real constraints like age and income.  We also compare the approach with traditional machine learning models such as LightGBM, and dig into an underrated advantage: synthetic consumers can produce richer, more candid qualitative feedback than many human panels. If you care about product testing, consumer insights, or the future of focus groups, listen through and tell us where you’d trust this and where you wouldn’t.  Subscribe, share with a colleague, and leave a review with your take: would you let synthetic consumers influence a real launch? Paper: http://arxiv.org/abs/2510.08338 [https://t.co/W5BlqI49ci] Support the show [https://www.buymeacoffee.com/KGilmurray] 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 [https://www.linkedin.com/in/kierangilmurray/] 🦉 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 [https://tinyurl.com/MyBooksOnAmazonUK]

AI-First Strategy at Scale: Pega's Roadmap with David Vidoni

Token subsidies are fading, AI prices are rising, and suddenly the fun part of experimentation comes with a nasty surprise: runaway spend. We dig into what that shift means for CIOs and IT leaders who still need to ship results, protect budgets, and prove ROI.  If you have spent time counting tokens or worrying that one enthusiastic pilot will burn through a month’s AI budget, this conversation is for you. David Vidoni, CIO at Pega, shares why predictable cost matters as much as model capability and how “charging for outcomes” changes the way you govern AI.  We talk about the practical tension between creativity and cost control, and why leaders should pause and ask whether AI is genuinely the best tool for a given challenge.  The goal is not to slow innovation down, but to stop wasting energy on spend anxiety and refocus on measurable business value. We also get concrete on delivery: how Blueprint supports a design-first approach that clarifies what you are building before you build it, reduces costly mistakes, and speeds up time to first release.  You will hear real internal stats, plus what it takes to deliver secure, compliant, repeatable outcomes rather than variable answers.  Finally, we explore agentic AI wins in legal and contract work, including significant hours saved and major ticket deflection. Listen, then subscribe, share with a fellow CIO or product leader, and leave a review with your biggest AI cost or governance challenge. Support the show [https://www.buymeacoffee.com/KGilmurray] 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 [https://www.linkedin.com/in/kierangilmurray/] 🦉 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 [https://tinyurl.com/MyBooksOnAmazonUK]