PegaWorld 2026: The Year Agentic AI Had To Prove Itself episode artwork

EPISODE · Jun 20, 2026 · 22 MIN

PegaWorld 2026: The Year Agentic AI Had To Prove Itself

from The Digital Transformation Playbook · host Kieran Gilmurray

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 developmentAI 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.#PegaPartnerSupport the showIf you are leading your businesses strategic transformation and need greater clarity, stronger execution and measurable results, let’s connect.  🌎 Website: www.KieranGilmurray.com📅 Book a call: https://calendly.com/kierangilmurray/catch-up📘 Kieran Gilmurray | LinkedIn🌐 Substack: https://kierangilmurray.substack.com📕 Amazon https://tinyurl.com/MyBooksOnAmazonUK AI Transparency Notice:  This podcast uses a hybrid format. When an episode features one of Kieran Gilmurray’s written articles, the narration is generated using a synthetic clone of his voice via ElevenLabs AI (the underlying article text is entirely human-authored). Episode descriptions and summaries are assisted by AI and should be considered unedited by a human unless specified. 

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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 ...

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PegaWorld 2026: The Year Agentic AI Had To Prove Itself

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