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Why Does AI Momentum Stall in Large Organizations? with Kyle Lagunas & Allyn Bailey

Modern CTO18 June 2026Watch on YouTube

Part of series

Ep. 12 · Enterprise AI Adoptie

Verkent waarom en hoe bedrijven AI adopteren, met focus op vertrouwen, tempo en de impact op werknemers.

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Description

Understanding these key points is what actually moves the needle on AI gains. Today, we're talking to Kyle Lagunas, analyst and founder at Kyle & Co, and Allyn Bailey, senior director of communications at SmartRecruiters, about why AI momentum in HR is stalling and what's actually moving the needle. We discuss why the organizations leading on AI aren't doing anything flashy, how the most boring red-tape work turns out to be the biggest unlock, why HR's instinct for risk avoidance is exactly the wrong posture for this moment, and what a surprising finding about EU companies under heavy regulation reveals about the relationship between guardrails and speed. All of this right here, right now, on the Modern CTO Podcast! To learn more about SmartRecruiters, check out their website here: https://www.smartrecruiters.com/ To read Kyle and Co's full AI Momentum Model, check it out here: https://www.smartrecruiters.com/resources/landing/from-exploration-to-impact-the-new-ai-momentum-model-for-hr/ 00:00 – Introduction: Kyle Lagunas and Allyn Bailey 00:21 – Why a Maturity Model Didn't Fit AI in HR 01:35 – How SmartRecruiters and Kyle & Co Built the Research 02:54 – The Ethics Gap in HR and AI 04:25 – Why "Boring" Infrastructure Beats Big Ideas 06:18 – Using the AI Momentum Framework in Your Org 07:03 – The 12-Question Assessment Tool Explained 09:36 – Building Common Language Across the C-Suite 11:20 – What SmartRecruiters Wanted to Understand 13:01 – The Three Dimensions: Capability, Posture, Investment 14:06 – Why Risk Avoidance Is HR's Achilles Heel 15:20 – AI Literacy as a Make-or-Break Factor 17:13 – HR's Tech Debt Problem Since COVID 20:01 – What the Top 12% of AI Adopters Actually Do 23:43 – The Surprising EU Finding: More Rules, More Progress 25:11 – Policy Always Lags Tragedy: AI Regulation Outlook 28:00 – HR's Measurement Problem: Quality vs. Speed 29:17 – HR Operations vs. the Human Side of HR 31:54 – Automation Free-for-All and the Innovation Identity Crisis 35:45 – Are HR Teams Using AI to Think, Not Just Automate? 36:55 – From Chatbots to Decision Support: The Evolution 40:17 – Building Trust With AI (The Tesla Analogy) 41:25 – Why Momentum Implies Competence 43:18 – Job Automation, Social Disruption, and Human Nature 48:21 – Value Exchange as the Future of Work 50:03 – SAP's Autonomous Enterprise Vision and SmartRecruiters 52:39 – Closing Thoughts and Sign-Off

What you'll learn

  • Boring infrastructure work (red-tape) is often the biggest unlock for AI success, not flashy innovation projects.
  • Top-performing AI adopters (top 12%) have strong AI literacy and overcome HR's traditional risk-avoidant posture.
  • Regulation and guardrails can actually accelerate speed, as demonstrated by EU companies operating under heavy compliance requirements.
  • AI momentum requires three dimensions in balance: capability, posture, and investment working together.
  • HR teams should use AI for decision-making and thinking, not just task automation.

Frequently asked questions

Why does AI momentum stall in HR organizations according to the research?
AI momentum stalls due to a combination of factors: lack of AI literacy, HR's risk-averse nature, insufficient infrastructure investment, and misalignment between capabilities and ambitions. Organizations focus on flashy projects while neglecting the boring, essential technical foundations.
What are the three dimensions of the AI Momentum Model?
The model consists of capability (technical ability), posture (organizational attitude and readiness), and investment (financial and human resources). These three must be balanced for real AI momentum in organizations.
How do regulation and speed relate according to the research?
A surprising finding is that EU companies under heavy regulation actually make faster AI progress. Clear guardrails and regulatory frameworks help organizations stay focused and avoid unnecessary experimentation, paradoxically leading to more momentum.
What should HR teams do differently with AI than they currently do?
HR teams primarily use AI for task automation, while top performers see it as a tool for better decision-making and thinking. The shift is from 'how do we automate this' to 'how does AI help us make better choices'.

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