What if the “AI agents” your organization is investing in aren’t actually agents at all? I woke up one morning, checked my phone, and saw yet another company announcing they are now an “AI agent company.” I have seen it over and over again. Different vendors. Same claim. No clear definition. I walk through in this episode what actually separates a workflow, a copilot, and a true agent, and why that distinction matters more than ever. I also share real examples of where organizations are getting this wrong, and what happens when you layer AI on top of broken processes. This is not about chasing the next buzzword. It is about knowing what you are actually deploying, what you can trust it with, and whether your foundation is ready for it. Because putting AI on top of broken processes does not create transformation. It hides the problem until it shows up at scale. If we cannot define what we are deploying, we cannot govern it, trust it, or scale it.

Highlights:

Why “AI agent” has become one of the most misused terms in tech right now
The critical difference between workflows, copilots, and true agents
How to tell if a system is actually reasoning or just following a pre-built path
The hidden risk of “agent sprawl” and why it mirrors the rise of shadow IT
Why most AI demos look smarter than the systems actually are
The real reason agents fail when deployed on outdated processes and bad data
What adaptive reasoning and memory actually mean and why they matter
The 5 questions every leader should ask before trusting any “AI agent”
Why clean data and validated processes matter more than the technology itself

Host Bio:

Jason Averbook has spent thirty years watching the gap between where organizations say they are with technology and where work is actually happening. He has a name for it. He has a framework for closing it. And he built Now to Next to do exactly that.

Now to Next is the AI studio Jason co-founded with Jess Von Bank in 2026 — built on practitioner intelligence, original research, and the conviction that human transformation precedes digital transformation. Always has. Always will.

Before Now to Next, Jason co-founded Leapgen, acquired by Mercer in 2023, where he led global HR transformation strategy and the firm's generative AI practice. Earlier he served as CEO of The Marcus Buckingham Company, co-founded Knowledge Infusion through its acquisition by Appirio, and held senior roles at PeopleSoft and Ceridian. He has advised hundreds of Fortune 1000 companies, authored two books on the future of HR and workforce technology, delivered more than 1000 keynote presentations globally, and teaches as an adjunct professor at universities worldwide.

He is consistently recognized as one of the top three thought leaders globally on the future of work.

Follow Jason Averbook:

Substack: https://substack.com/@jasonaverbook X: https://x.com/jasonaverbook LinkedIn: https://www.linkedin.com/in/jasonaverbook Instagram: https://www.instagram.com/jasonaverbook YouTube: https://www.youtube.com/@nowtonextwithjasonaverbook Facebook: https://facebook.com/jasonaverbook

(0:00) Introduction and defining AI agents (2:49) Categorizing AI agents and system paths (6:22) Use cases and historical evolution from workflows to agents (11:28) Architectural differences: Workflow vs. agent (15:18) Key features of genuine agents: Adaptive reasoning and memory (19:34) Real-world application: Enhancing HR efficiency (21:48) Questions to ask vendors about AI agents

EP23: The Agent Illusion: Why Most “AI Agents” Aren’t What You Think