AI Transformation Lab

In this episode I turn that gut check into a decision you can defend. The key is a better question — not “should we build or buy?” but “how much orchestration does this work actually need?” That question sorts every AI decision into three tiers. Work that lives inside one app — buy the AI already there. Work that crosses standard systems — bridge them with an orchestration platform. Work that runs...

Most teams look at a slow process and ask one question — can AI do this faster? It’s the wrong first question. The better one is harder: should this work exist at all? In this episode I borrow a seventy-year-old lens from the Toyota Production System — the wastes of Lean — and point it at knowledge work, where waste hides far better than it ever did on a factory floor.

In this episode, Chris Bradley makes the case that Continuous Improvement is the non-negotiable core of agentic AI. Recorded from Veritiv's Customer Service center in Jacksonville — the day before a three-day Kaizen — he lays out a simple model for bringing AI to any process: three levels, Automate, Improve, and AI-Native Rebuild. Level one paves the cow path. Level two strips the waste with Lean...

This episode is about the fix — building a portable layer of identity, memory, and skills that travels with you across every environment. I call it your Agentic DNA. A small set of files you own, that capture the version of you AI needs to know about, that deploy into any new harness in minutes instead of months.

In this episode, I walk through the seven capabilities that define Codex now — full file access, persistent memory, plugins, skills, GPT Image 2.0, browser and computer use, and automations — and where each one actually changes the work.

The big three AI labs are all building superapps — but each is packaging them differently. Google blurs everything together inside Antigravity. OpenAI is consolidating into Codex. Anthropic took a third path: three distinct surfaces inside one Claude desktop app — Chat, Cowork, and Code.

In Episode 1, I mentioned a competitive analysis I ran in thirty minutes that would have taken two weeks. A global network analysis — fifty-plus competitor locations, fifteen manufacturing hubs, proximity calculations, coverage gaps, and a full action plan for leadership.

Most AI tools know the internet. NotebookLM knows your sources. That distinction sounds small. It isn't. When you're doing serious research — regulatory analysis, competitive intelligence, executive briefing prep — the difference between a tool that synthesizes the web and a tool that synthesizes your documents is the difference between fast and trustworthy.

In Episode 3, Chris Bradley introduces a three-habit framework built for continuous AI fluency: the AI Pulse, a monthly calibration that keeps your mental model of AI's capabilities current; the Workflow Lab, a weekly thirty-minute session dedicated to examining and redesigning one workflow at a time; and the Workflow Pause, an in-the-moment reflex that catches automation opportunities before you...

The gap between AI users who've adapted to 2026 capabilities and those still using 2024 techniques is creating a significant productivity divide and the difference isn't about being smarter, it's about understanding what changed. In this episode of the AI Transformation Lab Podcast, host Chris Bradley, Chief Marketing Officer at Veritiv and head of their AI Transformation Lab, reveals how agentic...

In this episode of the AI Transformation Lab Podcast, host Chris Bradley, Chief Marketing Officer at Veritiv and head of the AI Transformation Lab, explores the fundamental shift from generative AI to agentic AI and why this distinction will reshape how knowledge work gets done in 2025 and beyond.