Mid-sized companies can become AI-native, but most can’t rent their way there. By one market tracker’s count, few of the firms that sell AI deployment help are built for them. The practical path is to grow the capability inside: one person who owns AI deployment in each business, working on the company’s own workflows. Key […]
How to Recalibrate a Role Without Breaking the Workflow
To redesign a role around AI, don’t start with the tool. Map the role’s tasks. Decide for each one whether AI should automate it, help the person doing it, or stay out. Redesign the handoffs between people and AI, set the measures, and name the owner. Done in that order, the job changes without the […]
Who Leads an AI-Native Transformation?
An AI-native transformation needs three roles, not one. A Center of Excellence sets the guardrails and approves what gets built. A vendor, implementer or forward deployed engineer builds it. And an AI project manager inside the business carries each system into the workflow and owns it after launch. In many companies, the first two are […]
AI Isn’t Ending Work. It’s Creating Jobs That Don’t Have Names Yet
AI isn’t ending work, but it isn’t leaving work alone either. The best evidence so far shows two things at once: early-career workers in the most AI-exposed jobs are falling behind, and most of the work people do has always been new work. Which way AI cuts inside a company, we’d argue, is decided when […]
What Makes a Company AI-Native? It Isn’t the Model
An AI-native company has redesigned its core workflows around AI and owns how that AI is deployed inside the business. It isn’t defined by the model it buys, since its competitors can buy the same one. It’s defined by whether someone on its own payroll is accountable for how AI enters each workflow, and for […]