The Three Things Firms Get Wrong About Transformation

What if the way your firm measures the success of AI is the exact thing that will guarantee it fails?

Summary

Rachel Riopel is an enterprise transformation executive who has spent the better part of two decades inside AEC firms watching technology initiatives stall out at the technology layer. She came up as an architect, got hooked on Revit when nobody quite knew what to do with it, and never fully went back to project work once she saw how wide the gap was between what technology could do and what firms were actually doing with it.

In TRXL 227, we talked about what enterprise transformation actually looks like when you strip away the hype. The conversation ranged from a compelling "horses or coal" metaphor Rachel found in The Atlantic about how automation reshapes different kinds of workers, to a practical framework she calls “The Three Cs,” to a pointed warning about what firms lose when they reduce AI's value to a single, seductive metric: speed.

What kept coming up, in different forms throughout the conversation, is a tension I've seen play out many times myself: the gap between doing a pilot and actually changing an organization. Rachel frames transformation as a design problem, not a technology problem, and that framing unlocks a different set of questions entirely. With somewhere between 70 and 90% of transformation initiatives still failing, the firms that understand this distinction are going to look very different from the ones that don't.

What's Inside

• Horses or Coal. The Atlantic article that opens this conversation poses a sharp question about how automation reshapes different workers and whether AEC professionals are positioned to be the resource that grows more valuable under pressure, or the one that gets replaced entirely.
• The Three Cs. Rachel's framework for diagnosing whether a firm is actually ready for transformation: cash, clarity, and capability; and why capability is the one most firms overlook until it's too late.
• The Productivity Trap. Firms are fixating on speed as the primary measure of AI's value, and Rachel argues that fixation is pointing in exactly the wrong direction. Find out what she says firms should be measuring instead.
• The Knowledge Transfer Problem. What happens to emerging professionals when AI shortcuts the middle of the learning process, and why the "greens and grays" gap may be one of the most underappreciated risks in the industry right now.
• Technology as Expense vs. Investment. Why treating transformation as a cost center rather than a design challenge is a fundamental misread, and what organizational structures actually enable transformation to take hold.