The Fork in the Road
In my last post, I mapped out the AI adoption continuum and argued that the gap between companies seeing massive gains and the ones seeing nothing comes down to people. The reason is that most companies skip right past the upstream questions: what does "AI transformation" mean?
You can answer this in two ways, but these lead to remarkably different places.
Version One: Productivity. Do the same things faster, leaner, and cheaper. This L0–L2 on my AI Continuum is tools-based, procurement-driven, and capped at incremental improvement. It is a cost optimization play disguised as transformation.
Version Two: People. Not "How do we speed up what we already do?" but ask: "what would we build if we started today?" When you take that question seriously, you land in a place that makes executives uncomfortable: everyone is a builder. By “builder,” I don’t mean everyone becomes an engineer shipping production code. I mean more people can directly shape outcomes, workflows, decisions, products, and systems instead of waiting in line for someone else to do it.
Most companies pick version one because they never even realized there was a choice.
The Default Path: Procurement Theater
If you lack a clear vision of where AI transformation ends up, you buy the tools, give them to your best engineers, and let them run. You host brown bags and pull together demos. You shield everyone else from questions about roles changing or processes dying. You alleviate their fears by keeping the change contained, manageable, technical, and compliant.
The technical teams that do have access are busy building. They produce an impressive laundry list of initiatives without an overarching theme or vision. Ask anyone to explain in business terms what they accomplished, and the room gets quiet. The work is technically sophisticated and directionally unclear.
That's Procurement Theater, when you end up engineering the appearance of transformation without creating the conditions for it. It is the natural default when nobody defines the destination.
You gave people a Ferrari and no map, so they pull donuts in the parking lot.
Procurement Theater shows up in three paradoxes. Each is a version of the same disease: saying yes at the strategic level and no at the operating level.
Paradox 1: "Be AI-native, but watch the tokens."
Companies set aggressive AI transformation goals and manage the tools like expensing office supplies. They enforce token budgets and per-seat cost scrutiny. Usage dashboards flag "heavy users" instead of celebrating them. The person using AI the most, who is transforming their workflow, gets a tap on the shoulder about cost.
Meanwhile, the person who logged in once and never came back gets their access revoked. The company claws back the seat and calls it fiscal responsibility instead of helping them learn.
You punish power users for costing too much and abandon low users for adopting slowly. Who are you transforming?
Paradox 2: "Experiment freely, but don't touch anything."
The tools get provisioned, but the environment stays static. Every system (e.g. CI/CD, code review, deployment, access control) is designed for professional engineers shipping production software. A PM who writes API specs is prohibited from writing code. A designer cannot prototype beyond a static screen. Building is for engineers, and everyone else writes documents about what they want built.
When leadership says "experiment with AI," the only people who can experiment already had access. Everyone else gets chat. Chat summarizes a doc or drafts an email, but it falls short of transformation. The highest-value use cases that rethink workflows require access nobody is willing to approve.
It is a self-fulfilling prophecy. You restrict the tool to low-value tasks and use the low-value results as evidence that the tool has low value.
Paradox 3: "Transform everything, but change nothing."
This is the hardest version. The company wants AI-native operations, but the org chart, processes, and incentives stay the same. AI gets layered on top of the existing system. It is merely an addition.
Meanwhile, the big procurement decisions keep rolling in non-engineering teams like HR, legal, and finance, where multi-quarter SaaS evaluations lead to multi-year contracts. Nobody asks: does this tool need to exist in two years? By ignoring the question, you lock in pre-AI architecture for a post-AI world and enshrine obsolescence.
This mirrors Feedback Theater , where the performance replaces the substance. Feedback Theater is review culture without honesty. Procurement Theater is AI adoption without transformation.
The Builder Path
Choosing the people path is hard. It requires swallowing a pill most organizations reject: none of the things you built thus-far will survive. The processes, the financial model, the PERF process, and the tooling assumptions will all get rethought.
If you start from the belief that everyone is a builder and organize around making that true, the to-do list looks like a company redesign.
Education changes. Not "here's a 30-minute webinar on prompt engineering." Real investment in developing builder capacity across the entire org, teaching prototyping, agent workflows, and system possibilities.
Tooling changes. The next wave isn't 500 engineers shipping 50 services. It's 5,000 people across every function shipping apps, automations, and internal tools. You need repos, sandboxes, lightweight deployment paths, and permission structures designed for a fundamentally different profile of creator.
Access changes. People need to connect AI to the systems where the work happens, like the codebase, the data warehouse, and internal APIs. They need tools, access, and the ability to build and ship with guardrails that enable rather than block non-engineers.
Measurement changes. Stop counting active seats, token usage, and lines of code. Start counting eliminated processes, faster decisions, and new shipments. Treating tokens solely as costs ignores their value as an investment.
Kill things. The clearest sign of AI transformation is what you stopped doing. What procurement did you cancel? What manual process did you eliminate? What meeting disappeared? If the answer is "nothing," you accessorized.
This is what AI-First Thinking looks like at the org level. If you ask "what would we build if we started today?" and the answer is "what we have now, with an AI layer on top," you need to ask harder.
Where Are You?
Ask yourself: are you focused on tools, or are you building builders?
If your AI strategy lives solely in engineering & IT, you see it as a tools issue.
If you see your people as having limitless potential, enable them and get out of the way. You build builders. If that scares you, steer that Ferrari to the next frontier.
Building builders is the transformation.
