A machinist I worked with ran a five-axis CNC mill. Twenty-two years on the floor. He could hear when a tool was about to fail. He knew which programs needed a warm-up cycle that wasn't in any manual. He had nudged feeds and speeds over thousands of hours until the machine performed better than its published tolerances.
You don't walk up to that person and tell them they're doing it wrong. You watch. You ask questions. You learn what they know that nobody wrote down.
That's how AI should work.
The shame cycle
Enterprise technology has a messaging problem. For 30 years, the pitch has been some version of: your tools are bad, your data is messy, your processes are broken, and we're here to fix you.
"Get off Excel." "If it's not in the ERP, it doesn't count." "Your data needs to be clean before AI can touch it."
Meanwhile, the people doing the actual work have been quietly building the tools they need.
30-40% of enterprise IT spending in large organizations is shadow IT.
That's a third of the budget going to tools people chose for themselves. Not rebellion. Not laziness. An organization solving problems faster than its official systems can.
Excel as signal
Excel, PowerPoint, and Word are ubiquitous because they're freeform. They don't force a process. They don't require a six-month implementation, a certified admin, or a data migration project. You open them, and they do what you need.
Critics call that a weakness. No structure, no audit trail, no governance. That's true, and it's also half the story. Freeform tools let people build exactly what the work requires, which is why approximately 500 million people pay for Excel and Bloomberg called it an "AI-resistant, multitrillion-dollar empire."
When the workaround shows up, the workaround is the signal. Three patterns we see again and again:
Finance reports. The ERP holds the transactional data; every report and every pivot gets built in Excel. People work backwards: export, paste, format, model, present. When something breaks, the standard pushback is "use the ERP the way it's meant to be used." Better question: what does the finance team need to do that the ERP refuses to let them do?
Scheduling. The ERP has an MRP. The MRP runs. And then the actual production schedule gets exported to Excel for finalization, because the fine-tuning, the constraint juggling, the "this week we have to flex around the new hire" judgment, none of it fits inside the MRP's model. The Excel layer is where the schedule actually gets made.
The Excel jungle. Linked workbooks across a shared drive. VBA macros nobody touches in case they break. A spreadsheet that pulls from three others, which pull from two more, which pull from a flat file the night-shift supervisor updates manually. From the outside it looks like a hornet's nest. From the inside it's a working production system holding together tribal knowledge and process nuance that no ERP module ever asked about.
Three examples. One pattern. The workaround is the work; the official system couldn't carry it.
The numbers on "rip and replace"
The enterprise software industry's preferred strategy (rip out the old thing, install the new thing, mandate adoption) has a brutal track record:
- 70% of large-scale transformations fail (McKinsey, 2022)
- 55-75% of ERP implementations fail (Godlan/KPC, 2025)
- 67% of enterprise software features go unused (Gartner, 2024)
The pattern repeats with every wave of technology: impose a system from the top down, demand people change how they work, watch adoption stall, blame the users.
What if the users aren't the problem?
A different posture
There's a concept in change management research that's so obvious it shouldn't need to be stated: projects with excellent change management are up to seven times more likely to succeed (Prosci). The way you introduce something matters more than what you introduce.
We think about it as three stages, not as a framework we put on a slide, but as a posture:
Connect. Plug into the workflow that already exists. The Excel model, the emailed report, the homegrown tracker. Don't ask anyone to stop what they're doing. Start where the work happens.
Extend. Add what the current tool can't do on its own. Traceability. Collaboration. AI that reflects the user's expertise rather than replacing it. The existing workflow gets better without anyone learning a new system.
Replace. Eventually, the user stops needing the workaround. Not because you killed it, but because you understood the work well enough that the next spreadsheet didn't have to get built. Replacement comes last, and it's earned.
Workflows as evidence
Every workaround is an argument about how the work should run. The Excel pivot a finance team rebuilds every week says something about the ERP's reporting module. The scheduler's annotated PDF says something about the MRP. The night-shift handoff document, the unofficial vendor whitelist, the "ask Carla before you touch this" rule: these are the operating system the people actually use, layered on top of the one the company bought.
That layer is collective. It crosses people, handoffs, tools, and shifts. No single veteran owns it. When you read the workarounds, you're reading the workflow the organization actually runs on, even though no one wrote it down that way.
A 2023 NBER study by Brynjolfsson, Li, and Raymond looked at customer-service teams that gave AI access to their top performers' interactions. Novice productivity jumped 34%. Workers with two months of experience matched the output of those with six. The AI mirrored how the team's best work was already happening and made it available to everyone.
That's the model we believe in. Read the workflow that already exists. Reflect its patterns. Make them available to the next shift, the next hire, the next role rotation. The intelligence is already in the building; the system just hasn't been the one carrying it.
The reframe
The phrase "you are the product" usually means the platform harvested your data and sold it. Flip it: a system that reflects you (your expertise, your judgment, your way of seeing the problem) is valuable because you are.
The next time someone tells you to get off Excel, or that your data needs to be clean before AI can touch it, or that your workarounds need to be eliminated, consider the possibility that your workarounds are the smartest thing in the building. They show you where the real work happens, and what the official systems missed.
Read them. Then build the AI that respects them.