Automating the Mess

The lines under "How it sounds" are typical phrasing we wrote, not quotes from clients or interviews.

How it sounds

• “Can AI fix our onboarding?”
• “Let's have AI answer the tickets so we don't have to sort out the ticket process.”
• “Only Maria knows how month-end works, but maybe AI can learn it.”

What it looks like

AI gets put on top of a process nobody has written down or agreed on. The output is inconsistent, exceptions pile up and people blame the tool. Meanwhile the knowledge that would make it work is still in one or two people's heads.

Why it happens

Fixing a process is slow and sometimes political, and buying AI feels like a way to skip that step. When one person holds all the context, the rest of the team can't use a tool to do that work. AI can't follow a process nobody has written down.

What it costs

• The 2025 DORA report (nearly 5,000 technology professionals worldwide) found that AI "magnifies the strengths of high performing organizations and the dysfunctions of struggling ones," and Google's announcement of the report says AI adoption "does continue to have a negative relationship with software delivery stability." That's software teams, so for other work it's direction.
• We don't have a dollar figure for automating a broken process, so the cost is our reasoning: rework, exceptions handled by hand and a team that decides AI doesn't work here.

First move

Pick the one process you most want AI to help with and write down how it's done today, with the people who do it. Fix the obvious breaks first, then try AI on the written version.

The fifteen patterns, with what each one costs and a first move, are in The AI anti-pattern field guide.

An AI strategy decides who owns the work, which tools stay, and what changes first.

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