What Should Stay Human When You Embed AI Into Operations?
A liability-based framework for deciding which decisions must stay human when you embed AI into business operations, and which are just coordination work.
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A liability-based framework for deciding which decisions must stay human when you embed AI into business operations, and which are just coordination work.
The old route for contract review is email, PDFs, and Word track changes. Here's how I'd design an AI-native system that compares against a playbook and keeps judgment calls human.
A teardown of why onboarding stays slow across HR, IT, and payroll, and how a coordination layer — not a chatbot — would fix the handoff.
A system teardown of vendor onboarding: why chasing tax forms, insurance certificates, and bank details still takes weeks, and what an AI-native intake and risk-tiering system would automate versus keep human.
Adding an AI agent to a broken workflow rarely fixes it. Here's why the failure is usually the process, not the model — and what to map before you automate.
A system teardown of expense report reconciliation: why the old route of receipts, card statements and spreadsheets persists, and what an AI-native coordination layer would look like.
Most AI adoption fails not because the model is bad, but because teams skip the workflow redesign and bolt AI onto a broken coordination layer. Here is where adoption should actually start.
A system teardown of accounts payable: why three-way matching is still manual, and what an AI-native invoice processing route would automate and keep human.
The 1995 insurance claims workflow is a document relay between six people. Here's how I'd redesign it as an AI-native intake, triage, and settlement route.
Where the AI-to-human handoff should actually sit in a workflow, using refund and return approval as the worked example.