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In 2020, an automated license-plate reader in Aurora, Colorado matched a plate number to a stolen vehicle report — but not the vehicle’s state or type. A patrol car pulled the vehicle over at gunpoint. At 87 degrees, they held the family for nearly 2 hours.

It was the wrong vehicle.

How is that possible?

Nobody had decided, in advance, that a partial match wasn’t enough to act on.

AI is running. Nobody designed what the human does next.

That gap — between machine output and the person who has to act on it — is where most AI deployments quietly fail. Not because the technology is wrong. Because nobody asked the right question before deployment: who is this decision for, and what are they authorised to do when the AI is confident and wrong?

Think of it as a fence. Someone has to mark the boundary before it can be built or enforced. That boundary is the spine — it decides what’s safe to automate and what isn’t. Most organisations build the fence — the guardrails — without ever having built the spine.

You can’t decide in the moment — there’s no time to say no. The decision happens before it runs, or it doesn’t happen at all.

How We Work

There are four parts to this. Most organisations focus on the last two.

The redesign. Before anything gets automated or enforced, the decision workflow itself has to be rethought — not documented as it exists today, but rebuilt around what AI can now actually do. Skip this step and you’re automating a workaround nobody needs anymore. This happens with a subject-matter expert who knows the workflow and its failure modes, working through what the process should be, not what it’s always been.

The spine. Out of that redesign comes the boundary or which decisions are safe to hand to AI, and which always need a person, regardless of how confident the system is or what further evidence might say. This is judgement work, done in advance, not in the moment.

The guardrail. The infrastructure that forms, holds, and enforces a decision once its boundary is set. This is genuinely hard engineering, and some of the best minds in AI are working on it right now.

The automation. The work that runs inside the boundary once it’s marked — fast, repeatable, and safe precisely because someone already decided it was safe.

Almost everywhere, the first two are missing. Organisations reach straight for enforcement and automation, on top of a decision process nobody redesigned and a boundary nobody set.

That’s where SpatialNext starts — with one focused engagement built around exactly that gap.

The Decision Spine Diagnostic

Two weeks. One workflow. Fully mapped. A focused engagement examining one consequential AI-enabled decision workflow — not as it’s documented, but as it actually runs. You leave with a redesigned workflow, a decision inventory, a boundary matrix, and an authority map built against the sign-off chains you already have: knowing exactly where your fence has no line marked, before a regulator, a plaintiff’s attorney, or a headline finds it for you.

If you’re deploying AI at a point where a wrong call has real consequences, and can’t currently answer — by name and in writing — what your system is actually authorised to do on its own, that’s usually where our conversations start.

Free 30-minute conversation. Learn more here or contact me directly: mattsheehan@spatialnext.io

Case Study

By the time the alert reached the patrol car, only one of three checks on the licence plate agreed. The second and third — the vehicle’s state and description — did not. Nobody had decided, in advance, what a partial match should mean, so the system treated one confirmed field as enough. It had a guardrail: rules that ran the check. It didn’t have a spine: nobody had decided a one-of-three match wasn’t enough to act on at all.

Aurora is not an isolated failure example. A Doritos bag mistaken for a gun got a sixteen-year-old handcuffed at gunpoint — a different sensor, a different model, the same missing layer: a signal became an action, and nobody had decided in advance whether the signal was enough.

That’s the gap this practice exists to close. Not after the stop. Before it.

That’s what the Decision Spine Diagnostic maps: Two weeks. One workflow. Fully mapped. Let’s have a free 30-minute conversation: mattsheehan@spatialnext.io

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AI is running. Nobody designed what the human does next.

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