AI Strategy & Impact

Every AI project should tie back to one number

We help you pick the AI use cases worth pursuing, then measure whether they actually moved a real business metric, not just whether they deployed.

You don't need faith that this works. You need someone who's scored it before.
4‑partframework, scored before anything is built
35+years running Microsoft-first IT
600+engineers
24/7AI operations coverage after launch
How we prioritize

Four things we score, before anything gets built.

Most AI backlogs don't need a longer list. They need a way to tell which three items on the list you already have are worth funding first. Part of Netrix Global's broader AI practice.

The number it moves

If nobody can name the metric, it isn't ready to build yet.

  • Cycle time
  • Error rate
  • Cost per ticket, time to first response

What it actually takes

Not just how good the demo would look.

  • Data readiness
  • Integration work
  • Model risk

How fast you'd know

A tightly scoped use case can show a signal within a quarter. One that touches five systems won't, and that's fine to know going in.

  • Tightly scoped: a quarter
  • Multi-system: longer, by design
  • Timeline set before you start

Who owns it

A named business owner accountable for the metric, not just an IT owner accountable for the deployment.

  • A named business owner
  • Accountable for the metric
  • Not just the deployment
How we measure impact

A baseline you can hold us to.

We measure impact against the number we baselined before we built anything, not against whether the thing technically works.

We sit down with the people sponsoring the work, usually IT leadership alongside whoever owns the budget, and run the use case list through the framework above. What comes out is a sequenced roadmap: what to build first, what to build once the data's ready, and what to shelve for now.

Before anything ships, we baseline the metric it's supposed to move. Once something's live, our AI operations team keeps watching it, because deployed AI drifts, and a metric that looked good in month one can slide by month four.

Strategy is usually first, and it points to everything after it: agent buildouts and integration for use cases that need an agent tested against real systems, workflow and automation for the repetitive work eating a day a week, and user adoption and training so what gets built actually gets used. If it turns into an ongoing need for AI-specific leadership, a Fractional Chief AI Officer can own it without a full-time hire.

1–2weeks for the working sessions and scored roadmap
4things scored before anything gets built
1 qtrto see a real signal on a tightly scoped use case
OngoingAI operations monitoring after launch
Why Netrix

Why score it with us.

Plenty of consultants will run a workshop and leave you with a deck. Here's what's different about scoring your AI list with Netrix Global.

Questions we get first

Questions we get first.

Before you build anything.

How do you decide which AI use cases to prioritize?
How is this different from an AI Readiness Assessment?
Do we need a formal strategy engagement if leadership already picked a use case?
How long does an AI strategy engagement take?
What if the AI use case doesn't move the number we expected?
Ready when you are

Find out which of your AI ideas is actually worth building first.

Thirty minutes with an engineer who'll run your list through the same framework we use with every client.

Get an AI Strategy Session
No slideware. Just the framework, run against your actual list.