AI Transformation Services

Identify AI use cases that are actually worth building.

The board wants an AI roadmap by Q2. We need to understand how 500 people actually work. We can’t shadow 500 people.

When to use this

You can’t shadow 500 people

The board wants an AI roadmap but you don’t know how 500 people actually work. Workshops give you opinions, not reality.

Big commitment, thin evidence

You’re about to commit $5M to an AI platform but you haven’t validated whether the use cases actually justify it.

Pilots keep failing

Your AI pilots keep failing because you picked workflows that looked automatable from the outside but weren’t in practice.

How it works
1

Define what you need to learn

Map the processes, workflows, and pain points you need to understand before committing to a direction.

2

Deploy across functions

Capture how work actually happens today from every stakeholder group – not just the loudest voices in a workshop.

3

Find the real opportunities

Platform identifies where time goes, where friction is, and what’s realistically automatable versus what only looks that way.

4

Build the roadmap

Evidence-backed recommendations: which use cases, in what order, with what ROI – grounded in how people actually work.

Impact
Right use cases
AI roadmap based on real workflows and real pain, not assumed ones
Full picture
Every function’s reality captured, not just workshop opinions from the loudest voices
Validated before committed
Use cases pressure-tested before budget is spent on platforms
Adoption clarity
Know which teams will adopt and which will resist, before you roll out