Find where AI delivers.Start there.

Most AI programs start with the technology. The ones that work start with the work.

Grounded in global frameworks

Brought to you by wellgrounded.ai

How it works

Four steps. One clear direction.

A structured way to identify where AI creates real value — and where to begin.

01

Pick your industry and function

Select your industry from the list, then choose the function you want to explore.

02

Explore your AI opportunity map

See every job to be done classified by how AI fits. Click any to understand what generative and agentic AI can do — in plain English.

03

Rate your organisation's readiness

Rate your organisation's readiness across five dimensions — data, talent, governance, leadership, and change management.

04

Get your prioritised roadmap

Three waves — quick wins, scale, transform — built around your actual maturity with a build recommendation for each initiative.

✦ Generative AI use cases · ⟳ Agentic AI opportunities · ↗ Prioritised 3-wave roadmap · ↻ Tailored to your maturity

What you get

Clarity in minutes for faster decisions.

Full opportunity map

Every job to be done in your function, placed on the value chain and tagged by how humans and AI share the work.

Readiness-aware view

See which ideas fit your current data, skills, and governance posture — before you commit to a program.

Three-wave roadmap

Quick wins, scale, and transform — sequenced with build style (taker, shaper, maker) for each initiative.

How this tool thinks

Three principles behind every recommendation

01
Work first, technology second

Start with jobs to be done and process flow. Technology decisions come after the work is clearly defined.

02
Generative and agentic are not the same thing

Generative AI produces content and surfaces insight. Agentic AI takes actions across systems. Confusing the two is how programs get scoped incorrectly from the start.

03
Grounded in global frameworks

Every map is anchored in the APQC Process Classification Framework and O*NET occupational taxonomy, not model intuition.