Find the AI opportunities that matter for your business. Our discovery workshops identify high-impact use cases based on your actual operations.
The best AI projects solve real problems. The worst ones chase technology for its own sake. Our discovery process helps you find the opportunities where AI can genuinely move the needle for your business.
Most organisations have more AI ideas than they can possibly pursue. The challenge is not generating possibilities but identifying which ones deserve investment. Get this wrong and you waste time, money, and enthusiasm on projects that never deliver.
We have seen too many businesses pick AI use cases based on what is fashionable rather than what fits their situation. Discovery done properly prevents this.
Our discovery process uses structured workshops combined with operational analysis. We bring AI expertise. You bring knowledge of your business. Together, we identify opportunities that neither side would find alone.
Operational mapping comes first. We learn how your business actually works: where effort goes, where problems cluster, where opportunities hide. This often reveals AI applications that are not obvious from the outside.
Ideation workshops generate possibilities. We facilitate sessions with cross-functional teams, using prompts and frameworks designed to surface practical ideas. Participants leave with dozens of potential use cases, not vague concepts.
Prioritisation narrows the field. We assess each idea against criteria that matter: potential impact, technical feasibility, data availability, implementation complexity, and fit with your strategic direction. What emerges is a shortlist you can act on.
Discovery produces a use case portfolio document containing:
An inventory of AI opportunities. The full set of ideas surfaced, written clearly enough to compare.
Profiles for top-ranked use cases. What the use case is, who it serves, what it changes, and what “success” means.
A prioritisation view. A matrix showing impact, feasibility, risk, and readiness so decisions are transparent.
Dependencies and prerequisites. Data, integrations, process changes, and ownership required for each priority item.
A recommended delivery sequence. What to do first, what to do next, and what to defer.
Early delivery guidance. The likely shape of the work and the key assumptions to validate before build.
The format is practical. Each use case profile includes enough detail to inform investment decisions and start scoping work.
Most discovery engagements include two to four workshop sessions, each lasting half a day. These work best with diverse participants: leadership, operations, customer-facing teams, and technical staff.
Between sessions, our team analyses findings, conducts research, and prepares materials. The process typically spans two to three weeks.
Consider use case discovery when:
You know AI could help but are unsure where to start. You need a structured way to identify opportunities that match your reality.
You have a long list of ideas and need to choose. You want a transparent method to prioritise based on impact and feasibility.
Previous AI projects missed expectations. You want a more rigorous approach that surfaces constraints and assumptions early.
Resources are limited. You need to focus on the highest-impact opportunities first and avoid distractions.
Use these prompts to explore and refine opportunities before you commit to a shortlist.
“What are the most valuable AI opportunities in our business, based on where time and errors cluster today?”
“Which opportunities are feasible with our current data and systems, and what would block delivery?”
“How should we define success metrics for each use case so we can evaluate results honestly?”
A structured process to identify and prioritise AI opportunities based on business impact, feasibility, and organisational fit.
Strategy sets direction and principles; discovery creates a concrete, ranked portfolio of initiatives tied to real operational work.
No. We start from business processes and outcomes, then identify what data and integrations matter for feasibility.
A cross-functional group that understands how work is actually done—operations, customer-facing teams, IT—and someone who can make prioritisation decisions.
Typically feasibility for the top use case(s), then a scoped build plan with clear guardrails, metrics, and ownership.