AI on quality foundations
Find the AI use cases worth funding
AI Use-Case Discovery & Prioritisation turns a pile of AI ideas into a short, ranked list. Opportunities are evaluated on business value, feasibility, data readiness and risk. You get preliminary business cases for the strongest candidates and a clear recommendation on what to do next.
A senior lead replies within one business day. No obligation.
AI pressure, and no way to choose
The board, the ministry or the market expects AI. Ideas come from every department and every vendor. Without a common way to judge them, money goes to the loudest idea, or to pilots the data can't support.
What it costs: Money spent on the wrong ideas, pilots that never pay back, and fading trust in AI at board level.
What it sounds like:
“Everyone talks about AI. We don't know where to start.”
“Where would AI actually pay off for us?”
“We have dozens of ideas and no way to compare them.”
“Can our data even support this?”
Business value and data readiness, judged together
We start by identifying business problems and opportunities, including ideas your teams have already proposed. We evaluate where AI could create meaningful value, where conventional analytics or automation may fit better, and which opportunities deserve further investigation. Data readiness is checked early, because AI ideas often fail on data, not on the model. The result is a decision, not a long list.
The AI path
Two steps: AI Use-Case Discovery & Prioritisation, then AI Pilot-to-Production.
What you get
- A long list of AI use cases from across the business.
- An opportunity map: business value against data readiness.
- Preliminary one-page business cases for the strongest candidates, typically three. Each covers:
- the business problem and expected outcome;
- the expected value, and how it could be measured;
- indicative costs, effort and dependencies;
- data and technical readiness;
- key risks and assumptions;
- the recommended next decision.
Estimates and assumptions are clearly marked. These are not validated investment proposals.
- A recommended next step: a first pilot, with the data work it needs, or a reasoned recommendation not to start yet if no candidate is ready.
Typical first result
A ranked list of AI use cases, business cases for the strongest candidates, and a recommended next step.
A senior lead replies within one business day. No obligation.
How it works
- Workshops with the agreed business areas.We identify business problems and opportunities, including ideas already proposed.
- Evaluate and prioritise.Compare the agreed candidate opportunities on business value, indicative feasibility, data readiness and risk. Identify the candidates that merit a deeper look.
- Validate promising candidates.Review critical assumptions, available data, constraints and dependencies, at a depth appropriate to the engagement. This is not a full readiness assessment; where further feasibility work or a readiness assessment is needed, we say so.
- Recommend.Business cases for the strongest candidates and a recommendation to leadership.
A matrix with business value on one axis and data readiness on the other, a quick-wins area where both are high, and six example ideas plotted on it.
Feasibility and risk are also part of the ranking. High value and ready data alone don't make a use case viable.
Who does the work
A senior DataOfis lead runs the workshops and the scoring, keeping the discussion on business problems rather than tools. Analytics and data specialists from our network check the data behind the strongest ideas.
Working together
- Indicative duration: 2–3 weeks for a focused discovery, covering an agreed set of business areas and candidate opportunities. A broader, organisation-wide discovery is scoped separately.
- What DataOfis is responsible for: the agreed outputs — the long list, the opportunity map, the business cases and the recommendation. You decide which ideas to fund.
- Bought on its own: a recommended pilot can be built by your own team, by us, or by another provider.
- What we need from you: a sponsor, time from business-line leaders for the workshops, and access to the people who know the data.
Questions we often hear
Yes. We can start from your list and focus on scoring, data readiness and business cases.
We don't begin with tool selection. Where relevant, we consider technical options and constraints at a high level, without recommending a specific product before the requirements are clear. We have no vendor to favour.
Then we say so, explain why, and show what would need to change.
The recommended pilot can continue into AI Pilot-to-Production, with your team, with us, or with another provider.
What often comes next
Talk to us about your AI ideas
Tell us where AI sits on your agenda and which ideas you already have. We'll discuss how a discovery would work for you.
A senior lead replies within one business day. No obligation.
See what comes after discovery AI Pilot-to-Production