AI use case and opportunity assessment We show where AI pays off in your business, and where it does not.
Management expects something from AI. A list of ideas is circulating. But nobody has worked out which case pays off. The AI Value Scan covers the first two steps of our approach: we review workflows and data on site, assess the cases consistently and set a measurable target for the best ones.
What if your business could achieve more?
We find out where together with your team, before anything is implemented.
The AI Value Scan by DataClue shows where AI pays off in your business and where it does not. We review workflows, data and systems on site. Then we assess the use cases by business value, feasibility and effort. The result is an AI value map with three to five prioritized use cases and a clear recommendation for each one.
When the AI Value Scan fits
- AI is on the agenda, but there is no shared view of where it actually creates value.
- There are plenty of ideas, but business value, feasibility and effort have never been measured against the same yardstick.
- Pilots have started before anyone agreed which problem they should solve and how their success would be measured.
- Promising ideas have stalled late before because nobody checked data, interfaces or operating conditions early on.
What you walk away with
- An AI value mapThree to five prioritized use cases instead of a long list of ideas, each with the business problem, value drivers and feasibility.
- Baseline, target and measurement planWhere the data supports it, the value is quantified and a measurement plan agreed. Where it does not, the assumptions are stated openly instead of creating false precision.
- A clear recommendation per caseImplement, investigate further or stop, with effort, risks, dependencies and a sequence for implementation.
- A data and feasibility finding per caseWhich data is available, which interfaces are missing and what IT and data protection need to settle before the start.
What it takes
- Who is involved
- On your side: a contact person in the business and the specialists who run the workflows in question, for a few joint sessions. On ours: a consulting and engineering team working on site with you.
- What data we need
- Read access to the data of the workflows in question, for example from ERP, line-of-business systems, file storage and spreadsheets. We clarify exactly which in the first step.
- Data protection and IT
- The data stays in your systems or in an environment you choose, processed under the GDPR. We use AI models hosted in the EU. Your data is not used to train third-party models. Access rights, operating model and deletion are settled before we access any data.
How the AI Value Scan works
Focus the business questions
Agree on priorities, performance gaps and the decisions and workflows we look at.
Review workflows, data and systems
Understand on site how work gets done today and which data is realistically available.
Assess the use cases
Translate business problems into concrete use cases and compare them by the same yardstick: business value, effort, and feasibility in data, systems and day-to-day work.
Prioritize and set the target
Agree three to five priorities, the sequence and, for the first cases, the target, stop criterion and decision threshold.
Applied AI & Analytics
What does routine work cost you today? Estimate it with your numbers
For example entering documents, copying data between systems, routing requests or compiling reports. Your assumptions, not a forecast.
40hours of routine work per week, today · about one full-time position
AI Value Scan
Frequently asked questions
How is the AI Value Scan different from an AI readiness assessment?
A readiness assessment measures a company's maturity. The AI Value Scan assesses concrete use cases in your workflows by business value, feasibility and effort. For the prioritized cases it sets a measurable target.
Do we end up with an AI strategy deck?
No. You get prioritized use cases with target, effort and risks, and a clear recommendation per case. The result is built so that a priority case can move straight into implementation without restarting the analysis.
What if AI does not pay off for us?
Then we tell you. Stopping is a result too: it keeps budget and management attention from flowing into a pilot without value.
Do you commit to a particular AI platform?
No. The recommendation starts from the business problem and your existing systems, not from a preferred technology stack.
Contact
Which ideas on your AI list pay off?
Bring your AI agenda, an existing list of ideas or simply the workflows that cost your team the most time.
