Service · AI Consulting
Find the AI opportunities worth pursuing – before technology becomes the goal.
Companies don't need as many AI applications as possible. They need the right ones. We look at processes, data and business models and pinpoint where AI can deliver a concrete economic return.
01Starting point
The real question isn't “Where could we use AI?” It is:
Where does AI actually pay off?
Many organisations start with tools or technology. We start with business processes, problems and objectives. Typical questions at the outset:
- 01
Which processes currently absorb unnecessary manual effort?
- 02
Where do media breaks or recurring errors occur?
- 03
Which decisions would benefit from better data?
- 04
Where do people lose time searching, documenting or handling routine tasks?
- 05
Which AI applications create measurable business impact?
02How we work
From analysis to a prioritised roadmap.
Every engagement follows a clear structure. Scope and depth depend on company size, the question at hand and the number of areas in focus.
01
Understand
We analyse the relevant processes, systems, data sources and organisational constraints.
02
Identify
We define concrete AI use cases rather than abstract ideas.
03
Assess
Each use case is rated on value, feasibility, data availability, effort and risk.
04
Prioritise
The result is a clear sequence of the projects that matter most.
05
Build the roadmap
We set out what can be delivered in the short term and what should be prepared strategically.
03Assessment
Consistent criteria for every use case.
To keep decisions transparent, every use case is assessed against the same criteria. The outcome is an opportunity matrix that weighs value against feasibility.
Business value
What time, cost or quality gains are realistic – and for whom?
Technical feasibility
Can today's models and tools solve the task reliably?
Data availability
Is the required data available, accessible and of sufficient quality?
Implementation effort
How much integration, development and organisational change is needed?
Risk
What requirements apply for data protection, traceability and human oversight?
Strategic relevance
Does the use case support company objectives or remain an isolated fix?
04Deliverables
What an AI consulting engagement produces.
Possible deliverables, depending on objectives and scope:
Prioritised use case list
Opportunity matrix
Business case assessment
Technology recommendations
Process and data requirements
Implementation roadmap
Make-or-buy recommendation
Governance and data protection requirements
05From advice to delivery
The work doesn't stop at the concept.
After the analysis, AI Infusion can lead the technical implementation or deliver it together with specialised technology partners – so responsibility for concept and outcome stays in one place.
Typical next steps are automating individual processes or building a custom AI application.
Next step
Where does AI pay off in your organisation?
Give us a short outline of your situation. In a first conversation we clarify which questions an AI consulting engagement should answer.
Discuss your AI potential