AI Potential Analysis: An AI Readiness Assessment Based on Your Real Processes
Our AI readiness assessment shows where AI really adds value in your processes – not based on ideas, but along real workflows and activity volumes. The result: prioritised AI use cases with traceable business value, a solid target picture and a pilot ready to start.
with clear effort limits
process modelling along real workflows
ready to start with go/no-go criteria
certified information security
Why an AI readiness assessment?
Use cases without assessment
Ideas exist – but they are not consistently assessed for business value, feasibility and risk. A reliable prioritisation is missing.
Shadow AI
GenAI used via private accounts – without governance, without traceability and with risks for sensitive information.
No reliable target picture
It is unclear which use cases are really worthwhile, what benefit they deliver and how they can be operated securely.
What the AI potential analysis delivers
At the end there is no collection of ideas, but a basis for decisions: which AI use cases are worthwhile, in which order, and under which conditions they can be operated securely.
- Prioritised use cases with transparent assessment logic
- Quantified business value: time savings, lead time, quality and risk reduction
- Target picture of use cases, governance building blocks and integration principles
- Pilot use case ready to start: scope, success criteria, security and operations check, go/no-go
Our four-phase approach
Secure AI use in the short term, and in parallel a solid basis for prioritised use cases – governance and business value considered together from the start. After each phase you have a basis for decisions without committing too early.
01 · Establish secure AI use
Controlled company access instead of shadow AI – in parallel and optional, for example with a GDPR-compliant platform such as Langdock.
02 · Analysis along real processes
A business process analyst captures activities, volumes and media breaks in workshops and models relevant workflows in BPMN.
03 · Prioritisation, target picture & roadmap
Use cases are prioritised by benefit, feasibility, data situation, security and operability and turned into a consistent target picture.
04 · Prepare the pilot
A prioritised use case is made ready to start: scope, success criteria, security and operations check as well as go/no-go criteria.
Target picture: use and governance cleanly separated
This is what the AI potential analysis works towards: secure, controllable AI use – from the day-to-day work of business units to governance and operations, built in four layers.
Secure company access to AI
Central, controlled access instead of private accounts: identity/SSO integration, user and group management, usage guardrails, logging and transparency.
Knowledge & data sources per use case
Only relevant sources, connected as needed – such as DMS, intranet, policies, process documents, tickets and knowledge bases. Focus on quality, timeliness and permissions.
AI capabilities per use case
Purpose-bound and controlled: assistants and chat, research and answers, summarisation and extraction, classification, decision support.
Governance & operations
Trust through control: roles and permissions, logging and audit trails, traceability, ISMS-oriented processes, operations and support.
The role of the business process analyst
The business process analyst is an integral part of the AI readiness assessment. They run team-based workshops to identify potential and model selected processes in BPMN.
This means AI use cases are not just collected but assessed on the basis of real workflows, activity volumes and process variants – the solid foundation for prioritisation, deriving savings potential and later implementing a pilot.
Frequently asked questions about the AI potential analysis
What is an AI potential analysis?
A structured analysis of your processes that shows where AI delivers concrete value. Instead of just collecting ideas, we assess AI use cases based on real workflows and activity volumes in terms of business value, feasibility and risk.
How does an AI readiness assessment work?
In four phases: establish secure AI use, analysis along real processes, prioritisation with target picture and roadmap, and preparation of a pilot. We work in phases with clear effort limits – so after each phase you have a solid basis for decisions without committing too early.
How long does an AI potential analysis take?
That depends on the number of areas involved and the depth of the processes. In the initial call we clarify the right scope and define the effort limits for each phase.
What is the result?
Prioritised use cases with a transparent assessment, a target picture of use cases, governance building blocks and integration principles, and a pilot use case ready to start with scope, success criteria and go/no-go criteria.
What role does the business process analyst play?
The business process analyst captures activities, volumes and media breaks in workshops and models relevant workflows in BPMN. This means use cases are assessed on the basis of real processes – not just ideas.
Do we need a secure AI platform first?
Both run in parallel: controlled, GDPR-compliant use – for example with Langdock – reduces shadow AI immediately, while the potential analysis identifies the most valuable use cases.
What happens after the potential analysis?
The potential analysis is the starting point. How things continue with pilot, automation and operations is shown by our AI consulting – from workflow systems like n8n to Claude in the enterprise.
Where does AI add real value in your company?
Let’s find out in a no-obligation initial call which of your processes are worth an AI readiness assessment.
Your contact for the AI potential analysis
Board Member, cimt Group
Note: This text was created with AI assistance.