Use Cases
What AI and GEO concretely make possible.
Two equally weighted areas, many possibilities: from visibility in generative search systems to a custom AI solution in everyday work.
The following examples are possible use cases. They do not represent client projects that have already been delivered. Until real cases can be published, they serve to illustrate what's possible.
How each use case is structured
- 01Starting situation
- 02Challenge
- 03Possible AI solution
- 04Required data and systems
- 05Expected business value
- 06Possible limits or prerequisites
GEO Use Cases
AI Visibility Monitoring
- Starting situation
- A company doesn't know whether and how it appears in generative search systems.
- Challenge
- Without measurement, AI visibility stays a black box – opportunities and risks are unclear.
- Possible AI solution
- Continuous monitoring of relevant prompts, brand mentions and sources with Peec AI, interpreted by Midas Touch.
- Data & systems
- Topic and prompt list, competitors, website content, access to the monitoring platform.
- Expected value
- Transparency about your own AI visibility and a foundation for targeted measures.
- Limits & prerequisites
- Results develop over time; a reliable conclusion needs several measurement cycles.
Competitor analysis in generative systems
- Starting situation
- A company suspects that competitors are recommended more often in AI answers.
- Challenge
- Without analysis, the reasons competitors are mentioned can't be understood.
- Possible AI solution
- A comparative analysis of share of voice, sources used and competitors' content approaches.
- Data & systems
- Defined prompts, a competitor list, publicly available content.
- Expected value
- An understanding of why certain providers are mentioned, and concrete starting points to catch up.
- Limits & prerequisites
- Generative systems are dynamic; results can differ between platforms.
GEO content strategy
- Starting situation
- The website doesn't answer the audience's questions in an AI-readable, citable form.
- Challenge
- Content exists, but isn't structured so that generative systems can reliably use it.
- Possible AI solution
- Content gap analysis, optimisation of structure and entities, and content briefings for new content.
- Data & systems
- Existing website content, relevant prompts, thematic priorities.
- Expected value
- A higher likelihood of being considered and cited in relevant AI answers.
- Limits & prerequisites
- Impact emerges over the medium term and in alignment with existing SEO activities.
International GEO analysis
- Starting situation
- A company is active in several countries and languages.
- Challenge
- AI visibility differs by market, language and platform.
- Possible AI solution
- Separate analyses by market and language, with market-specific prompts and competitors.
- Data & systems
- Market-specific prompt sets, local competitors, multilingual content.
- Expected value
- A clear view of strengths and gaps per market instead of a blanket overall view.
- Limits & prerequisites
- Scope and effort grow with the number of markets and languages (GEO Scale).
AI Use Cases
Company-wide knowledge assistant
- Starting situation
- Knowledge is spread across documents, wikis and drives and is hard to find.
- Challenge
- Employees lose time searching for information and answers.
- Possible AI solution
- An internal AI assistant that accesses approved documents and knowledge sources and answers questions.
- Data & systems
- Document repositories, wikis, a permission system, defined access roles.
- Expected value
- Faster access to company knowledge and fewer follow-up questions in the team.
- Limits & prerequisites
- Quality depends on the data foundation; permissions must be mapped cleanly.
AI agent for customer enquiries
- Starting situation
- Incoming customer enquiries are reviewed, classified and distributed manually.
- Challenge
- This takes time and leads to inconsistent response times.
- Possible AI solution
- An AI agent classifies enquiries, suggests replies and routes them to the responsible team.
- Data & systems
- Historical enquiries, a knowledge base, integration with the ticket or mail system.
- Expected value
- Faster, more consistent handling and relief for the service team.
- Limits & prerequisites
- Sensitive cases should still be reviewed by people.
Automated proposal preparation
- Starting situation
- Proposals are compiled manually from various sources.
- Challenge
- Creating them is time-consuming and error-prone.
- Possible AI solution
- A workflow that gathers relevant information, prepares a proposal and submits it for review.
- Data & systems
- Product/price data, CRM, proposal templates.
- Expected value
- Faster proposal creation and more time for the substance of the discussion.
- Limits & prerequisites
- Final approval stays with sales; data quality is decisive.
AI-supported document review
- Starting situation
- Documents need to be checked for completeness and specific criteria.
- Challenge
- Manual review is monotonous and time-intensive.
- Possible AI solution
- An agent extracts relevant information, checks it against defined criteria and flags anomalies.
- Data & systems
- Document samples, review criteria, optionally a connection to a DMS.
- Expected value
- Consistent review and a team focus on the exceptions.
- Limits & prerequisites
- For legally relevant checks, human oversight remains necessary.
Research agent for sales & marketing
- Starting situation
- Research on accounts, topics and competitors ties up a lot of time.
- Challenge
- Information is scattered and has to be pulled together manually.
- Possible AI solution
- An agent researches, summarises and prepares the results in a structured form.
- Data & systems
- Public sources, internal notes, CRM information.
- Expected value
- Better preparation of meetings and campaigns with less effort.
- Limits & prerequisites
- Results should be reviewed before use.
Content Quality Agent
- Starting situation
- Content is created in varying quality and tone.
- Challenge
- Consistent review is hard to ensure manually.
- Possible AI solution
- An agent checks content against defined criteria (tone, structure, completeness) and gives feedback.
- Data & systems
- Style guide, examples, review criteria.
- Expected value
- More consistent quality and fewer correction loops.
- Limits & prerequisites
- Editorial responsibility stays with the team.
Which use case fits your company?
Describe your situation to us – we'll check which GEO or AI use case realistically creates value.