Bildschirmfoto 2025-08-26 um 07.47.48

AI chat management for banks and insurance companies: Act now to secure customer trust

A contribution from Sophie Hundertmark

Sophie Hundertmark is an expert in the practical use of artificial intelligence with a focus on chatbots, AI strategies and responsible technology integration. She is a researcher and lecturer at the Lucerne University of Applied Sciences and Arts and is currently writing her dissertation in the field of Conversational AI at the University of Fribourg. As a consultant, she supports companies, administrations and educational institutions in the introduction of effective AI solutions. More about Sophie Hundertmark on LinkedIn.

A CustomGPT was used for linguistic and stylistic creation – as well as for translation. This is based on the GPT-5 language model from OpenAI and was developed by Sophie Hundertmark herself.


When I talk to executives from banks or insurance companies today, I hear an exciting observation: They are well aware that fewer and fewer inquiries are coming via Google and that their customers’ information behavior is increasingly shifting to ChatGPT, Gemini or Perplexity. At the same time, I often hear the uncertainty: “We know that something is changing – but we don’t know what we should actually do.”

This is exactly where AI Chat Management comes in. Because it is no longer enough just to have a good website or to carry out search engine optimization. In the future, visibility will not only be decided by Google, but above all in AI-based dialog systems and AI summaries. In this article, I would like to show you what AI chat management means, why it is particularly relevant for banks and insurance companies – and how you can get started step by step.


What does AI Chat Management mean?

More than chatbots

Many people immediately associate the topic with AI chatbots on their own website. But AI chat management is much more: it is about the strategic control of visibility in all AI-based search and dialog systems.

These include:

  • Chatbots (e.g. on your own website or in apps)
  • Generative AI platforms such as ChatGPT or Claude
  • Google AI Summaries that appear in classic search results
  • Industry GPTs or specialized financial assistants

The three levels

As I described in an earlier article:

  • LLMO (Large Language Model Optimization) ensures the technical readability of your content.
  • GAIO (Generative AI Optimization) ensures that texts are formulated in an AI-compatible way.
  • AI Chat Management is the overarching strategy that brings together technology, content and organization.

Why banks and insurance companies are particularly affected

Trust as a currency

Especially in your industry, trust determines customer relationships. However, trust is not only created in direct conversations, but also where customers search for information. If ChatGPT or Google does not name you, a trust deficit will quickly arise.

Changing customer expectations

An example: Someone asks ChatGPT about “the best sustainable pension solutions in Switzerland”. If your bank or insurance company does not appear there, you are invisible to this potential customer.

Regulation and control

Banks and insurance companies must also ensure that information is correct, up-to-date and compliant. If you neglect AI chat management, you run the risk of ChatGPT providing incomplete or incorrect information – with serious consequences for reputation and trust.


Action plan for banks and insurance companies

1. carry out an analysis of the current situation

  • Check how you are currently visible in ChatGPT, Perplexity or Google AI Summaries.
  • Ask typical customer questions such as: “Which bank offers good pension solutions?” or “Which insurance company has the best offers for young families?”
  • Document whether and how you are named.

2. define goals

  • Think about which target groups are most relevant for you.
  • Focus initially on segments that are increasingly searching via ChatGPT (e.g. young investors, digitally savvy customers).
  • Defines measurable targets: number of mentions in AI systems, quality of responses, share of LLM.

3. optimize content

  • Creates dialog-capable content that answers typical customer questions.
  • Pay attention to technical readability (structured data, FAQ areas, semantic labeling).
  • Write texts in such a way that they are not only recognized by AI systems, but also rendered in a meaningful way.
  • Remember: It’s not just about being found, it’s about being present with the right content and the right positioning.

4. establish processes and roles

  • Appoint an AI Chat Manager who is responsible for the strategy.
  • Integrates compliance, marketing and IT – so that content is both technically correct and AI-optimized.
  • Sets up continuous monitoring to quickly identify incorrect responses and take countermeasures.

5. maintain customer focus

In the end, it’s always about the customer. AI chat management is not an end in itself, but a way to meet customer expectations and build long-term trust. Only when AI systems recognize you as a relevant, trustworthy source will they also show you to users.


Conclusion

For banks and insurance companies, now is the time to take action. AI chat management is not an optional gimmick, but a strategic necessity to remain visible and trustworthy in an AI-driven search landscape. Those who start early secure a decisive competitive advantage – and above all strengthen their most important capital: customer trust.

If you have any questions or would like to discuss the topic in more detail, please get in touch with me directly – I look forward to hearing from you.

preferably by WhatsApp message or e-mail.

Further information:

SEO 2025: How to become visible in AI searches with ChatGPT, Perplexity & Co. A contribution incl. Video interview with Prof. Dr. Nils Hafner.

Revolutionize your business visibility with AI Chat Management. Various offers to get you started.

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