Breakfast Session: AI Agents in Practice | 06.10.2026 | Zurich

From Use Case to Everyday Operations

Explore practical applications with Claude, Qlik and n8n, alongside a banking example that puts business context and accountability into focus. Join HICO Group in Zurich on October 6 for live demonstrations, discussion, coffee and croissants.

What Can AI Agents Take Off Your Team’s Desk?

Cleaning inconsistent data, preparing reliable information for analysis and connecting systems all involve recurring work. AI agents can support these tasks. Putting them into everyday use also raises practical questions: Which data can they trust? Who defines the rules? And when should a person review the result?

At our breakfast session in Zurich, we bring these questions together. Following a short introduction to responsibility and governance, we explore three live workflows developed with Claude, Qlik and n8n. A fourth example from banking looks at what happens when an AI agent needs to interpret a business metric.

There will be time to discuss your own processes, ask questions and consider which approaches could work in your organisation.

Four practical perspectives on AI agents

1. Clean data and assign sales territories with Claude

Inconsistent location data can make assigning sales territories a time consuming task. This example shows how Claude cleans source data, assigns postal code areas to the relevant territory manager and flags uncertain cases for review. The results are then prepared for use in Qlik Analytics.

We also look at how coding agents can support the development and maintenance of data pipelines.

2. Build a Trusted Data Product with Qlik

Teams need to understand what their data contains, which rules have been applied and whether it is suitable for the task. This demonstration explores how the Qlik Data Product Agent brings sources together, applies business rules and documents the resulting data product.

The focus is on making data quality visible and helping people understand why they can trust the information they use.

3. Automate Interfaces and Data Workflows with n8n

Connecting systems often involves repetitive work, particularly when interfaces or data structures change. We show how n8n, REST APIs and AI can work together to interpret API responses, suggest field mappings and flag inconsistencies.

The example explores how data transfer and validation can be automated, and where human review remains necessary.

4. A Banking Example: What Does “Revenue” Mean to an AI Agent?

“What was our revenue last quarter?” sounds like a straightforward question. An AI agent still needs to know which definition applies, which entities to include and which source is authoritative. We discuss how an agent could support this reporting task and what it needs to produce a useful answer. The example brings together business definitions, trusted data and clear ownership, considerations that matter whenever teams use AI to prepare information for decisions.

From Live Examples to Your Own Use Cases

Together, we will discuss where these approaches could support your team, which prerequisites matter and how to decide whether an AI agent or a conventional workflow is the right fit.

You will leave with a clearer understanding of:

• Which recurring tasks are suitable candidates for AI support.
• What data, business rules and responsibilities need to be in place.
• Where human judgment and approval remain essential.
• How to move from a promising example towards everyday use.

Who Should Attend the Breakfast Session in Zurich?

This session is for business and technology professionals evaluating practical uses of AI, including leaders and specialists in BI, Data & Analytics, IT, Data Engineering, Sales Operations, Finance and Digital Transformation.

Professionals from banking and wealth management will also find a dedicated example addressing business context and accountability.

You do not need deep technical knowledge. The session combines demonstrations with business questions and open discussion.

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