[This post is based on Marit Pasterkamp‘s Information Science Master thesis]

Recent advances in AI have led many software companies to add AI features to their products. But what happens when AI is no longer just a feature and becomes the primary interface? In her Master Information Science thesis at VU Amsterdam, Marit Pasterkamp explored this question in the context of marketing automation. Working with Spotler, she designed and evaluated an AI Agent that allows users to create marketing customer journeys through natural language instead of manually building workflows.

Using a user-centered design approach, she developed a functional prototype and tested it with both experienced and inexperienced users. The findings showed that both groups saw value in the AI Agent, but for different reasons. Experienced users appreciated it most for creating complex journeys quickly, while novice users benefited from the lower learning curve and intuitive conversational interface.

Screenshot of the AI Agent prototype showing the two-column editor, with on the left the conversational window and on the right the visual flow canvas.

A key finding was that trust differs between user groups. Experienced users tended to verify AI-generated output before accepting it, while inexperienced users often trusted the AI and instead doubted their own knowledge.

The research concludes that AI Agents can function as effective interfaces for journey creation, but work best in a hybrid approach that combines AI-generated output with opportunities for manual editing and validation. Transparency, usability, and user control remain essential for successful adoption.

Reference

Pasterkamp, M. (2026). Maintaining Usability and Trust: The Effective Design of an AI Agent-driven Interface for Customer Journey Automation in the Marketing Technology Domain. Master’s Thesis, Vrije Universiteit Amsterdam