1. Initial Situation

In recent years, the field of workflow automation has undergone a substantial technological shift driven by AI. Platforms such as n8n, Make.com, Zapier, Pipedream, and Node-RED are evolving from traditional automation tools into AI-supported orchestration systems through increasingly deep AI integration. As a result, both the capabilities of process automation and the required user competencies are changing.

However, the market is highly fragmented. Platforms differ significantly with respect to:

• Their process definition approaches (visual, declarative, script-based)
• The required skill level, determining the extent to which usage is possible without technical knowledge (no-code, low-code, developer-first)
• Their connectors, especially concerning AI models, third-party services, data sources and REST-APIs
• Their extensibility and deployment models (cloud, hybrid, self-hosted)

2. Research Goal/Research Questions

This leads to the central question: How do modern AI-enabled workflow automation platforms differ in terms of their modeling techniques, functionality and technical requirements for users?

The objective of this thesis is to conduct a systematic market analysis of AI-enabled workflow automation platforms. The focus is on the modeling techniques applied, the technical skills required from users, and the available connectivity and integration options. In addition, an exemplary workflow will be defined using subject-oriented modeling and implemented in relevant platforms for comparison.

Further research questions include:

• Which modeling techniques do AI-enabled workflow automation platforms employ and how do they differ from common process modeling approaches?
• To what extent and in what ways do the platforms use AI for workflow generation?
• What technical skills do users need to create, operate and monitor a complete workflow?
• How do no-code, low-code, and developer-first platforms differ regarding flexibility, complexity and usability?
• How can a subject-oriented workflow be implemented using workflow automation platforms?
• Which categories of tools can be derived from the systematic comparison?

 

3. Planned Method + Planned structure

3.1 Method

• Systematic market analysis based on product documentation, whitepapers and technical specifications
• Development of a criteria catalog focusing on:
  • Modeling techniques
  • Degree of AI support
  • Technical skill requirements
  • Connectivity and integration capabilities
  • Security and deployment options
  • Extensibility
• Selection of relevant and scope fitting platforms
• Criteria-based comparison of platforms in tabular form
• Synthesis of findings and derivation of platform categories