CAIN 2025

Welcome to CAIN 2025 — 4th International Conference on AI Engineering – Software Engineering for AI

Co-located with ICSE 2025

April 27-28th, 2025

The CAIN Conference Series aims to bring together researchers and practitioners in software engineering, data science, and artificial intelligence (AI) as part of a growing community targeting the challenges of Software Engineering for AI-enabled systems. In the development and implementation of AI-enabled systems — defined as systems that contain AI components — experience has shown that the main challenge is not to develop the best models or algorithms but rather to provide support for the entire system life cycle – from a business idea, through data collection, model training, system design and development, product deployment and operation, and eventually its maintenance and evolution. Therefore there is a clear need to advance the field of Software Engineering for AI. While there are many well-established venues in the fields of AI and machine learning (ML), CAIN is unique because it takes a systems and life cycle perspective on AI engineering.

CAIN has the following goals for the following years.

• Identify the main challenges in software engineering for AI systems, considering industrial needs and experience.
• Create a roadmap that captures research directions in AI engineering in relation to AI-enabled systems life cycle and the software engineering practices to support it.
• Contribute to a better understanding of the differences between data science and software engineering approaches such that practices from both fields can come together to solve practical problems in AI engineering.
• Identify industrial challenges in building and using AI-enabled systems and contribute to solving them.
• Build a thriving community of software engineering, data science, and AI practitioners and researchers

CAIN’25 will have sessions that combine submissions from multiple tracks:

• Invited keynotes and panels
• Presentations of accepted research and experience papers
• Industry talks
• Poster presentations

Scope and Topics of Interest

The area of interest for CAIN is Software Engineering for AI Systems — improving the development of AI-based systems throughout the full life cycle. Topics include but are not limited to:

• System and software requirements and their relationship to AI/ML modeling.
• Data management to ensure relevance and efficiency related to business goals.
• System and software architecture for AI-enabled systems.
• Integration of AI and software development processes into the AI system development life cycle, including continuous integration and deployment, and system and software evolution.
• Assurance and management of g system and software nonfunctional properties and their relationship to AI/ML properties, including runtime properties such as performance, safety, security, and reliability; and life-cycle properties including reusability, maintainability, and evolution.
• Collaboration, organizational, and management practices for successful development of AI-enabled systems.
• Building effective infrastructures to support the development of AI systems and components.
• Software engineering methods and tools for next-gen AI systems (e.g., systems that integrate foundation model-based systems/agents)

Note on Scope: Submissions that report strictly on data science or model development without any connection to software engineering and AI-enabled systems will be desk-rejected. As stated earlier, there are many venues for those papers where authors would get much more valuable and relevant feedback. Additional information on CAIN scope can be found here.

The CAIN’25 conference is co-located with the 47th International Conference on Software Engineering (ICSE’25). Please find more information about ICSE’25 here. Stay tuned for more information!