Five Stages of AI-Driven R&D Evolution in Companies
Jan Bosch outlines five maturity stages for AI in R&D processes, from assistant to kaizen generator, transforming software development teams.
Jan Bosch, a research center director, professor, and startup investor, has identified five key stages that companies progress through when integrating AI into their R&D processes.
The AI Maturity Model for R&D
- AI Assistant: Generative AI supports individual developers by autocompleting code, generating test cases, and creating documentation, boosting productivity.
- AI Compensator: AI acts as a virtual team member, filling knowledge gaps in tools, domains, or regulatory compliance.
- AI Supercharger: Most of the team is replaced by AI agents, with humans overseeing prompts and outputs for maximum efficiency.
- AI System Generator: A fully autonomous AI team generates complete, tested systems based on intent-driven prompts.
- Kaizen AI Generator: AI continuously monitors, experiments, and improves systems, optimizing performance across multiple instances.
Industry Impact and Future Outlook
- Software engineering is at the forefront of AI adoption, with disruptions reshaping traditional roles.
- Jevon’s paradox suggests increased demand for software engineers as AI reduces costs and expands possibilities.
- Generative AI amplifies human creativity, according to Fi-Fi Li, rather than replacing it.
This series explores AI’s transformative role in R&D, with implications for software, mechanics, and electronics.
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About the Author
Alex Thompson
AI Technology Editor
Senior technology editor specializing in AI and machine learning content creation for 8 years. Former technical editor at AI Magazine, now provides technical documentation and content strategy services for multiple AI companies. Excels at transforming complex AI technical concepts into accessible content.