Back Exploring AI for Product Innovation: Hands-on Insights from TRICAS
Artificial Intelligence (AI) is transforming industries worldwide, but how can it contribute to the innovation process? At TRICAS, two interns from different Universities of Applied Sciences recently explored this question briefly through a hands-on AI tool-scouting exercise.
Starting with a broad inventory of AI tools, they mapped out those most relevant to product innovation and concepting. But theory alone isn’t enough—the real value of these tools only becomes clear through practical application. So, they tested the tools in a realistic case study, using AI across different phases of the innovation process.
Key Takeaways: AI in Product Innovation
Analysis Phase
- Iterate: Quickly defines project focus and product propositions with structured guidance.
- Claude.ai & ChatGPT: Used for functionality schemes and persona creation—Claude generates visuals, while ChatGPT provides textual content.
- ChatGPT: Helped generate a Brand Identity Prism.
- Moo’ed AI: Useful for creating mood boards.
Ideation Phase
- ChatGPT: Extensively used for brainstorming technical and styling options. It also generated concept visuals, though without deep rationale behind its proposals.
- IGOR^AI: A powerful search engine designed to enhance technology scouting for research and development (R&D) teams. This has been part of the TRICAS innovation process for some time.
Concept Phase
- Vizcom: Helped refine the aesthetic appearance of the product. While it lacks understanding of technical functionality and offers limited design control, it can generate a 3D model suitable for 3D printing.
Lessons Learned
The students’ experiment showed that AI can be a powerful tool, but it requires curation. While some tools proved incredibly useful, others were too superficial or lacked functionality. Prompting skills are crucial, as results vary significantly between tools.
Another key insight: AI performs much better on popular topics. Using AI for a well-known product category, like a car, yields far more useful results than for a niche or highly specialized product. The more common the topic, the richer the AI-generated insights and outputs.
AI is evolving fast, and product developers need to stay ahead of the curve. At TRICAS, we are actively training ourselves in applying AI and continuously tracking its developments.
Curious about how AI can enhance your product innovation process? Let’s connect and explore the possibilities together!
