PRISE: A Framework for AI Product Incubation From Concept to Implementation
AI product incubation faces unique challenges such as difficulty in technical feasibility assessment, ambiguous value perception, and engineering transformation barriers. This research proposes the PRISE framework (Problem Definition, Rapid Validation, Impact Evaluation, Single-focus Development, En...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11077161/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | AI product incubation faces unique challenges such as difficulty in technical feasibility assessment, ambiguous value perception, and engineering transformation barriers. This research proposes the PRISE framework (Problem Definition, Rapid Validation, Impact Evaluation, Single-focus Development, End-to-End Productization), integrating design thinking, lean startup, and engineering practices with adaptive modifications for AI characteristics. Through analysis of seven cross-industry cases from Microsoft’s AI Vertical team, we validated the framework’s practicality. The research reveals five key patterns for successful AI product incubation: user-decision maker separation identification, lightweight validation priority, technology-value transformation mechanism, deep cultivation of vertical scenarios, and end-to-end delivery thinking. This framework fills the gap in AI product development methodology, providing systematic guidance and operational tools for practitioners while offering new perspectives for AI innovation management theory. |
|---|---|
| ISSN: | 2169-3536 |