Utilising Generative AI to supercharge radical innovation in new product development
PhD - Qualitative research | Design theory | Industry relevance
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This research is turning GenAI from tool hype into repeatable innovation practice: frameworks, methods, and interventions that teams can actually use.
Services
Literature review
Case Study
Thematic Analysis
Research through design (RtD)
Frameworking
Frontier challenges
GenAI is rewriting how teams explore, decide, and design. The hard part isn’t the tools, it’s adoption, meaning, and trust.
Industry-backed
Built with real partners. Tested in real workflows. Evidence over hype.
Bridging disciplines
Where design meets AI. Where academia meets practice.
The research question
How can designers leverage Generative AI in the metaproject phase of new product development to facilitate radical innovation?
Why this matters
Most organisations are using GenAI to go faster. More concepts. More images. More options.
But radical innovation isn’t a volume problem. It’s a meaning problem: choosing which future is worth building and aligning a team around it.
My lens
My theoretical anchor is Verganti’s Design-Driven Innovation, particularly the role of Key Interpreters in shaping meaning and guiding radical innovation.
GenAI introduces a new actor into that system: a synthetic collaborator that can simulate users, generate alternatives, remix references, and accelerate sensemaking. The question becomes: does it dilute interpretation, or amplify it?
Method
This is applied research grounded in real organisations.
Study 1: Multi-case qualitative study
A deep look at how Key Interpreters are currently using GenAI in early-phase work:
Attitudes, behaviours, toolchains
How meaning is created, negotiated, and sold internally
Where GenAI accelerates vs. confuses vs. changes decision authority
Study 2: Research-through-Design / Design action research
I design and test GenAI-enabled methods with partners:
Workshops, prompts, workflows, prototypes
Measurable criteria for “better” early-phase decisions
Refined framework based on outcomes, not opinion
Scale
PhD by thesis, 70,000 words, 3 studies
4 Industry partners, 37 participants
Industry frameworks, academic publications
Credits
All research, critical thinking, and theory development by Thom Luke / Threshold Design.
This research builds practical knowledge on how designers acting as key interpreters in the metaproject phase of new product development, can use GenAI to augment their practice, enabling radical innovation.
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