Treat AI as a junior teammate not as a replacement: business researchers
Key Points
- Research led by Nyenrode Business University on AI in product development
- Advises treating generative AI as a "synthetic teammate", not a staff replacement
- "Human-first" approach: humans keep responsibility for objectives, inputs, processes, outputs
- AI helps across four stages: customer insight, idea generation, prototyping, launch
- Risks to manage: errors, bias, misuse of data
Companies building new products should treat generative AI as a “synthetic teammate” that supports staff rather than replaces them, according to new research led by Nyenrode Business University.
The research sets out a “human-first” approach in which AI works alongside teams much like a junior colleague would – useful for speeding up work and generating ideas, but requiring close management to guard against errors, bias and the misuse of data.
Under this model, humans stay responsible for objectives, inputs, processes and outputs, with the technology enriching rather than leading the work.
The study was led by Stefanie Beninger and Dieter Vlaminck at Nyenrode, working with colleagues from IE University, Royal Holloway, University of London, The Pennsylvania State University and Dickinson College.
The researchers set out four stages of product development where generative AI can help, and where human oversight remains essential:
- Understanding customers – AI can act as a marketing intelligence researcher, analysing data to surface new customer segments and needs. Human oversight is needed to check data quality and relevance.
- Generating new ideas – AI can produce a high volume of creative suggestions, but managers must stay open-minded and screen those ideas for quality and feasibility.
- Concept development and prototyping – AI can speed up prototyping and design work, though human expertise is required to ensure quality and compliance with project specifications.
- Launching and commercialising – AI can support marketing and supply chain strategies, but human judgment is needed to adapt to cultural nuances and market realities.
The central message is that AI should encourage and enhance innovation while keeping people in charge.
As a junior member of the team, the technology is valuable but must be carefully managed to avoid risks including errors, bias and the potential misuse of data.
Beninger and Vlaminck argued that, approached this way, AI becomes a genuine team member that strengthens innovation without displacing human leadership.
