Short answer
Develop AI innovations that not only offer functional benefits but also create opportunities for meaningful stakeholder interaction and investment, fostering both immediate appreciation and sustained engagement.
- Field
- Innovation & Markets
- Source
- Journal of Product Innovation Management (2025)
- Method
- Theoretical framework development and proposition formulation
- Evidence
- Moderate effect
The perceived value and trust in AI-driven innovations are significantly influenced by how stakeholders intrinsically and extrinsically invest their resources in engaging with them. This innovation & markets research insight is drawn from a 2025 study published in Journal of Product Innovation Management. Using Theoretical framework development and proposition formulation, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Develop AI innovations that not only offer functional benefits but also create opportunities for meaningful stakeholder interaction and investment, fostering both immediate appreciation and sustained engagement.
AI Innovations Thrive on Stakeholder Investment: A Model for Engagement and Value
The perceived value and trust in AI-driven innovations are significantly influenced by how stakeholders intrinsically and extrinsically invest their resources in engaging with them.
Journal of Product Innovation Management · 2025
Key Findings
- 01Stakeholder engagement with AI innovations can be conceptualized as intrinsic (cognitive/emotional investment) and extrinsic (relational investment).
- 02The way stakeholders think or feel about AI innovations can differentially impact the relationship between their engagement, perceived innovation value, and trust.
Application
Design takeaway
Develop AI innovations that not only offer functional benefits but also create opportunities for meaningful stakeholder interaction and investment, fostering both immediate appreciation and sustained engagement.
How to apply
When developing new AI products or services, map out the potential points of intrinsic and extrinsic stakeholder investment and design features that encourage and reward these investments.
Project actions
- 01When researching a new product, consider how users will 'invest' in it beyond just purchasing it.
- 02Think about how your design can encourage users to develop a relationship with the product over time.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Provides a novel framework for understanding stakeholder engagement with AI innovations.
- +Integrates psychological and relational perspectives on user interaction.
Limitations
It can be challenging to accurately measure 'intrinsic' and 'extrinsic' investments without extensive user studies.
Reliability & validity
The proposed framework's reliability and validity would need to be established through rigorous empirical testing across diverse AI innovations and user groups.
Think critically
To what extent can 'investment' be a purely voluntary act, and how might design ethically encourage or necessitate such investment from users?
Design Principles
"Foster stakeholder value through strategic resource investment in AI innovation engagement."
Understanding stakeholder engagement is crucial for the successful adoption and diffusion of AI innovations. By framing engagement as a form of resource investment, businesses can develop strategies to foster deeper connections, leading to increased perceived value and trust, which are vital for market success.
What This Means for Your Design
For new AI products to be successful, people need to feel like they are investing something in them, whether it's their time, thoughts, or emotions, and this investment helps them see the product as valuable and trustworthy.
How to use in your project
- 1.Use the concepts of intrinsic and extrinsic investment to analyze user engagement with your design concept.
- 2.Discuss how your design aims to foster perceived innovation value and trust through these investment mechanisms.
Add to My Project
Quick Cite
Paragraph starter
This design project explores how stakeholders' intrinsic and extrinsic resource investments in AI-leveraging innovations can cultivate perceived innovation value and trust. By conceptualizing engagement as a form of investment, the design aims to foster deeper user connections, leading to greater adoption and market success.
Source
Journal of Product Innovation Management
Innovations Leveraging Artificial Intelligence, Stakeholder Engagement, and Innovation Value: An Investment Model Perspective
journal · 2025
View sourceQuestions About This Research
- What does the research say about ai innovations thrive on stakeholder investment: a model for engagement and value?
- Develop AI innovations that not only offer functional benefits but also create opportunities for meaningful stakeholder interaction and investment, fostering both immediate appreciation and sustained engagement. Evidence: Journal of Product Innovation Management (2025).
- Why does "AI Innovations Thrive on Stakeholder Investment: A Model for Engagement and Value" matter for design?
- Understanding stakeholder engagement is crucial for the successful adoption and diffusion of AI innovations. By framing engagement as a form of resource investment, businesses can develop strategies to foster deeper connections, leading to increased perceived value and trust, which are vital for market success.
- How can designers apply this research?
- Develop AI innovations that not only offer functional benefits but also create opportunities for meaningful stakeholder interaction and investment, fostering both immediate appreciation and sustained engagement.
- What were the main findings?
- Stakeholder engagement with AI innovations can be conceptualized as intrinsic (cognitive/emotional investment) and extrinsic (relational investment).. The way stakeholders think or feel about AI innovations can differentially impact the relationship between their engagement, perceived innovation value, and trust.
- What research method was used?
- Theoretical framework development and proposition formulation.
- How strong is the evidence?
- Evidence strength is rated Moderate effect, based on a 2025 journal from Journal of Product Innovation Management.
- What should I do differently in my next project?
- When developing new AI products or services, map out the potential points of intrinsic and extrinsic stakeholder investment and design features that encourage and reward these investments.
- What are the limitations?
- The propositions require empirical validation; the specific nature of 'thinking' vs. 'feeling' AI innovations needs further definition; the model's applicability may vary across different types of AI innovations and stakeholder groups.