Short answer
When designing AI solutions or their go-to-market strategies for executive decision-makers new to AI, focus on clearly articulating the tangible value and ensuring strong security assurances, rather than solely emphasizing technical readiness.
- Field
- Innovation & Design
- Source
- Journal of Enterprise Information Management (2025)
- Method
- Quantitative research using survey data and statistical modeling.
- Sample
- 252 participants
- Evidence
- Strong effect
For CEOs without prior AI experience, the decision to purchase AI solutions hinges more on perceived value and security than on organizational readiness or compatibility. This innovation & design research insight is drawn from a 2025 study published in Journal of Enterprise Information Management. Using Quantitative research using survey data and statistical modeling. with 252 participants, researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing AI solutions or their go-to-market strategies for executive decision-makers new to AI, focus on clearly articulating the tangible value and ensuring strong security assurances, rather than solely emphasizing technical readiness.
AI Purchase Intention Driven by Perceived Value and Security, Not Just Readiness
For CEOs without prior AI experience, the decision to purchase AI solutions hinges more on perceived value and security than on organizational readiness or compatibility.
Journal of Enterprise Information Management · 2025
Key Findings
- 01Security and perceived value are the strongest positive drivers of AI purchase intention.
- 02Response costs act as a significant deterrent to AI purchase intention.
- 03Facilitating conditions and organizational compatibility have a secondary impact at the pre-adoption stage.
- 04Perceived value and organizational compatibility are necessary, but not sufficient, conditions for AI adoption.
Application
Design takeaway
When designing AI solutions or their go-to-market strategies for executive decision-makers new to AI, focus on clearly articulating the tangible value and ensuring strong security assurances, rather than solely emphasizing technical readiness.
How to apply
When developing business cases or product pitches for AI solutions targeting executive leadership, emphasize the ROI and security protocols. Frame the AI's impact in terms of strategic advantage and risk reduction.
Project actions
- 01When researching a new technology for a design project, consider who the decision-maker is and what their primary concerns might be, especially if they are not experts in the field.
- 02Think about how to communicate the benefits and risks of your design in a way that resonates with different stakeholders, not just end-users.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Novel model focusing on purchase intention rather than usage.
- +Combines two analytical methods (PLS-SEM and NCA) for a comprehensive view.
Limitations
The study's focus on CEOs limits its applicability to other organizational levels. The findings are based on purchase intention, which may not translate directly into actual adoption.
Reliability & validity
The study uses established statistical methods (PLS-SEM, NCA) and a substantial sample size, contributing to its reliability and validity. However, the reliance on self-reported data for purchase intention is a potential limitation.
Think critically
How might the findings change if the decision-makers had some level of AI experience, or if the technology was less complex than AI?
Design Principles
"For novel technology adoption by novice decision-makers, prioritize perceived value and risk mitigation (e.g., security) over internal readiness factors."
This insight challenges traditional adoption models by highlighting that strategic investment in new technologies like AI, especially by leadership unfamiliar with them, is primarily influenced by their perceived benefits and the associated risks. Understanding these drivers is crucial for technology providers aiming to effectively market and position their AI solutions to executive decision-makers.
What This Means for Your Design
If you want a boss who doesn't know much about AI to buy an AI tool, you need to show them how much money it will save or make them, and prove it's safe and won't cause problems.
How to use in your project
- 1.Reference this study when discussing the strategic decision-making process for adopting new technologies, particularly when user experience or perceived value is a key factor in the adoption of a design.
Add to My Project
Quick Cite
Paragraph starter
Research into AI adoption by executive leadership, such as that by Maldonado-Canca et al. (2025), indicates that perceived value and security are paramount drivers of purchase intention among CEOs with no prior AI experience. This suggests that for novel technologies, the strategic benefits and risk mitigation aspects often outweigh considerations of organizational readiness or compatibility during the initial decision-making phase.
Source
Journal of Enterprise Information Management
AI in enterprise management: determinants of purchase intention among CEOs without AI experience
journal · 2025
View sourceQuestions About This Research
- What does the research say about ai purchase intention driven by perceived value and security, not just readiness?
- When designing AI solutions or their go-to-market strategies for executive decision-makers new to AI, focus on clearly articulating the tangible value and ensuring strong security assurances, rather than solely emphasizing technical readiness. Evidence: Journal of Enterprise Information Management (2025).
- Why does "AI Purchase Intention Driven by Perceived Value and Security, Not Just Readiness" matter for design?
- This insight challenges traditional adoption models by highlighting that strategic investment in new technologies like AI, especially by leadership unfamiliar with them, is primarily influenced by their perceived benefits and the associated risks. Understanding these drivers is crucial for technology providers aiming to effectively market and position their AI solutions to executive decision-makers.
- How can designers apply this research?
- When designing AI solutions or their go-to-market strategies for executive decision-makers new to AI, focus on clearly articulating the tangible value and ensuring strong security assurances, rather than solely emphasizing technical readiness.
- What were the main findings?
- Security and perceived value are the strongest positive drivers of AI purchase intention.. Response costs act as a significant deterrent to AI purchase intention.. Facilitating conditions and organizational compatibility have a secondary impact at the pre-adoption stage.. Perceived value and organizational compatibility are necessary, but not sufficient, conditions for AI adoption.
- What research method was used?
- Quantitative research using survey data and statistical modeling. with 252 participants.
- How strong is the evidence?
- Evidence strength is rated Strong effect, based on a 2025 journal from Journal of Enterprise Information Management.
- What should I do differently in my next project?
- When developing business cases or product pitches for AI solutions targeting executive leadership, emphasize the ROI and security protocols. Frame the AI's impact in terms of strategic advantage and risk reduction.
- What are the limitations?
- The study focuses specifically on CEOs with no prior AI experience, which may not generalize to other executive roles or those with existing AI familiarity. The findings are based on self-reported purchase intention, not actual purchase behavior.