Short answer
To encourage the adoption of AI coaching chatbots, designers must focus on making them demonstrably effective, simple to operate, and engaging for users, while also proactively mitigating fears related to technology use.
- Field
- Innovation & Markets
- Source
- Journal of Work-Applied Management (2025)
- Method
- Quantitative survey analysis using a modified technology acceptance model.
- Sample
- 139 participants
- Evidence
- Strong effect
The adoption of AI coaching chatbots in contact centres is significantly influenced by users' perception of performance enhancement, ease of use, and the enjoyment derived from the interaction. This innovation & markets research insight is drawn from a 2025 study published in Journal of Work-Applied Management. Using Quantitative survey analysis using a modified technology acceptance model. with 139 participants, researchers explored how this design variable affects real-world outcomes. The key design takeaway: To encourage the adoption of AI coaching chatbots, designers must focus on making them demonstrably effective, simple to operate, and engaging for users, while also proactively mitigating fears related to technology use.
AI Coaching Chatbots: User Adoption Driven by Performance, Ease of Use, and Hedonic Motivation
The adoption of AI coaching chatbots in contact centres is significantly influenced by users' perception of performance enhancement, ease of use, and the enjoyment derived from the interaction.
Journal of Work-Applied Management · 2025
Key Findings
- 01Performance expectancy (belief that the chatbot will improve performance) directly influences intention to use.
- 02Effort expectancy (belief that the chatbot is easy to use) directly influences intention to use.
- 03Hedonic motivation (enjoyment derived from using the chatbot) directly influences intention to use.
- 04Vulnerability (fear of negative impacts from technology) influences intention to use.
Application
Design takeaway
To encourage the adoption of AI coaching chatbots, designers must focus on making them demonstrably effective, simple to operate, and engaging for users, while also proactively mitigating fears related to technology use.
How to apply
When developing or implementing AI coaching tools, conduct user research to understand perceptions of performance benefits, usability, and enjoyment. Design training and communication strategies that highlight these aspects and address potential user anxieties.
Project actions
- 01When designing a new technology, consider how users will perceive its benefits and ease of use.
- 02Think about ways to make using the technology enjoyable, not just functional.
- 03Anticipate and address potential user fears or concerns about the technology.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Combines established technology acceptance models with a specific index (TAP).
- +Uses a robust statistical method (PLS-SEM) for analysis.
- +Addresses a relevant and growing area of AI application in the workplace.
Limitations
The study's findings are based on self-reported intentions, which may not always translate to actual behaviour. The specific context of contact centres might mean the results aren't directly applicable everywhere.
Reliability & validity
The use of established theoretical models (UTAUT2, TAP) and a robust statistical method (PLS-SEM) suggests good internal validity. However, the cross-sectional nature of the survey limits the ability to establish causality and may affect external validity if the contact centre context is highly specific.
Think critically
How might the 'vulnerability' factor differ across different age groups or levels of technological familiarity within the contact centre environment?
Design Principles
"User adoption of AI tools is maximized when the technology is perceived as beneficial, easy to use, enjoyable, and safe."
Understanding the drivers of user adoption is crucial for the successful integration of AI coaching tools in high-pressure work environments. Designing these tools with a focus on perceived benefits and user experience can overcome resistance and maximize their potential for improving employee performance and retention.
What This Means for Your Design
People are more likely to use a new AI tool if they think it will help them do their job better, is easy to use, and is fun. They might also be worried about how the technology could affect them.
How to use in your project
- 1.Use the findings to justify design choices that focus on user experience and perceived benefits.
- 2.Reference the study when discussing the importance of user adoption in technology implementation.
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Quick Cite
Paragraph starter
This research highlights that user adoption of AI coaching chatbots is driven by perceived performance benefits, ease of use, and hedonic motivation. Therefore, design efforts should focus on creating intuitive interfaces that clearly demonstrate value and offer an engaging user experience, while also addressing potential user vulnerabilities related to technology.
Source
Journal of Work-Applied Management
Individual propensity to use an AI coaching chatbot in the contact centre environment
journal · 2025
View sourceQuestions About This Research
- What does the research say about ai coaching chatbots: user adoption driven by performance, ease of use, and hedonic motivation?
- To encourage the adoption of AI coaching chatbots, designers must focus on making them demonstrably effective, simple to operate, and engaging for users, while also proactively mitigating fears related to technology use. Evidence: Journal of Work-Applied Management (2025).
- Why does "AI Coaching Chatbots: User Adoption Driven by Performance, Ease of Use, and Hedonic Motivation" matter for design?
- Understanding the drivers of user adoption is crucial for the successful integration of AI coaching tools in high-pressure work environments. Designing these tools with a focus on perceived benefits and user experience can overcome resistance and maximize their potential for improving employee performance and retention.
- How can designers apply this research?
- To encourage the adoption of AI coaching chatbots, designers must focus on making them demonstrably effective, simple to operate, and engaging for users, while also proactively mitigating fears related to technology use.
- What were the main findings?
- Performance expectancy (belief that the chatbot will improve performance) directly influences intention to use.. Effort expectancy (belief that the chatbot is easy to use) directly influences intention to use.. Hedonic motivation (enjoyment derived from using the chatbot) directly influences intention to use.. Vulnerability (fear of negative impacts from technology) influences intention to use.
- What research method was used?
- Quantitative survey analysis using a modified technology acceptance model. with 139 participants.
- How strong is the evidence?
- Evidence strength is rated Strong effect, based on a 2025 journal from Journal of Work-Applied Management.
- What should I do differently in my next project?
- When developing or implementing AI coaching tools, conduct user research to understand perceptions of performance benefits, usability, and enjoyment. Design training and communication strategies that highlight these aspects and address potential user anxieties.
- What are the limitations?
- The study's findings are based on a single cross-sectional survey, which may not capture long-term adoption trends or causal relationships definitively. The specific context of contact centres might limit generalizability to other industries without further research.