Short answer
Prioritize the integration of social and human factors into the AI design and implementation process, alongside economic and technical considerations, to mitigate adoption barriers and ensure responsible innovation.
- Field
- Innovation & Design
- Source
- Technology in Society (2020)
- Method
- Tertiary study based on systematic literature reviews.
- Evidence
- Moderate effect
While economic benefits are primary drivers for AI adoption in business, significant barriers exist due to technical limitations and crucial social considerations like job security and trust. This innovation & design research insight is drawn from a 2020 study published in Technology in Society. Using Tertiary study based on systematic literature reviews., researchers explored how this design variable affects real-world outcomes. The key design takeaway: Prioritize the integration of social and human factors into the AI design and implementation process, alongside economic and technical considerations, to mitigate adoption barriers and ensure responsible innovation.
AI Adoption in Business: Economic Drivers vs. Social Barriers
While economic benefits are primary drivers for AI adoption in business, significant barriers exist due to technical limitations and crucial social considerations like job security and trust.
Technology in Society · 2020
Key Findings
- 01Economic benefits are the main drivers for AI adoption.
- 02Barriers include technical aspects (data availability, model reusability) and social considerations (job security, trust, knowledge gaps, dependence on non-humans).
- 03Few reviews adequately address human, organizational, and societal factors outside of healthcare management.
- 04There's a recommendation for increased focus on social aspects, rigorous evaluation, hybrid approaches, and multidisciplinary collaboration in AI design and implementation.
- 05Lack of systematic reviews in early adopter sectors like finance and retail, with existing reviews not sufficiently addressing human/societal implications.
Application
Design takeaway
Prioritize the integration of social and human factors into the AI design and implementation process, alongside economic and technical considerations, to mitigate adoption barriers and ensure responsible innovation.
How to apply
When developing AI-driven products or services for business, conduct thorough user research that includes understanding potential job impacts, building trust mechanisms, and engaging with diverse stakeholder groups.
Project actions
- 01When researching AI adoption, look beyond just the technical feasibility and economic benefits.
- 02Consider the ethical implications and potential societal impacts of your design choices.
- 03Involve diverse user groups in your research to capture a wider range of perspectives and concerns.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Provides a broad overview of AI adoption factors across multiple business domains.
- +Synthesizes findings from numerous systematic reviews, offering a comprehensive perspective.
Limitations
The findings are based on a synthesis of existing literature, and the specific context of your design project might introduce unique drivers or barriers not covered in the reviewed studies.
Reliability & validity
The reliability of the findings is enhanced by synthesizing multiple systematic reviews. Validity is supported by the breadth of industries and functions covered, though specific industry nuances might be generalized.
Think critically
To what extent do the 'social considerations' identified in this study represent universal challenges, and how might they vary significantly across different cultural contexts or specific industry sectors?
Design Principles
"Human-centric AI development requires a holistic approach that balances technological advancement with social well-being and stakeholder engagement."
Understanding these drivers and barriers is essential for successful AI integration. Designers and strategists must balance the pursuit of economic efficiency with the human and societal impacts to ensure responsible and effective implementation.
What This Means for Your Design
Companies want to use AI to make more money, but people worry about losing jobs, not trusting the AI, and not understanding it. We need to think about these worries when we build AI for businesses.
How to use in your project
- 1.Use this research to justify the inclusion of user-centered design principles and ethical considerations in your design process, especially when dealing with AI or automation.
- 2.Cite this study when discussing the challenges and opportunities of implementing new technologies in a business context.
Add to My Project
Quick Cite
Paragraph starter
This research highlights that while economic incentives drive AI adoption in business, significant social considerations such as job security, trust, and knowledge gaps act as substantial barriers. Therefore, any design project involving AI must proactively address these human and societal factors to ensure successful integration and user acceptance.
Source
Technology in Society
Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study
journal · 2020
View sourceQuestions About This Research
- What does the research say about ai adoption in business: economic drivers vs. social barriers?
- Prioritize the integration of social and human factors into the AI design and implementation process, alongside economic and technical considerations, to mitigate adoption barriers and ensure responsible innovation. Evidence: Technology in Society (2020).
- Why does "AI Adoption in Business: Economic Drivers vs. Social Barriers" matter for design?
- Understanding these drivers and barriers is essential for successful AI integration. Designers and strategists must balance the pursuit of economic efficiency with the human and societal impacts to ensure responsible and effective implementation.
- How can designers apply this research?
- Prioritize the integration of social and human factors into the AI design and implementation process, alongside economic and technical considerations, to mitigate adoption barriers and ensure responsible innovation.
- What were the main findings?
- Economic benefits are the main drivers for AI adoption.. Barriers include technical aspects (data availability, model reusability) and social considerations (job security, trust, knowledge gaps, dependence on non-humans).. Few reviews adequately address human, organizational, and societal factors outside of healthcare management.. There's a recommendation for increased focus on social aspects, rigorous evaluation, hybrid approaches, and multidisciplinary collaboration in AI design and implementation.
- What research method was used?
- Tertiary study based on systematic literature reviews..
- How strong is the evidence?
- Evidence strength is rated Moderate effect, based on a 2020 journal from Technology in Society.
- What should I do differently in my next project?
- When developing AI-driven products or services for business, conduct thorough user research that includes understanding potential job impacts, building trust mechanisms, and engaging with diverse stakeholder groups.
- What are the limitations?
- The study is based on existing systematic reviews, meaning its findings are limited by the scope and quality of the original reviews. There's a noted lack of comprehensive reviews in certain key industries.