Managerial AI Adoption Hinges on Perceptions, Ethics, and Organizational Context

Why It Matters

Understanding these multifaceted factors is crucial for designers and developers creating AI tools for managerial use. It highlights that technical functionality alone is insufficient; the human element, organizational environment, and ethical implications must be proactively addressed to ensure adoption and effective utilization.

Key Finding

The adoption of AI by managers is a complex process influenced by how managers feel about AI, ethical considerations, their personal psychology, social influences, the organization's environment, external factors, and the AI's technical design.

Key Findings

• Managers' perceptions of AI (usefulness, ease of use, trust) are critical.
• Ethical concerns (bias, transparency, accountability) pose significant barriers.
• Individual psychological factors (risk aversion, cognitive biases) and social/psychosocial factors (peer influence, organizational culture) play a role.
• Organizational factors (support, training, infrastructure) and external pressures (market, regulation) impact adoption.
• Technical and design characteristics of AI systems (usability, reliability, integration) are fundamental.

Research Evidence

Aim: What are the key facilitators and barriers influencing managers' adoption of AI-based systems in their decision-making processes?

Method: Systematic Literature Review

Procedure: A systematic review was conducted following PRISMA guidelines, searching the Scopus database for articles published between 2010 and 2024 using specific keywords. Eligible studies underwent rigorous screening and quality assessment before data synthesis.

Sample Size: 16 eligible studies synthesized from 202 screened articles

Context: Managerial decision-making within organizations

Design Principle

Design AI systems with a holistic approach, considering user psychology, organizational context, and ethical implications alongside technical functionality.

How to Apply

When designing AI decision-support tools for managers, conduct thorough user research to understand their existing perceptions, concerns, and workflows. Develop clear ethical guidelines and ensure the AI's design promotes transparency and accountability.

Limitations

The review is based on existing literature, which may have its own biases or gaps. The specific context of AI adoption can vary greatly across industries and organizations.

Student Guide (IB Design Technology)

Simple Explanation: For managers to use new AI tools for making decisions, they need to feel good about them, trust them, and think they are ethical. The company also needs to be ready for the AI, and the AI itself needs to work well and be easy to use.

Why This Matters: This research helps understand why people might or might not use a new technology, which is vital for designing products that people will actually want to use and that will be successful.

Critical Thinking: How might the relative importance of these seven factors shift depending on the specific industry, the type of decision being made, or the maturity of AI integration within an organization?

IA-Ready Paragraph: The adoption of AI in managerial decision-making is not solely a technical challenge but is deeply intertwined with human factors and organizational context. Research indicates that managerial perceptions of AI, ethical considerations, individual psychological traits, social dynamics, organizational readiness, external pressures, and the technical design of AI systems collectively act as significant facilitators or barriers to adoption. Therefore, any design project aiming to integrate AI into managerial workflows must proactively address these multifaceted influences to ensure successful implementation and user acceptance.

Project Tips

• When researching a new product, consider how users will perceive its technology and any ethical concerns.
• Investigate the organizational context and social factors that might affect adoption.
• Focus on user experience and usability as key design drivers.

How to Use in IA

• Reference this study when discussing the importance of user perception, ethical considerations, and organizational factors in the adoption of a new design or technology.
• Use the identified factors as a framework for analysing potential barriers and facilitators for your own design project.

Examiner Tips

• Demonstrate an understanding of the human factors and contextual elements that influence the success of technological adoption, not just the technical merits of a design.
• Critically evaluate how your design addresses potential user skepticism and ethical considerations.

Independent Variable: ["Managers' Perceptions of AI","Ethical Factors","Psychological and Individual Factors","Social and Psychosocial Factors","Organizational Factors","External Factors","Technical and Design Characteristics of AI"]

Dependent Variable: Managerial adoption of AI-based systems in decision making

Strengths

• Comprehensive systematic review adhering to PRISMA guidelines.
• Synthesis of findings into a structured analytical framework.
• Covers a broad range of influencing factors.

Critical Questions

• To what extent can AI truly overcome inherent human cognitive biases in decision-making, or does it merely shift the locus of bias?
• How can designers proactively mitigate ethical concerns and build trust in AI systems for sensitive managerial decisions?

Extended Essay Application

• An Extended Essay could explore the ethical design principles for AI decision-support systems in a specific managerial domain, drawing on the factors identified in this review.
• Investigate how different organizational cultures might necessitate tailored AI adoption strategies.

Source

Exploring Facilitators and Barriers to Managers’ Adoption of AI-Based Systems in Decision Making: A Systematic Review · AI · 2024 · 10.3390/ai5040123