The Role of Artificial Intelligence in Building Patient Trust in Healthcare Settings
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By
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Sara L Jackson
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August 21, 2026
Clinical Report: The Role of Artificial Intelligence in Building Patient Trust
Background
The integration of AI in healthcare is rapidly evolving, necessitating an understanding of patient perceptions and trust. Trust is crucial for effective clinician-patient relationships and influences patient engagement with AI technologies. Addressing patient concerns is essential for the successful adoption of AI in clinical settings.
Data Highlights
No numerical data available in the source material.
Key Findings
- Patients express concerns about privacy and data security related to AI applications.
- The complexity of AI decision-making processes raises issues of transparency and accountability.
- There is a potential for AI to negatively impact clinician-patient relationships and trust.
- Ethical considerations and fair access to AI technologies are significant societal concerns.
Clinical Implications
Clinicians should prioritize transparency and patient consent when implementing AI technologies in practice. Addressing patient concerns about AI can help maintain trust and improve the therapeutic relationship.
Conclusion
Understanding and addressing patient concerns about AI is vital for fostering trust and ensuring the successful integration of AI in healthcare.
Related Resources & Content
- Hou J, Zhang Z, Cheng X, Wang W, J Med Internet Res, 2026 -- Patient concerns regarding artificial intelligence applications in health care: systematic review and meta-synthesis based on social ecological theory
- Delbanco T, Walker J, Darer JD, et al., Ann Intern Med, 2010 -- Open notes: doctors and patients signing on
- Salmi L, Lewis DM, Clarke JL, et al., JAMIA Open, 2025 -- A proof-of-concept study for patient use of open notes with large language models
- aace endocrine ai — Medical AI: What shapes patient trust?
- Frontiers in Digital Health — Stakeholder experience with artificial intelligence in healthcare: a bibliometric study of satisfaction, trust, acceptance, and patient engagement
- aace endocrine ai — Why we all belong in the AI conversation
- Medical AI: What shapes patient trust?
- Stakeholder experience with artificial intelligence in healthcare: a bibliometric study of satisfaction, trust, acceptance, and patient engagement
- Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions | FDA
- Patient Concerns Regarding Artificial Intelligence Applications in Health Care: Systematic Review and Meta-Synthesis Based on Social Ecological Theory - PMC
- 2026 RFS Annual Meeting Handbook | AMA
Based on findings from:
AI and Patient Trust in Health Care
Sara L Jackson. Journal Of Medical Internet Research, 2026.
https://www.jmir.org/2026/1/e104760
This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.
