Table 5. GenAI Social impact framework:... | Emerald Publishing

Table 5.

GenAI Social impact framework: well-being risks

Well-being risks	Patient	Professional	Organization
Ethical and legal concerns	Privacy concerns= patients may experience concerns about privacy and the need for greater protection of personal data (A: Sidaoui et al., 2024; P: Capgemini, 2024)	Concerns about professional liability= ethical risks include the potential for misuse of GenAI and concerns about professional liability for healthcare providers and other legal and ethical considerations (A: Wubineh et al., 2024; P: Deloitte, 2024)	Data privacy and bias concerns= ethical concerns arise from data privacy issues, the potential for bias in GenAI algorithms (A: Aldwean and Tenney, 2024; P: European Parliament, 2022) Accountability and transparency concerns= concerns arise regarding ensuring accountability and transparency in GenAI decision-making processes (A: Belanche et al., 2024; P: VSP Global Innovation Center, 2024)
Reluctance and stress	Resistance to AI-enabled care= patients may experience a perceived risk using GenAI in medicine and demonstrate resistance to GenAI-based healthcare services (A: Longoni et al., 2019; P: Brillio, 2024)	Questions about accuracy of AI-enabled advices= the reliability of information provided by GenAI may be questionable, raising concerns about the accuracy of AI-generated advice and recommendations (A: Pasca and Arcese, 2024; P: EXL, 2024) Discomfort about AI-enabled diagnoses= GenAI could cause discomfort in relying on GenAI for diagnoses and reduce trust in GenAI diagnostics (A: Belanche et al., 2024; P: GAO, 2024) Mental strains= GenAI may contribute to increased stress and anxiety among healthcare workers (A: Irgang et al., 2025; Le and Cayrat, 2024)	Risk for AI-disfavoring culture= cultural and personnel factors may hinder AI implementation (A: Huang and Rust, 2024; P: Deloitte, 2024) Unpreparedness for introduction= healthcare organizations may face financial barriers related to the cost of GenAI infrastructure and implementation, encounter high costs and risks associated with GenAI, and experience implementation barriers in realistic settings (A: Kulkov, 2023; P: EXL, 2024) Integration and interoperability issues= data integration and interoperability issues with existing systems (A: Shah et al., 2024; P: Deloitte, 2024) Regulatory and policy barriers = regulatory and political obstacles hinder the introduction of GenAI (A: Afjal, 2024; P: GAO, 2024)
Altering healthcare jobs	Dehumanized care experience= patients may experience a lack of empathy and human interaction when using GenAI (A: Belanche et al.., 2024; P: Capgemini, 2024)	Job insecurity= GenAI may lead to job displacement and insecurity among healthcare professionals (A: Huang and Rust, 2018; P: Deloitte, 2024)	Demand for new skills= cultural and personnel factors may create a need for interdisciplinary skills, leadership in technology adoption, effective management of external expertise, and integration of processes and strategy (A: Pham et al., 2024; P: Bain and Company, 2025)
Taking over decision-making	Fear of overreliance on AI= GenAI could lead to the deskilling of physicians, and result in overreliance on GenAI, diminishing independent thinking (A: Kannelønning, 2024; P: Nomura Research Institute, 2024)	Restrained autonomy for professionals= GenAI tools might limit healthcare professionals’ ability to make independent decisions and exercise their judgment (A: Tursunbayeva and Renkema, 2023)	Lack of a critical approach= healthcare organizations may face risks related to supplier opportunism, encounter fragmented GenAI research and application efforts, and lack essential infrastructure and capabilities for successful GenAI implementation (A: Meyer et al., 2024; P: Capgemini, 2024) Standardization= AI tools might standardize processes and protocols, resulting in a lack of possibilities to react to unforeseen events in the process (A: Grigsby et al., 2025; Tursunbayeva and Renkema, 2023)

Well-being risks	Patient	Professional	Organization
Ethical and legal concerns	Privacy concerns= patients may experience concerns about privacy and the need for greater protection of personal data (A: Sidaoui et al., 2024; P: Capgemini, 2024)	Concerns about professional liability= ethical risks include the potential for misuse of GenAI and concerns about professional liability for healthcare providers and other legal and ethical considerations (A: Wubineh et al., 2024; P: Deloitte, 2024)	Data privacy and bias concerns= ethical concerns arise from data privacy issues, the potential for bias in GenAI algorithms (A: Aldwean and Tenney, 2024; P: European Parliament, 2022) Accountability and transparency concerns= concerns arise regarding ensuring accountability and transparency in GenAI decision-making processes (A: Belanche et al., 2024; P: VSP Global Innovation Center, 2024)
Reluctance and stress	Resistance to AI-enabled care= patients may experience a perceived risk using GenAI in medicine and demonstrate resistance to GenAI-based healthcare services (A: Longoni et al., 2019; P: Brillio, 2024)	Questions about accuracy of AI-enabled advices= the reliability of information provided by GenAI may be questionable, raising concerns about the accuracy of AI-generated advice and recommendations (A: Pasca and Arcese, 2024; P: EXL, 2024) Discomfort about AI-enabled diagnoses= GenAI could cause discomfort in relying on GenAI for diagnoses and reduce trust in GenAI diagnostics (A: Belanche et al., 2024; P: GAO, 2024) Mental strains= GenAI may contribute to increased stress and anxiety among healthcare workers (A: Irgang et al., 2025; Le and Cayrat, 2024)	Risk for AI-disfavoring culture= cultural and personnel factors may hinder AI implementation (A: Huang and Rust, 2024; P: Deloitte, 2024) Unpreparedness for introduction= healthcare organizations may face financial barriers related to the cost of GenAI infrastructure and implementation, encounter high costs and risks associated with GenAI, and experience implementation barriers in realistic settings (A: Kulkov, 2023; P: EXL, 2024) Integration and interoperability issues= data integration and interoperability issues with existing systems (A: Shah et al., 2024; P: Deloitte, 2024) Regulatory and policy barriers = regulatory and political obstacles hinder the introduction of GenAI (A: Afjal, 2024; P: GAO, 2024)
Altering healthcare jobs	Dehumanized care experience= patients may experience a lack of empathy and human interaction when using GenAI (A: Belanche et al.., 2024; P: Capgemini, 2024)	Job insecurity= GenAI may lead to job displacement and insecurity among healthcare professionals (A: Huang and Rust, 2018; P: Deloitte, 2024)	Demand for new skills= cultural and personnel factors may create a need for interdisciplinary skills, leadership in technology adoption, effective management of external expertise, and integration of processes and strategy (A: Pham et al., 2024; P: Bain and Company, 2025)
Taking over decision-making	Fear of overreliance on AI= GenAI could lead to the deskilling of physicians, and result in overreliance on GenAI, diminishing independent thinking (A: Kannelønning, 2024; P: Nomura Research Institute, 2024)	Restrained autonomy for professionals= GenAI tools might limit healthcare professionals’ ability to make independent decisions and exercise their judgment (A: Tursunbayeva and Renkema, 2023)	Lack of a critical approach= healthcare organizations may face risks related to supplier opportunism, encounter fragmented GenAI research and application efforts, and lack essential infrastructure and capabilities for successful GenAI implementation (A: Meyer et al., 2024; P: Capgemini, 2024) Standardization= AI tools might standardize processes and protocols, resulting in a lack of possibilities to react to unforeseen events in the process (A: Grigsby et al., 2025; Tursunbayeva and Renkema, 2023)

Note(s):

A = illustrative references to academic articles; P = illustrative references to practitioner publications from business or governments

Source(s): Authors’ own work