Table 5 Future research directions 1.... | Emerald Publishing

Table 5

Future research directions

1. Strategic priorities	Employee experience: Exploring impacts of AI-enabled HRM on employee experiences, engagement, and motivation through approaches such as personalized feedback and career development strategies (Silic et al., 2020; Malik et al., 2023). Further, extension of studies on gamification in employee satisfaction across industries Organizational culture: Explore the role of organizational culture in successful digitalization of HR and strategies to build a technology-conducive culture. Limited studies show positive effects of digital culture on AI-supported leadership and supply chain digitalization (Rožman et al., 2023; Kolmykova et al., 2022) Implementation challenges: Focus on SMEs’ barriers to adoption of AI-enabled HR, emphasizing organizational practices and employee digital capabilities (Hansen et al., 2024; Wang et al., 2024)
2. Technical considerations	AI Integration: Investigate AI’s role in automating HR functions like recruitment, onboarding, and performance management. Explore its complementarity with human expertise for soft skills assessment (Zheng et al., 2024; Zavyalova et al., 2022) Data Privacy: Analyze ethical and legal frameworks for acquisition, storage, and utilization of employee data, ensuring fairness and compliance. Effective cybersecurity is seen in combining AI with human intervention (Thite and Iyer, 2024) Cybersecurity: Explore the dual roles of AI and human expertise in safeguarding digital HR systems against threats
3. Human impact	Workforce Diversity: Study AI’s potential to reduce biases and promote inclusivity in hiring, particularly for neurodiverse individuals. For example, DXC Technology recruits’ autistic individuals for cybersecurity and data analysis roles (Carrero et al., 2019) Employee Wellbeing: Evaluate digital HR tools for supporting mental health through telehealth and virtual wellness programs. Explore further potential of AI to detect stress and burnout symptoms, enabling early interventions (Fan et al., 2023) Skill Development: Investigate the need to upskill HR professionals to effectively collaborate with AI systems and address workforce adaptability challenges
4. Ethical framework	Bias Mitigation: Examine strategies to prevent AI from replicating human biases, particularly in recruitment (Kelan, 2023). For example: Possibility of integrating AI’s cognitive assessments with human evaluations for better insights about emotional intelligence metrics Privacy Protection: Address ethical concerns in AI-powered monitoring and decision-making systems, ensuring transparency and employee trust Fairness in AI Systems: Investigate frameworks for fairness in AI algorithms to ensure equitable recruitment and employee evaluations (Rigotti and Fosch-Villaronga, 2024)

1. Strategic priorities	Employee experience: Exploring impacts of AI-enabled HRM on employee experiences, engagement, and motivation through approaches such as personalized feedback and career development strategies (Silic et al., 2020; Malik et al., 2023). Further, extension of studies on gamification in employee satisfaction across industriesOrganizational culture: Explore the role of organizational culture in successful digitalization of HR and strategies to build a technology-conducive culture. Limited studies show positive effects of digital culture on AI-supported leadership and supply chain digitalization (Rožman et al., 2023; Kolmykova et al., 2022)Implementation challenges: Focus on SMEs’ barriers to adoption of AI-enabled HR, emphasizing organizational practices and employee digital capabilities (Hansen et al., 2024; Wang et al., 2024)
2. Technical considerations	AI Integration: Investigate AI’s role in automating HR functions like recruitment, onboarding, and performance management. Explore its complementarity with human expertise for soft skills assessment (Zheng et al., 2024; Zavyalova et al., 2022)Data Privacy: Analyze ethical and legal frameworks for acquisition, storage, and utilization of employee data, ensuring fairness and compliance. Effective cybersecurity is seen in combining AI with human intervention (Thite and Iyer, 2024)Cybersecurity: Explore the dual roles of AI and human expertise in safeguarding digital HR systems against threats
3. Human impact	Workforce Diversity: Study AI’s potential to reduce biases and promote inclusivity in hiring, particularly for neurodiverse individuals. For example, DXC Technology recruits’ autistic individuals for cybersecurity and data analysis roles (Carrero et al., 2019)Employee Wellbeing: Evaluate digital HR tools for supporting mental health through telehealth and virtual wellness programs. Explore further potential of AI to detect stress and burnout symptoms, enabling early interventions (Fan et al., 2023)Skill Development: Investigate the need to upskill HR professionals to effectively collaborate with AI systems and address workforce adaptability challenges
4. Ethical framework	Bias Mitigation: Examine strategies to prevent AI from replicating human biases, particularly in recruitment (Kelan, 2023). For example: Possibility of integrating AI’s cognitive assessments with human evaluations for better insights about emotional intelligence metricsPrivacy Protection: Address ethical concerns in AI-powered monitoring and decision-making systems, ensuring transparency and employee trustFairness in AI Systems: Investigate frameworks for fairness in AI algorithms to ensure equitable recruitment and employee evaluations (Rigotti and Fosch-Villaronga, 2024)

Source(s): Authors’ own creation