Leveraging Artificial Intelligence for Sustainable Human Resource Management: Advancing Green HRM Practices

 

Artificial Intelligence

Artificial Intelligence (AI) is a branch of computer science that enables machines to perform tasks that normally require human intelligence. These tasks include learning, reasoning, problem-solving, and decision-making. AI systems use algorithms and data to recognize patterns, predict outcomes, and make automated decisions. It encompasses technologies such as machine learning, natural language processing, and robotics. AI can process large volumes of data faster and more accurately than humans. It is widely applied in industries like healthcare, finance, education, and HR. By mimicking human cognitive functions, AI helps organizations improve efficiency, reduce errors, and innovate processes (Russell & Norvig, 2021).

Branches of AI

• Expert Systems: Simulate human decision-making for complex problems, used in healthcare and banking (Tan et al., 2016).
• Machine Learning (ML): Machines learn from historical data to predict outcomes; applied in finance, HR, healthcare, education, and robotics.
• Robotics: Develops robots to perform repetitive or physical tasks efficiently (Alattas et al., 2019).
• Natural Language Processing (NLP): Enables machines to understand and interpret human language, used for text analysis and insights from large datasets (Chowdhary et al., 2019).
• Planning: Supports strategic decision-making by outlining steps to achieve desired outcomes (Luketina et al., 2023).

Sustainable Human Resource Management

Sustainable HRM refers to the adoption of human resource practices that align HR functions with long-term environmental, social, and organizational sustainability goals. Under this concept, HR activities such as recruitment, training, performance appraisal, compensation, and employee engagement are redesigned to promote eco‑friendly behaviour, resource efficiency and social responsibility instead of focusing solely on short‑term profit or administrative functions (Dilrukshi & Aluthge, 2024; Gazi et al., 2024). Evidence suggests that implementing sustainable HRM improves employee commitment, encourages pro‑environmental behaviours, and enhances organizational performance along multiple dimensions  such as economic, environmental and social (Rehman et al., 2025). Thus, Sustainable HRM transforms HR from a purely administrative role into a strategic driver for achieving the triple bottom line, balancing people, planet and profit in a holistic manner.

Green Human Resource Management

Green Human Resource Management (GHRM) refers to the integration of environmental management into human resource practices to promote sustainability within organizations (Renwick et al., 2013; Gomes et al., 2023). It involves adopting eco-friendly policies and procedures across the employee life cycle, including recruitment, training, performance management, rewards, and employee engagement. The primary goal of GHRM is to create a workforce that is aware of environmental issues and actively contributes to organizational sustainability objectives while maintaining productivity and employee well-being.

Types of AI in Human Resource Management

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AI-Enabled Tools for Green HRM Practices

AI-Powered Recruitment Tools

AI has transformed recruitment in Green HRM by reducing paper usage, streamlining hiring processes, and identifying candidates who align with sustainability values. Companies are increasingly adopting AI-based recruitment solutions to make hiring more efficient and eco- friendly. HireVue, for instance, uses AI to evaluate video interviews, analyze candidate responses, and shortlist the most suitable applicants, eliminating the need for multiple in-person interviews and printed applications. X0PA AI employs predictive analytics to assess candidate potential and cultural fit, helping organizations hire efficiently while supporting environmentally conscious recruitment practices. These tools allow HR departments to make data-driven decisions while minimizing environmental impact.

Learning and Development Platforms

AI-driven learning platforms enhance employee development in a sustainable manner by providing digital and personalized training solutions. These platforms reduce the need for printed materials, in-person sessions, and travel. Coursera for Business uses AI to create tailored learning paths, recommending courses based on employee skill gaps and career goals. EdApp leverages AI to track employee progress, deliver microlearning modules, and provide feedback, ensuring continuous learning with minimal environmental footprint. Organizations such as Unilever and IBM utilize these platforms to upskill employees in sustainable practices while reducing resource consumption.

Performance Management and Analytics Tools

Monitoring employee performance and sustainability outcomes is crucial for Green HRM. AI-powered analytics tools help HR departments track productivity, engagement, and eco-friendly practices. Workday HCM integrates AI to provide predictive insights into employee performance, engagement, and workforce planning, enabling organizations to align HR strategy with sustainability objectives. SAP SuccessFactors leverages AI for performance evaluation, identifying areas where sustainability initiatives can be improved and rewarding employees for green behavior. Multinational companies like Microsoft and Siemens use these tools to integrate sustainability KPIs into their performance management systems.

Employee Engagement and Collaboration Tools

Engaging employees in sustainability initiatives is critical for a successful Green HRM strategy. AI tools enhance engagement by automating communication, tracking participation, and promoting eco-friendly practices. Peakon (Workday) uses AI-driven surveys and sentiment analysis to measure employee engagement, identify barriers to green initiatives, and provide actionable insights. Collaboration platforms like Slack, when integrated with AI bots, automate reminders for eco-friendly programs, encourage participation in sustainability challenges, and foster a green organizational culture. Companies like Google and Deloitte have leveraged such AI tools to boost employee awareness and involvement in environmental programs.

Payroll and Administrative Automation

AI automation reduces manual paperwork and administrative tasks, contributing to environmentally friendly HR operations. Platforms like ADP Workforce Now utilize AI to manage payroll, attendance, and time-off requests automatically, reducing paper use and administrative workload. Zoho People employs AI to track leaves, performance, and HR records digitally, minimizing reliance on physical resources. Organizations such as Accenture and Infosys have implemented these tools to enhance efficiency while supporting green HRM objectives.

AI for Green Policy and Sustainability Reporting

Sustainability reporting is a critical aspect of Green HRM, and AI simplifies the collection, analysis, and reporting of environmental data. Tools like Persefoni provide AI-driven carbon footprint analysis, helping organizations track the environmental impact of HR operations. Sustainalytics uses AI to monitor ESG performance, evaluate HR sustainability programs, and generate actionable insights. Companies like Nestlé and Coca-Cola use these AI solutions to maintain transparency, track progress, and meet sustainability goals across human resource activities.

Chatbots for Employee Support

AI-powered chatbots support employees while reducing the need for resource-intensive HR processes. IBM Watson Assistant provides instant responses to HR queries, including information about green policies and eco-friendly practices, reducing the need for printed manuals and in-person support. Leena AI automates HR helpdesk tasks, guides employees on sustainability programs, and ensures quick, eco-friendly support. Global organizations such as HSBC and PwC have successfully implemented chatbots to streamline employee support and promote green HR initiatives.

 

Benefits of AI Tools in Green HRM

Artificial Intelligence (AI) tools provide significant benefits for Green Human Resource Management (GHRM) by enhancing sustainability, efficiency, and employee engagement. AI improves recruitment by automating candidate screening, reducing manual paperwork, and enabling eco-friendly hiring practices (Bohr & Memarzadeh, 2020; Noonan, 2018). AI-driven learning platforms facilitate digital training and skill development, minimizing travel and printed materials while promoting sustainable HR practices (Noor, Khan & Abbas, 2023). Performance management and analytics tools help organizations monitor sustainability KPIs, reward environmentally conscious behavior, and align HR strategies with green objectives (Tursunbayeva & Renkema, 2023). AI also strengthens employee engagement by using intelligent systems to track participation in green initiatives and provide timely feedback (Hou, Du & Xu, 2023). Additionally, AI-supported administrative automation reduces resource-intensive tasks, streamlines HR workflows, and improves operational efficiency (Brougham & Haar, 2018). Finally, AI assists in sustainability reporting by analyzing HR-related environmental impacts, tracking organizational carbon footprints, and supporting decision-making for green policies (Shrestha, Ben-Menahem & von Krogh, 2020). Overall, integrating AI into GHRM enhances organizational sustainability while improving employee productivity, engagement, and well-being.

 

Limitation of AI in Green HRM

While Artificial Intelligence (AI) offers significant advantages for Green Human Resource Management (GHRM), several challenges and limitations must be considered. First, the adoption of AI can lead to job displacement or transformation, as automated processes may replace certain routine HR tasks, raising concerns about employee morale and reskilling needs (Frank et al., 2019; Brougham & Haar, 2018). Second, the implementation of AI tools often requires substantial financial investment and technological infrastructure, which can be a barrier for smaller organizations (Tursunbayeva & Renkema, 2023). Third, AI systems are only as effective as the data they are trained on; biases in data can lead to unfair hiring, performance evaluation, or decision-making, potentially undermining equity in green HR practices (Binns, 2018; Hou et al., 2023). Additionally, ethical and privacy concerns arise from extensive employee monitoring and data collection, which can conflict with organizational policies and employee trust (Shrestha et al., 2020). Finally, integrating AI with existing HR systems and aligning it with sustainability goals can be complex, requiring specialized knowledge and ongoing maintenance (Noor et al., 2023). These challenges indicate that while AI can enhance GHRM, careful planning, ethical oversight, and employee involvement are essential to ensure successful and sustainable implementation.

 Overcoming   Limitations of AI in Green HRM

To overcome the challenges associated with implementing AI in Green Human Resource Management (GHRM), organizations must adopt strategic, ethical, and inclusive approaches. First, the risk of job displacement can be mitigated by upskilling and reskilling employees, enabling them to work alongside AI tools rather than being replaced (Frank et al., 2019; Brougham & Haar, 2018). Second, organizations should conduct careful cost-benefit analyses and explore scalable AI solutions suitable for their size, ensuring financial feasibility and effective infrastructure deployment (Tursunbayeva & Renkema, 2023). Third, addressing data bias requires implementing transparent AI algorithms, continuous auditing of datasets, and integrating fairness checks to promote equitable decision-making in recruitment, performance evaluation, and employee engagement (Binns, 2018; Hou, Du & Xu, 2023). Ethical and privacy concerns can be managed by establishing clear data governance policies, informed consent protocols, and transparency in AI usage, thereby maintaining employee trust (Shrestha, Ben-Menahem & von Krogh, 2020). Finally, successful integration of AI with HR systems and sustainability objectives demands continuous training, collaboration between HR and IT experts, and the adoption of standardized frameworks to align AI initiatives with organizational green goals (Noor, Khan & Abbas, 2023). By combining technological investment with ethical oversight, workforce development, and strategic planning, organizations can maximize the benefits of AI while minimizing its risks, ensuring the effective and sustainable implementation of Green HRM.

Ethics in AI usage in Green HRM

The ethical use of AI in Green Human Resource Management (GHRM) is crucial to ensure that sustainability initiatives do not compromise employee rights or fairness. AI systems in GHRM may monitor employee behaviors, participation in eco-friendly practices, or resource usage, which can lead to privacy concerns if employees feel excessively tracked. Additionally, biased algorithms could unfairly favor or penalize certain employees, affecting recognition, promotions, or rewards linked to green initiatives. Ethical implementation requires transparency about data collection and usage, ensuring consent and confidentiality, and combining AI insights with human judgment to prevent unfair treatment. Maintaining accountability, fairness, and respect for employee autonomy is essential for building trust and sustaining engagement in GHRM practices (Opatha & Arulrajah, 2023).

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References

Binns, R. (2018) Fairness in Machine Learning: Lessons from Political Philosophy, Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency, pp. 149–159.

Bohr, A. & Memarzadeh, K. (2020) The rise of artificial intelligence in human resources management, Journal of Business Research, 123, pp. 229–237.

Brougham, D. & Haar, J. (2018) Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace, Journal of Management & Organization, 24(2), pp. 239–257.

Frank, M.R., Autor, D., Bessen, J.E., et al. (2019) Toward understanding the impact of AI on labor, Proceedings of the National Academy of Sciences, 116(14), pp. 6531–6539.

Hou, J., Du, J. & Xu, Y. (2023) AI applications in HR and employee decision-making, International Journal of Human Resource Studies, 13(1), pp. 45–61.

Noonan, M. (2018) Artificial Intelligence in Banking and HR Applications, International Journal of Banking Technology, 5(2), pp. 12–25.

Noor, M.I., Khan, S. & Abbas, T. (2023) Artificial Intelligence and Sustainable HR Practices, Journal of Entrepreneurship, Management and Innovation, 6(1), pp. 63–79.

Russell, S. & Norvig, P. (2021) Artificial Intelligence: A Modern Approach, 4th edn. Pearson.

Shrestha, Y.R., Ben-Menahem, S.M. & von Krogh, G. (2020) Organizational Decision-Making Structures in the Age of Artificial Intelligence, California Management Review, 62(4), pp. 66–83.

Tursunbayeva, A. & Renkema, T. (2023) Artificial Intelligence in Human Resource Management: Benefits, Challenges and Ethical Considerations, Human Resource Management Review, 33(2), 100862.