Cyber security challenges in human resource technology: protecting employee data in the digital age

Abstract

In the age of digital revolution, Human Resource Technology (HRTech) has emerged as a key facilitator for organizations to automate hiring, on boarding, payroll, employee management, performance management, and workforce analytics. Yet, the growing adoption of digital platforms, cloud computing, and data-based decision- making in (HRM) brings along substantial cyber security threats. These are due to the private and sensitive nature of worker information, such as personally identifiable information (PII), financial data, health information, background reports, and performance histories, which make HR systems potential targets for cyber attackers, This review critically examines the integration of Artificial Intelligence (AI) into Human Resource (HR) systems and its implications for cyber security. As organizations accelerate their digital transformation journeys, HR systems are increasingly responsible for storing and managing large volumes of sensitive employee data, necessitating robust cyber security frameworks. The study focuses on identifying key cyber security risks, evaluating AI-based security solutions, and assessing their effectiveness in protecting employee information such as salaries, performance evaluations, and personal identifiers.

With the spread of remote work and mobile access to HR systems, endpoint security is now more difficult to control. Moreover, applications of artificial intelligence (AI) and machine learning (ML) in hiring and employee monitoring raise ethical issues and new attack surfaces, including algorithm manipulation and data poisoning.

Sources were chosen for relevance to AI use in HR systems, their contributions to cyber security, and empirical information regarding threats and countermeasures. The review points out the convergence of HR management and information security, listing primary challenges and best practices for protecting data in modern organizational environments.

Findings reveal that while AI significantly enhances anomaly detection and automates security responses, it simultaneously introduces new risks, including AI-driven attacks and algorithmic biases. Notable solutions include AI-enabled encryption, behavioral threat detection, and AI-powered security training simulations. The dual-edged nature of AI underscores the need for adaptive security frameworks that evolve alongside emerging technologies. For HR professionals, embracing AI-based security tools offers a proactive approach to data protection, but it also demands a re-evaluation of traditional cyber security strategies. The paper further recommends that policymakers consider stringent, AI-focused regulations to address the unique threats posed by intelligent systems. Ultimately, the study advocates for a forward-looking, aggressive cyber security strategy to ensure the resilience and trustworthiness of HR technologies.

The abstract also highlights the need to implement a strong cybersecurity practice within HRTech environments. This involves practices such as end-to-end encryption, multi-factor authentication, periodic vulnerability scans, access controls, employee training and awareness programs, and incident response planning. Strategic coordination between HR and IT functions is required to instill security culture and build HR systems resilient to adapting cyber threats.

In summary, while HR Tech provides operational efficiencies and enhanced decision-making, it also introduces significant cybersecurity threats that need to be addressed immediately and in the long run. Organizations need to consider cyber security as an essential aspect of HR technology adoption and governance to safeguard their employees' data, ensure trust, and preserve business continuity in a digital-first ecosystem.