The Volatility, Uncertainty, Complexity and Ambiguity (VUCA) era drives companies to exert additional effort to achieve their objectives effectively. Lie et al. (2023) stated that a key measure of this achievement is organisational performance, which requires companies to deliver exceptional results to adapt and thrive in the fast-evolving business context. Moreover, superior organisational performance can only be obtained through superior employee work performance. Consequently, Human Resource (HR) management practices should prioritise the effort to ensure that employees’ work performance is always exceeding the organisation’s target, and in turn, contributing a positive impact towards organisational performance (Saraswati et al., 2023). Research shows that employees perform optimally when experiencing positive psychological well-being, which significantly influences both individual performance and productivity (Handayani et al., 2022; Kim et al., 2018; Lee et al., 2021; Sheeran et al., 2025; Zelenski et al., 2008).

World Health Organization (2005) described well-being as a condition in which a person recognises their own capabilities, can handle everyday life challenges, works efficiently and effectively, and contributes meaningfully to their community. In the hedonic perspective, subjective well-being pertains to an individual’s general evaluation of life and emotional experiences, including life satisfaction, positive affect and minimal negative affect (Diener et al., 2015). Meanwhile, the eudaimonic perspective was adopted to develop the concept of psychological well-being, defined as an individual’s psychological health based on the fulfilment of criteria for positive psychological functioning (Ryff, 2023).

The work environment contributes greatly to shaping employee well-being, particularly because of the unique challenges it presents. Anglin et al. (2018) concluded that promoting employee well-being is associated with improving the environment where the employee works, which then results in a job that is valuable, motivating and pleasant. In simpler terms, employees who work in a safe and stress-free work environment will exhibit optimal work performance. One such challenge is the increasing integration of technology in the workplace, which is often aimed at improving operational efficiency and reducing costs (Lee et al., 2021).

Among the various technologies adopted in recent decades, robots, artificial intelligence and service automation (RAISA) have gained prominence for its ability to identify patterns, make decisions and optimise work processes (Webb, 2019). In particular, a robot is identified as a system which can influence its surroundings by grasping and repositioning objects around it (Nikolova et al., 2024). Artificial intelligence (AI) refers to systems that exhibit smart responses by analysing their environment and, with a certain level of autonomy, performing actions aimed at achieving defined goals (Sheikh et al., 2023), while automation is defined as the replacement of human involvement in processes, procedures or equipment with automatic operation (Gerovitch, 2003).

Robots, artificial intelligence and service automation has been largely adopted in industrial settings, as reflected in a survey report conducted in 2025, revealing that 77% of 32 352 participants reported that their organisation had implemented RAISA in the work process. Moreover, 58% of the participants pointed out that they used RAISA for task completion on a regular basis (Gillespie et al., 2025). Closer examination found that RAISA has been applied in various industries to enhance the efficiency of repetitive and routine tasks within distinct workplace settings. For instance, in the manufacturing sector, robots are utilised as material and equipment automatic movers in factories and warehouses (Webb, 2019). In the tourism industry, AI is commonly employed to enhance customer service through human–AI interactions, such as assisting guests with travel planning and in-room services (Loureiro et al., 2023). Additionally, routine customer queries may be handled via chatbots or automated telephone routing systems (Henkel et al., 2020).

Empirical studies have shown that RAISA usage in the workplace, on the one hand, helped to promote employee well-being, such as dealing with difficult customers (Jiang et al., 2022; Willems et al., 2023). Robot, artificial intelligence and service automation was also perceived as a useful resource as it supports employees to complete routine and repetitive tasks (Stamate et al., 2021). Thus, employees had more free time for self-development and high-value innovations (Akter et al., 2024). Regarding self-development, employees perceived RAISA integration as an opportunity for career as well as skill enhancement (Konuk et al., 2023; Tong et al., 2021). On the other hand, the integration of RAISA at work could also reduce employee well-being as it acts as a job demand. Robot, artificial intelligence and service automation was proven to create work stress (Loureiro et al., 2023) and general health (Nazareno & Schiff, 2021). Employees needed to adapt to the new technology by investing more time in learning how to operate the new technology installation as it became part of their job requirements (Kong et al., 2021; Stamate et al., 2021). Furthermore, the automation led to workplace isolation because of the limitation of personal interaction between employees (Nurski & Hoffmann, 2022; Tang et al., 2023). Technical issues with regard to the integration of new technology created additional workload that led to work stress (Hang et al., 2022). Robot, artificial intelligence and service automation was also perceived as a threat because employee believes that it would replace their position doing routine tasks in the organisation (Schwabe & Castellacci, 2020).

Studies examining the impact of RAISA on well-being have produced mixed findings, suggesting that RAISA may function either as a supportive resource or as a potential risk factor. Considering the growing role of RAISA integration in shaping employee well-being, a scoping review is necessary to systematically map existing studies in this area. To the extent of our knowledge, no scoping reviews on employee well-being have specifically examined the integration of RAISA in workplace contexts. Existing reviews have largely emphasised the effects of broader technological domains, such as social media and general technology use, on individual well-being in settings such as healthcare (Aparicio et al., 2025; Lemahieu et al., 2025; Widjaya & Komara, 2023). Closer to the present scope, several reviews have addressed RAISA-related areas, including machine learning, social robots and AI-based conversational agents (Ghafurian et al., 2025; Li et al., 2023; Yang & Zou, 2025).

While the aforementioned reviews offer important perspectives on the intersection of technology and well-being, they do not capture the unique implications of RAISA, which introduces new forms of human–technology interaction in organisational settings, towards employee well-being. This gap highlights the need for a scoping review that consolidates current knowledge on employee well-being in the work environment with RAISA adoption. Such a review not only clarifies the state of the literature but also establishes a direction for future empirical research and organisational practices in the era of smart technology. Therefore, the purpose of this study was to: (1) carry out a scoping review on employee well-being in RAISA-integrated workplace, (2) map out the included studies and (3) provide recommendations, both for future research as well as practical strategies.

Several notes are being taken regarding the scoping review results presented above. The findings will be discussed in threefold: (1) the determinants, (2) intervening variables and (3) theoretical frameworks in the included studies.

Previous research on employee well-being in the workplace with RAISA integration has included personal as well as organisational factors as determinants. On the personal level, the determinants focus on how RAISA affects the employees’ psychological aspects, such as perception, emotion, attitude and behaviour. Integrating RAISA in the workplace will somehow affect employees because they are in contact with the smart technology on a daily basis. Employees’ perceptions towards RAISA may be different from one another. When they perceive RAISA as a resource that assists them in work completion, employees will experience a positive emotion that, in turn, leads to positive work attitude and behaviour (Huang & Rust, 2018). On the contrary, when they perceive it as a demand, RAISA will cost them effort and add up their workload. Moreover, employees will experience a negative emotion and, consequently, negative work attitude and behaviour will occur (Frey & Osborne, 2017; Nurski & Hoffmann, 2022).

The determinants on the organisational level focus on the organisation’s decision to integrate RAISA as part of its business strategy. The advancement of technology is often evaluated as an opportunity to create a more efficient mechanism in organisations, including work culture and employee workflows. Therefore, RAISA will help them to promote the organisation’s productivity and overall performance. Rather than resulting positively, the integration of RAISA has changed job characteristics that lead to a shift in how employees perceive their jobs (Nurski & Hoffmann, 2022). And as illustrated above, employees’ perception towards RAISA will then affect their well-being.

The second fold of our discussion emphasises variables, which intervene in the correlation between the determinant factors and employee well-being in the context of RAISA integration. Across the reviewed studies, intervening variables were present in most cases, whether they function as a moderator, a mediator or even both. According to Baron and Kenny (1986), a moderator is an intervening variable that affects how two variables are related to each other. In certain cases, the moderator may change the direction of correlation as well. Baron and Kenny (1986) also presented an explanation of a mediator, which explains the mechanism through which a predictor influences an outcome. In general, it was concluded that moderators determine when an effect is likely to occur, while mediators describe how or why the effect happens.

Given the functional description of mediating and moderating variables, involving intervening variables in the research model will clearly enrich our understanding of how each variable may affect the correlation. As illustrated by the JD-R model, personal factors – or personal resources – help employees to have access to more job resources. In this context, personal resources are defined as positive self-evaluation that refers to an individual’s appraisal of their capability to effectively control and influence their environment (Bakker et al., 2023). In this sense, when an employee is faced with a new situation like RAISA, they are going to need their own resources to deal with the uncertainties and demands. Therefore, their well-being will remain high. For instance, self-efficacy plays an important role as a buffer to promote employee well-being because it mitigates employees’ anxiety while dealing with the new technology, like RAISA (Chang et al., 2024).

On the other hand, organisational factors affect employee well-being as they may be perceived in a different way. For example, initially organisation implements AI adoption in order to create a more efficient work process. Conversely, employees may perceive it as a threat to their well-being because the adoption of AI will cost them extra effort to learn and adapt to the new technology installation (Wu et al., 2024). Furthermore, RAISA is possibly perceived as a substitute for their existence, which may cause them to lose their current job (Sharif et al., 2025). Hence, adding up these factors as intervening variables will help us to have a better understanding of the factors to leverage or degrade the effect of RAISA integration on employee well-being.

Finally, this scoping review has summarised theoretical frameworks that help to describe the mechanism of how the variables interact with each other from a different perspective. As an example, the JD-R theory is used to illustrate that the integration of RAISA is perceived as a job demand as well as a job resource. Job demands refer to the physical, psychological, social or organisational characteristics of work that require continuous physical, mental and/or emotional effort, which may lead to physiological or psychological strain. In contrast, job resources encompass the physical, psychological, social or organisational aspects of work that provide motivational value, support the achievement of work objectives, help buffer the impacts of job demands and enhance learning as well as personal development (Bakker et al., 2023). In this sense, RAISA integration is perceived as a demand when it develops a negative assumption, including unemployment risk perception, AI anxiety and technostress. Consequently, it affects employee well-being negatively. On the contrary, when perceived as a job resource, RAISA creates a motivational situation such as corporate trust, job autonomy and employee engagement.

The theory of stress is commonly used to give an overview of employee well-being in the context of RAISA. Stress occurs when there is a mismatch between external and internal pressures and the individual’s available resources or skills to manage them (Lazarus, 1993). Although the integration of RAISA can be very demanding because of its complications and employees’ lacking skills, when sufficient support is provided, RAISA facilitates how employees work and generates happiness in the workplace (Loureiro et al., 2023).

As an opposition to Lazarus and Folkman’s theory of stress, the conservation of resources (COR) theory claims that individuals aim to gain, maintain, develop and protect the resources they value most. This theory suggests that stress arises in three situations: (1) when important resources are at risk of being lost, (2) when essential resources have already been lost or (3) when significant effort is made to obtain key resources but fails (Hobfoll et al., 2018). When an organisation implements RAISA to take over certain tasks from employees, it can heighten the loss of their career resources, promoting the perceived threat of RAISA to their job security. As employees become more aware of RAISA, their job stress may rise, which could negatively impact their affective well-being at work (Jin et al., 2024).

Another theory used as a framework in the studies is SDT. This theory suggests that satisfying the three basic needs of competence, autonomy and relatedness places individuals in an optimal condition of well-being (Deci et al., 2017). Stamate et al. (2021) gave further explanation that RAISA is related to the satisfaction of employees’ basic needs, thus it will also affect their well-being. In this case, RAISA is opening more opportunities for employee to learn new knowledge and skills to operate the smart technology (competence), adding to their liberty for better time management because RAISA supports them with administrative work (autonomy), and increasing positive collaboration through real-time feedback (relatedness).

Overall, the determinants, intervening variables and theoretical frameworks reviewed in this study illustrate that employee well-being in a work environment with RAISA implementation is shaped by a complex interaction of contextual conditions, personal resources and theories. This highlights the need for a multidimensional perspective that not only captures direct influences but also accounts for mediating and moderating mechanisms, thereby offering a more holistic understanding of how RAISA transforms the dynamics of work and well-being.

This scoping review identified determinants, intervening variables, well-being concepts and theoretical frameworks utilised in 35 previous studies on employee well-being within the RAISA context. Generally, these studies examined various variables at both individual and organisational levels. The findings reinforced the notion that employee well-being in RAISA-integrated work environment is an impact of both personal and organisational factors. Moreover, the development of research models was largely shaped by theoretical frameworks. These frameworks played a crucial role in explaining the interactions among the variables examined in the studies.

Ultimately, this scoping review aims to offer valuable theoretical and practical insights for stakeholders. Future research on employee well-being in workplaces embedded with RAISA should be further refined. Future scoping reviews could explore additional themes and sub-themes, such as measurement tools, research gaps, methodologies and data analysis strategies. This would enable a more comprehensive mapping of existing studies on employee well-being in the RAISA context and generate sharper recommendations for future research. From a practical perspective, human resource management (HRM) should prioritise employee well-being in response to smart technology integration. Potential negative impacts can be reduced by carefully addressing determinants and intervening variables when designing interventions. Such programmes may focus on personal development, including skill enhancement and career management. Skill enhancement consists of upskilling (improving and/or expanding existing skills) and reskilling (learning new skills), while career management consists of developing career path programme, not only vertical but also cross-functional assignment. The objective is to ensure that employees are equipped with the necessary competencies and clear career expectations to adapt to rapidly evolving technologies.