Blog 05 - Employee Engagement in a Technology-Driven Workplace: Empowerment or Digital Exhaustion?
Employee Engagement in a Technology-Driven Workplace: Empowerment or Digital Exhaustion?
Technology has changed almost every part of the employee experience. Meetings can be held across countries, employees can access information instantly, Artificial Intelligence (AI) can remove repetitive work, and managers can analyse workforce data faster than ever before. Yet the same workplace can also overwhelm employees with notifications, constant digital communication, monitoring and an increasingly rapid pace of work.
This creates a major Human Resource Management (HRM) challenge. The same technology that can make work easier can also make work more intense. The same data that can help organisations understand employees can also make employees feel watched. The same AI tools that can increase autonomy can be used to control how work is performed.
What Does Employee Engagement Actually Mean?
Employee engagement is sometimes used loosely to describe whether employees are happy at work. Academic thinking is more precise. Kahn (1990) described engagement in terms of people bringing their physical, cognitive and emotional selves into their work roles. Schaufeli et al. (2002) later conceptualised work engagement through three dimensions: vigour, dedication and absorption.
The CIPD (2025) similarly recommends treating work engagement as a psychological state rather than simply a survey score. Engaged employees demonstrate energy and resilience, enthusiasm and pride, and deep concentration in their work. This matters because an employee can be satisfied with pay or conditions without necessarily being highly engaged in the work itself.
The Global Engagement Challenge
The latest Gallup data show that employee engagement remains a serious global challenge. In 2025, only 20% of employees worldwide were engaged at work. This followed 21% in 2024 and 23% in both 2022 and 2023, meaning global engagement declined for two consecutive years (Gallup, 2026).
Figure 1. Global employee engagement, 2022–2025. Author’s illustration based on Gallup (2026).
Gallup (2026) estimates that low engagement cost the world economy approximately US$10 trillion in lost productivity. South Asia experienced the largest regional decline in engagement in 2025, falling by five percentage points, while manager engagement in South Asia fell by eight points.
These figures matter because digital transformation is occurring at the same time that many employees and managers are already struggling with engagement. HR therefore cannot treat motivation, workload and trust as secondary issues during technological change.
How Technology Can Strengthen Engagement
The Job Demands–Resources model developed by Bakker and Demerouti (2007) provides a useful way to understand the relationship between technology and engagement. Job demands require sustained effort and can create strain, while job resources help employees achieve goals, develop capabilities and cope with those demands.
AI can function as a job resource when it removes repetitive administration, helps employees access information, supports decision-making or gives workers greater control over their tasks.
Figure 2. Selected positive employee experiences associated with AI adoption. Author’s illustration based on OECD (2023).
OECD surveys found that 63% of AI users in finance and manufacturing reported improved enjoyment of work. AI also supported decision-making: 70% of users in finance and 56% in manufacturing reported that AI assisted them with decisions. Most workers surveyed also said AI increased their control over the sequence in which they performed tasks—58% in finance and 59% in manufacturing (OECD, 2023).
This connects with Self-Determination Theory. Deci and Ryan (2000) argue that motivation is strengthened when people experience autonomy, competence and relatedness. Technology that helps employees solve problems independently or develop new capabilities may therefore strengthen intrinsic motivation rather than simply increase efficiency.
When Digital Tools Become Digital Demands
The positive story is only half of the picture. A digital tool can move from being a job resource to becoming a job demand when it increases workload, reduces recovery time or creates pressure to remain constantly available.
Figure 3. AI adoption and reported increases in work pace. Author’s illustration based on OECD (2023).
The OECD surveys found that 75% of AI users in finance and 77% in manufacturing reported an increase in the pace of work. Among finance workers subject to algorithmic management, 85% reported a faster work pace (OECD, 2023).
Technology can reduce effort per task while increasing the number of tasks employees are expected to complete. Efficiency can therefore rise at the same time that exhaustion rises.
From People Analytics to Employee Surveillance
People analytics can help organisations identify turnover risks, skills shortages and differences between teams. Used carefully, this can support better decisions. However, the line between measurement and surveillance can become very thin.
The International Labour Organization describes algorithmic management as the use of algorithmic systems and tracked data to organise, assign, monitor, supervise and evaluate work (ILO, 2025). The OECD (2023) also reports that when employers use AI to collect data about workers or how they do their jobs, the majority of surveyed workers were concerned about privacy. One in five workers reported that AI had decreased their autonomy, with this negative effect more common among workers subject to algorithmic management.
Employee Voice Matters During Digital Change
The CIPD (2025) identifies employee voice as an important driver of engagement. Employees need channels through which they can express views and influence matters that affect them at work. This becomes especially important when technology changes how work is performed.
Employees often understand the practical effects of new systems earlier than senior managers because they use them every day. They can identify when a digital process creates unnecessary work, when an automated metric is misleading or when a new system damages the employee or customer experience.
A digital transformation programme should therefore ask employees:
- Which parts of your job create unnecessary frustration?
- Which tasks should technology support rather than replace?
- Has technology increased or reduced your autonomy?
- Has your workload changed since the system was introduced?
- What training or support do you need?
The Role of Managers
Technology does not eliminate the importance of the line manager. In many cases, it increases it. The CIPD (2025) identifies managerial support, good-quality relationships, job design, organisational climate and autonomy as important influences on engagement.
Gallup’s 2026 research also highlights the role of managers in AI adoption. It reports that, apart from technical integration, one of the strongest predictors of whether employees use AI is whether their direct manager actively champions it. Managers therefore need to explain why a technology is being introduced, help employees develop confidence, clarify expectations and make sure efficiency gains do not automatically become unrealistic workload increases.
Global and Cross-Cultural Considerations
Employee engagement cannot be separated from cultural and institutional context. Brewster et al. (2017) emphasise that HRM practices operate within different national systems and cultures. The meaning employees attach to autonomy, monitoring, managerial authority and employee voice may therefore vary across countries.
For example, a highly individualised digital performance system may be accepted in one context but create resistance in another where teamwork and collective achievement are more strongly valued. Global HRM therefore requires consistent principles but enough local understanding to recognise how employees actually experience work in different locations.
A Better Model: Human-Centred Digital Engagement
Human-centred digital engagement should aim for:
Automation without dehumanisation — remove low-value work, not meaningful human interaction.
Measurement without surveillance — collect data for a legitimate and transparent purpose.
Productivity without exhaustion — use efficiency gains sustainably rather than continuously raising workloads.
AI without loss of autonomy — support employee judgement rather than replacing it unnecessarily.
Digital communication without constant availability — protect recovery time and healthy boundaries.
Change with employee voice — involve employees in technologies that affect their work.
🎥 Recommended Video
This Gallup discussion explores the recent decline in global employee engagement and why managers and workplace conditions matter.
▶ Watch on YouTubeMy Reflection
Before exploring this topic, I mainly associated workplace technology with efficiency. If an AI system reduces repetitive tasks or allows work to be completed more quickly, it seems reasonable to assume that employees will automatically benefit.
The evidence shows that the relationship is much more complicated. AI users can experience greater enjoyment, autonomy and decision support, but they can also experience a faster pace of work and greater monitoring. The same technology can therefore support engagement or damage it depending on how managers use the efficiency it creates.
I also realised that engagement cannot be created by technology itself. An organisation can introduce advanced digital systems while employees remain disengaged because of poor management, lack of recognition, excessive workload or weak employee voice.
For me, the most important lesson is that HR should not ask only whether technology improves organisational performance. HR should also ask how employees experience that technology. If AI removes a repetitive task, what happens to the time that is saved? If a monitoring system provides more data, does it help the employee improve or simply increase pressure? If a digital platform connects employees at all times, are they also allowed to disconnect?
💬 Join the Discussion
Does technology make you feel more empowered at work—or more monitored and pressured?
If an AI tool made you 30% more productive, should your employer increase your targets by 30%, or should some of that benefit be used to improve workload, development and wellbeing? Share your view in the comments.
References
Bakker, A.B. and Demerouti, E. (2007) ‘The Job Demands–Resources model: state of the art’, Journal of Managerial Psychology, 22(3), pp. 309–328.
Brewster, C., Sparrow, P., Vernon, G. and Houldsworth, E. (2017) International Human Resource Management. 4th edn. London: CIPD.
CIPD (2025) Employee engagement and motivation. 23 July. Available at: https://www.cipd.org/en/knowledge/factsheets/engagement-factsheet/ (Accessed: 12 August 2026).
Deci, E.L. and Ryan, R.M. (2000) ‘The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior’, Psychological Inquiry, 11(4), pp. 227–268.
Gallup (2026) State of the Global Workplace 2026: Global Data Summary. Available at: https://www.gallup.com/workplace/697904/state-of-the-global-workplace-global-data.aspx (Accessed: 12 August 2026).
Gallup (2026) Global Employee Engagement Continues Decline. 8 April. Available at: https://www.gallup.com/workplace/708071/global-employee-engagement-continues-decline.aspx (Accessed: 12 August 2026).
International Labour Organization (2025) Algorithmic management in the workplace. Available at: https://www.ilo.org/algorithmic-management-workplace (Accessed: 12 August 2026).
Kahn, W.A. (1990) ‘Psychological conditions of personal engagement and disengagement at work’, Academy of Management Journal, 33(4), pp. 692–724.
Marchington, M. and Wilkinson, A. (2020) Human Resource Management at Work. 7th edn. London: CIPD.
OECD (2023) ‘Artificial intelligence, job quality and inclusiveness’, in OECD Employment Outlook 2023: Artificial Intelligence and the Labour Market. Paris: OECD Publishing. Available at: OECD Employment Outlook 2023 (Accessed: 12 August 2026).
Schaufeli, W.B., Salanova, M., González-Romá, V. and Bakker, A.B. (2002) ‘The measurement of engagement and burnout: A two sample confirmatory factor analytic approach’, Journal of Happiness Studies, 3, pp. 71–92.
I agree that technology can empower employees by improving access to information, flexibility and collaboration. However, the same technology can create digital exhaustion when employees are expected to respond constantly to messages and notifications. This creates an interesting HRM tension between empowerment and availability. In my view, organisations need clear digital-work expectations so that technology remains a resource rather than becoming another job demand. Employee engagement should therefore be measured not only by how connected employees are, but also whether they have sufficient autonomy and boundaries.
ReplyDeleteThis is a very relevant and thought-provoking discussion of employee engagement in today’s technology-driven workplace. I particularly appreciate the distinction between technology as a resource and technology as an additional workplace demand. While AI and digital tools can improve productivity and reduce repetitive tasks, constant notifications, monitoring, and digital communication can also contribute to employee exhaustion.
ReplyDeleteThe explanation of engagement through vigour, dedication, and absorption provides a strong foundation for understanding why employee engagement is more than simply job satisfaction. I also agree that organizations should focus on how employees actually experience technology rather than measuring technological adoption alone. Effective leadership, clear digital boundaries, employee autonomy, and meaningful work will be essential to ensure technology strengthens engagement rather than creating digital exhaustion. Overall, this is an excellent analysis of an increasingly important HRM challenge.