Agora #96
12 - 19
Digitalisation is transforming work and creating new challenges for trade union rights. Key insights to support collective bargaining and union action.
Digitalisation is changing the reality of work in every sector. New tools, platforms and computerised systems are shaping how tasks are organised, how decisions are made, and how workers are monitored and evaluated. For trade unions, these changes matter because they directly influence members’ rights, working conditions and collective strength.
While technology offers job improvements, it also creates new pressures and blurs boundaries between work and private life. These impacts underscore the need for unions to have reliable, accessible evidence to respond effectively—through collective bargaining, organising, or policy advocacy.
With these concerns in mind, this publication offers a brief overview of a more extensive working paper that examines these issues in greater depth. It focuses on aspects of digitalisation most relevant to trade union work and highlights key findings to support negotiations and campaigns.
We suggest readers read the full findings, in-depth analysis and complete methodology in the original full working paper “Job quality and digitalisation” here.
1. Introduction
Digitalisation is a major driver of change in today’s labour markets, with digital technologies increasingly permeating sectors and occupations. Evidence from the European Company Survey (Eurofound 2019) confirms that digitalisation is both widespread and accelerating, a trend further reinforced by the Covid‑19 pandemic, which expanded the use of ICTs across diverse work settings.
Digitalisation affects labour markets directly through changes in employment relationships and work organisation—altering the duration, place and nature of work—and indirectly through shifting power dynamics, product and service innovation and broader structural changes in occupational composition, including job loss and the emergence of new roles.
Debate has centred on digital technologies’ potential to automate human labour (Frey and Osborne 2013), raising concerns about unemployment but also offering the possibility of reduced working hours (Piasna 2023a). Other research focuses on how technological change interacts with workers’ skills, shaping outcomes by occupational class, education or experience. These shifts may generate labour‑market polarisation in terms of demand, productivity and earnings between skilled and unskilled workers (Autor et al. 2003; Frank et al. 2019). While this literature illuminates the economic implications of technological change, it does not fully explain how digitalisation affects the qualitative dimensions of work or workers’ lived experiences. Although the job-quality effects of technological change have prompted considerable debate, many claims remain poorly grounded in empirical evidence.
This paper contributes to this gap by empirically testing key hypothesised effects of digitalisation on job quality. Using a multidimensional job quality index enables examination of how technology influences
2. Framework for an analysis of the job quality outcomes of digitalisation
Adoption of digital technologies in the workplace takes many different forms, so a common set of outcomes for all workers is unlikely. Rather, the impact of digitalisation depends on the type of technology used and its purpose, where and for whom it is applied, but also how its use is managed and regulated. In this paper, the focus is on the use of computerised systems at work – that is, programmable and/or connected devices – and on the contexts in which such computers influence what workers do. While still broad and, in principle, applicable to most, if not all, occupational classes, this approach to digitalisation aims to map its impact by comparing workers in similar jobs and institutional settings who are exposed to such digital technology with those who are not.
2.1 Transformation of work’s rhythms and temporalities
Digital technologies are reshaping the temporal organisation of work by enabling new forms of measuring, standardising and quantifying labour (Altenried 2020). They allow work to be broken into small time units and allocated in real time to match staffing needs (Lambert et al. 2019), while enhanced computational capacities make large‑scale task–worker matching both feasible and cost‑effective. These systems can compress task durations, reducing breaks and increasing work intensity (Green et al. 2022).
Such tools are transforming established time regimes. Continuous working days increasingly fragment into short, irregular units of paid time interspersed with unpaid periods, as employers exclude what they deem low‑value activities (Standing 2023). Workers describe this as experiencing ‘atomised’ and ‘punctuated’ time (Piasna 2023a). The platform economy illustrates this dynamic through algorithmic management (Kellogg et al. 2020), but similar scheduling and monitoring practices are now common in traditional workplaces as well, contributing to more unpredictable hours and hectic work rhythms (Scheele et al. 2023).
These efficiencies rely on workers being available to take up scattered units of paid activity, creating pressure for ‘incessant availability’ (Piasna 2023a). This often results in spillover into private time, extending work beyond contractual hours and blurring work–life boundaries, with negative consequences for work–life balance (Piasna 2023a). Digital technologies reinforce this through automated management and portable devices that bring work into personal spaces. Research highlights this risk in remote work (Arabadjieva and Franklin 2023), platform work (Schor 2020; Pulignano et al. 2021) and other digitally enabled work forms.
Where employment is highly individualised—such as among freelancers—digital tools can intensify pressures for self‑directed overwork, contributing to the ‘autonomy paradox’, in which autonomy feels like an obligation to work more (Mazmanian et al. 2013; Ivanova et al. 2018).
Overall, digitalisation tends to increase the unpredictability of working time, fragment the standard workday and intensify work. It also encourages extended availability, leading to longer hours and further spillover into private life. Although such processes predate digitalisation and have been linked to deregulation and flexibilisation, digital technologies appear to reinforce these patterns. The empirical analysis that follows examines differences in job quality among otherwise similar workers facing varying degrees of digitalisation.
2.2 Job demands and resources
The digitalisation of work introduces both new resources and new demands, reshaping power relations between workers, managers and organisations. One major potential benefit lies in upskilling: as technological developments raise skill requirements, workers increasingly need competencies to use and develop digital tools (Gallie 2007; ILO 2021). This shift is associated with more autonomous, creative, and innovation-driven jobs, suggesting a structural move towards higher-skilled, more autonomous work (Hancock et al. 2023).
However, digital technologies also expand employers’ capacities for supervision and control, which may undermine worker autonomy (De Stefano 2018; Parent-Rocheleau and Parker 2022). In platform work, algorithmic management combined with precarious contracts severely restricts workers’ ability to choose when and what they work on. The autonomy outcomes of digitalisation therefore depend strongly on employment quality, potentially creating a divide between secure workers who benefit from digital tools and precarious workers facing growing constraints and limited discretion.
Where education systems fail to meet rising skill demands, skilled workers gain bargaining power, which can translate into improved wages and career prospects. This aligns with evidence that digitalisation increases productivity and profitability, provided workers have sufficient leverage to negotiate gains (Tahlin 2007; Berg et al. 2023). Yet, while wage effects are well documented, the impact of digitalisation on aspects such as income stability or predictability remains less understood.
Digitalisation also affects job content, potentially reducing tedious or dangerous tasks (Jetha et al. 2023). At the same time, it introduces new psychological, psychosocial and ergonomic risks associated with digital device use (Wixted et al. 2018). As some physical risks decline and others increase—such as strain from prolonged computer use or demands imposed by automated machinery—overall effects may cancel out, explaining findings of no net change in physical risk factors (Antón et al. 2023). This underscores the importance of examining specific risk categories separately.
Finally, access to collective voice and representation remains a critical resource for job quality (Hyman and Gumbrell-McCormick 2020), especially for vulnerable workers (Piasna et al. 2013; Kirov 2015). Worker consultation may help ensure that digitalisation supports improvements in job quality. Yet digitalisation’s impact on representation is ambiguous: workplace fragmentation may weaken collective structures (Weil 2019), but firms where negotiation is possible may be more inclined to adopt new technologies with less resistance (Mengay 2020). As such, the relationship between digitalisation and worker representation remains an open empirical question.
3. European Job Quality Index (JQI)
The impact of digitalisation on job quality is assessed using the JQI. It is a multidimensional index of job quality developed by ETUI researchers, allowing comparison across EU countries (Leschke et al. 2008; Piasna 2017). Centred on workers’ well‑being, it captures aspects of work linked to health and safety, work–life balance, and psychological and economic well-being.
The index comprises six equally weighted dimensions: income quality; forms of employment and job security; working time and work–life balance; working conditions; skills and career development; and collective interest representation and voice. These draw on multiple data sources, including the European Working Conditions Survey (EWCS/EWCTS), the Labour Force Survey (LFS) and the ICTWSS database.
Because this working paper focuses on individual-level associations between technology use and job quality, only 2021 EWCTS individual data are used for the analysis. The analysis includes 58,403 employed adults aged 16+ and covers 27 EU countries. Further methodological details can be found in the original working paper.
4. Digital technologies at work: mapping the gaps between EU workers
Digitalisation in the workplace is measured through two indicators: use of ICT at work and the influence of computerised systems on work. ICT use is measured by how frequently workers use devices such as computers, tablets, or smartphones, coded from 0 (“never”) to 100 (“always”). The degree to which computerised systems influence work is measured separately on a five‑point scale, including the option that such systems do not apply. This second measure—central to the analysis—captures workers’ perceptions of how digital technologies shape their tasks.
Workplace digitalisation varies strongly by job type. ICT use is highest among clerical workers, professionals, managers, and technicians, and much lower in elementary occupations. The influence of digital systems mirrors ICT usage, though in lower‑skilled manual jobs—such as operators, assemblers and elementary occupations—digital technologies exert relatively high control despite lower overall use, suggesting disproportionate exposure to algorithmic management and technology‑driven pacing of work.
Differences also emerge across employment relationships. Employees with indefinite contracts use ICT most frequently, while the self‑employed—especially freelancers—use ICT often but report lower influence of computerised systems, similar to securely employed workers. Part‑time workers consistently show lower exposure to digital technologies than full‑time workers, even when accounting for job type and individual characteristics. Among full-time workers, women are more likely than men to use computers and experience their influence, a difference not observed among part‑time workers.
Significant cross‑national variation exists as well. Romania and Greece show notably low ICT use at work, while eastern, central and southern European countries generally display lower digital diffusion, with exceptions such as Croatia, Hungary and Czechia. Finland, followed by Sweden, shows the highest technology adoption. Importantly, the way digital technologies shape work tasks does not correspond directly to their frequency of use. For example, Germany, Luxembourg and the Netherlands exhibit high ICT use but low influence of digital systems on workers. Conversely, countries such as Romania, Lithuania, Spain, Poland and Portugal show lower ICT use yet strong technological influence on work organisation.
These patterns reflect broader institutional structures. Countries with historically weaker individual-level control (Gallie and Zhou 2013) tend to show higher exposure to the controlling aspects of digitalisation. By contrast, stronger industrial relations frameworks can moderate technological control, supporting more worker‑protective integration of digital tools. These findings align with research showing that the effects of digitalisation depend heavily on national institutional contexts (Kornelakis et al. 2022; Minardi et al. 2023).
5. Impact of digitalisation on job quality
5.1 Trade-offs and inequalities in job quality: an overview
Before analysing job quality differences related to digital technologies, we first provide an overview of how job quality varies between different groups of workers. The focus is on employment status because it affects both the precariousness of work and exposure to technology.
No labour market segment has the best outcomes on all aspects of job quality simultaneously. Employees on indefinite contracts feel most secure about their jobs and have largely predictable incomes, but only average prospects. Employees on non-standard contracts report similar prospects but lower job security and lower predictability of earnings. The self-employed are most optimistic about prospects (with little difference between freelancers and other self-employed). Their job security is lower than that of workers with indefinite contracts but slightly higher than that of fixed-term and other employees; freelancers feel less secure than other self-employed. Self-employment is generally associated with very low income predictability.
The work intensity index (including work at high speed, to tight deadlines, and working in free time to meet work demands), together with the need to work at short notice, moves in parallel with work autonomy across employment statuses: more autonomy is associated with more intense and less predictable work. This pattern is strongest among freelancers and other self-employed, suggesting self-directed work can lead to self-exploitation where job and income security are low. Employees with fixed-term contracts have the least autonomy and a less intense pace of work.
5.2 Punctuated working time and work intensification
The impact of digital technologies is first assessed in terms of working time – the temporalities and rhythms of work. Where computerised systems influence work organisation—through algorithmic management or automated allocation, evaluation or scheduling—working time is treated as discrete units rather than continuous periods. Digital technologies make managing such units easier and cost-efficient, enabling closer matching of labour supply and demand and resulting in punctuated working time.
This is evaluated by comparing how often workers are required to work at short notice. Overall, the analysis confirms a significant positive relationship between digitalisation and the frequency of working at short notice. This holds true for different aspects of digitalisation: automated management as well as the use of computers as tools for performing work tasks. To discern potential confounding compositional effects, all analyses are carried out while controlling for individual characteristics, job and contract type, as well as country fixed effects. An additional disaggregation of the results by broad economic sector reveals that digitalisation is linked to more frequent work at short notice, in particular in education, health care and financial services.
Therefore, automation enables fragmentation of working time and its scheduling at short notice to match peaks in demand and workload. This results in intensification of work. The results show that workers strongly affected by computerised systems most often work at high speed and under tight deadlines. The effect is observed across all sectors and is most pronounced in construction, manufacturing, health care and other services, and less manifest in transport.
In sum, when computer systems influence what people do at work, working hours are more punctuated, fragmented and unpredictable, and work is more intense. The extent of technological impact matters: a larger impact is associated with the most intense work and the most frequent short‑notice work. This supports claims that digital technology achieves efficiency gains by tightly matching tasks to fragmented time units, leading to effort‑biased technological change.
5.3 ‘Incessant availability’
The literature suggests a paradoxical impact of digital technologies: they support more efficient allocation of work by closely matching tasks to workers, yet simultaneously push workers to extend their availability (as noted in platform work and in more general technology‑mediated contexts). In many cases, workers struggle to disconnect, as work follows them into private time and spaces via portable devices.
The first test of this presumption concerns the spillover of work beyond paid hours, reflecting blurred work/non-work boundaries. Results show that workers experiencing any influence of computers on their work are significantly more likely to work in their free time to meet demands than those reporting no influence. The extent of this influence does not substantially change the frequency of spillover. An exception is the education sector, where spillover rises more clearly and linearly with the degree of computer influence.
A second measure of extended availability is the number of weekly working hours, particularly the incidence of very long weeks exceeding the 48‑hour legal limit. Results indicate that workers exposed to computer influence work more hours per week and are more likely to exceed 48 hours than workers not exposed at all. As with work spillover, the main difference is simply between presence versus absence of computer influence; the extent of influence does not produce a consistent linear pattern.
Extended availability can also be seen through self‑reported work–life balance—how well working hours fit with family and social commitments. Results show that workers whose work is influenced by computer systems report significantly worse work–life balance. Notably, this negative effect of digitalisation is stronger for men than for women.
Overall, work with digital technologies that shape work organisation is associated with greater spillover into private time, including more frequent work in free time, longer working hours and poorer work–life balance. These outcomes do not appear to increase with greater levels of computer influence, which is puzzling. Although the analysis controls for individual characteristics, job types and employment status, some unobserved factors may remain and warrant further investigation.
5.4 Empowering workers and resources at work
Given the significant impact of digital technologies on the temporal structure and demands of work, it is important to assess whether digitalisation also provides workers with additional resources. Digitalisation has been linked to upskilling and the removal of mundane, dangerous or unpleasant tasks, suggesting that jobs with greater ICT penetration might offer better quality at least in some respect.
Setting aside the general positive correlation between computer use and earnings—which partly reflects that higher‑skilled professionals are more likely to use computers—the results show a significant positive relationship between digitalisation and income predictability when compositional effects are controlled for. Workers who experience the influence of digital technologies have more predictable earnings, even when comparing very similar jobs.
However, greater income predictability does not translate into higher job security. The results show that job security declines as computer influence increases; workers exposed to such influence are more likely to think they could lose their job within six months. At the same time, they report more optimism about career prospects, particularly those experiencing a moderate degree of computer influence. It is unclear whether this optimism stems from perceived employability linked to digital skills or from expectations about growth in digitalised occupations.
Digital technologies also influence worker autonomy. While professionals who use computers often have greater autonomy, this is largely a compositional effect. The results show only small increases in autonomy among workers strongly affected by computers, and these differences disappear once job characteristics are controlled for. Digitalisation appears to increase managerial control and monitoring in many contexts, potentially limiting autonomy.
This varies significantly by employment status. The results indicate that employees do not show notable autonomy differences in relation to digitalisation once compositional factors are controlled for. For freelancers, however, digitalisation has a net negative effect on autonomy, suggesting increased control and subordination rather than entrepreneurial freedom. Given that freelancers are more exposed to digital technologies, this is concerning. In contrast, other self‑employed workers (such as directors or managing partners) experience increased autonomy with digitalisation.
Digital technologies also affect physical and psychosocial risks. The index of physical risks includes exposure to noise, chemicals, infectious materials, tiring postures, lifting and moving people, and carrying heavy loads. A separate measure captures repetitive hand or arm movements linked to computer use. The results show that low and moderate exposure to digitalisation is associated with more physical risks than no exposure. Only workers heavily influenced by computer systems report lower exposure to traditional physical risks, but they face the highest exposure to repetitive strain. This suggests limited overall substitution of risky tasks by technology, with trade‑offs between traditional hazards and computer-specific risks.
Finally, access to collective representation is examined, focusing on employees (since self-employed workers were not asked relevant questions in the survey). In general, collective representation is linked to improved job quality (Piasna 2023b) and may help workers negotiate the challenges of digitalisation. The results show that workers more exposed to computer systems have greater access to representation and voice mechanisms, even after accounting for compositional factors. However, there are no substantial differences in how access to representation moderates job quality outcomes across different levels of digital exposure.
6. Summary and conclusions
The growing use of digital technologies in European workplaces is clear, yet their precise impact on work remains under examination. While research has shown that digitalisation transforms job structures through changes in task content, automation and the creation of new occupations (Frey and Osborne 2013), this working paper focused on its consequences for job quality and workers’ experiences. It examined differences between digitalised and non-digitalised work settings among otherwise similar jobs.
Digitalisation’s impact was conceptualised through two perspectives: the role of computerised systems and algorithmic management in shaping working time, task allocation and work intensity; and changes in job demands and resources for workers. Job quality was assessed using the multidimensional European Job Quality Index, applied to data from the 2021 EWCTS across 27 EU Member States.
The results empirically support claims that digitalisation disrupts existing time regimes. Computerised systems were associated with more unpredictable, hectic, and intense work rhythms, work encroaching on private time, longer working hours, and poorer work–life balance. These effects were observed even among similarly skilled workers in similar jobs, with technology use as the main differentiating factor. This aligns with the thesis that digitalisation produces more “atomised” and “punctuated” working time and enables employers to tightly match workloads to staffing needs, while workers respond by extending their availability (Piasna 2023a).
The analysis also revealed a complex relationship between digitalisation and workers’ resources and bargaining power. After controlling for compositional factors, digitalisation was linked to greater income security and better career prospects, but also to lower job security. This corresponds with broader trends of fragmented labour markets and shifts away from stable employment, but the study shows that technology-related differences appear even within otherwise comparable jobs.
The findings likewise challenge the assumption that digitalisation increases autonomy: any observed rise in discretion stems from compositional factors rather than technology’s direct effects. Particularly concerning is the autonomy loss observed among freelancers—an already vulnerable group heavily exposed to digitalisation—echoing insights from the platform-economy literature (De Stefano 2018; Piasna and Drahokoupil 2021).
The analysis further highlighted trade-offs between traditional and emerging risks. Some physical risks are less common in digitalised work, but new risks linked to automation and prolonged computer use are rising, underscoring the need for closer monitoring and appropriate regulation. A more positive finding concerns access to collective representation, which increases with the intensity of computer influence on work. However, the direction of this relationship still needs to be better analysed. It is uncertain whether workplaces with stronger representation are more likely to adopt new technologies, or whether digitalised environments foster solidarity and participation, as suggested by Vandaele and Piasna (2023). Nevertheless, this suggests that workers facing new challenges and risks may also have opportunities to negotiate a more worker-centred digital transition.
For reference, please refer to the original working paper here.
Agnieszka Piasna
About the author
Agnieszka Piasna is a senior researcher in the Economic, Employment and Social Policies Unit at the ETUI. A labour sociologist, she studies job quality, labour market regulation, digitalisation, and gender equality. She coordinates the ETUI Internet and Platform Work Survey, contributes to the European Job Quality Index, and researches working time reduction. She has advised Eurofound, EIGE, ESAC, Eurostat, and the ETUC, and holds a PhD in sociology from the University of Cambridge.