Rural Greece in Transition: Digitalisation, Demographic Dynamics, and Migrant Labour

Abstract

The paper examines the current landscape, as well as the promises and pitfalls, of the digital transition in agricultural production and rural areas in Greece. It questions whether digitalisation is a viable option given the demographic dynamics, gaps in digital infrastructure, and heavy reliance on migrant labour in rural Greece. The methodological approach employs a mixed-methods design, integrating statistical and cartographic analyses of available census data with qualitative methods (semi-structured interviews, ethnographic observations, and a focus group). The main research question is grounded in a brief theoretical framework that addresses critiques of the inevitability of technological innovation and highlights the need to understand the complex dynamics of digital change. The paper analyses the dynamics and challenges of digital change in rural Greece, examining how demographic change and ageing, the structure and size of farms, and dependence on migrant labour relate to gaps and inequalities in digital infrastructure and skills. A critique of the prevailing discourse on digital transformation is supported by a discussion of the recently collected qualitative empirical material. The concluding section highlights the key findings and provides policy recommendations.

1. Introduction

Agriculture and rural areas are increasingly affected by a range of challenges, including climate change, environmental degradation, geopolitical instability, changing supply chains, and shifting consumer preferences. Digital technologies offer innovative solutions that can improve the resilience and sustainability of rural communities and farming systems [1]. Precision agriculture, for example, enables farmers to optimise resource use through data-driven decisions in order to reduce waste and increase efficiency [2]. In addition, digital platforms connect farmers directly with consumers, reducing dependence on middlemen and increasing profitability [3]. In rural areas, improved digital connectivity can boost the local economy beyond agriculture [3]. Remote work and digital education opportunities can help counteract population decline by attracting younger generations [4]. In addition, access to services such as telemedicine and e-government can improve the overall quality of life in remote regions [5].

The goal of digital transition in agriculture and rural areas is widespread not only in Europe, but worldwide. Although many authors do not distinguish between digital transition and transformation [6,7], in this paper we use the term ‘transition’ to illustrate the adoption and widespread use of digital technologies and reserve the term ‘transformation’ for more far-reaching changes in agriculture and rural areas. The digital modernisation of agricultural production along the agri-food value chain is seen as an important goal, where knowledge, research, innovation and stakeholder support can improve productivity and competitiveness on the one hand and the effective management of natural resources on the other to address the consequences of the environmental crisis. In this way, the digital transition is presented as an all-encompassing process that aims to address issues of economic efficiency together with the protection of environmental resources [7]. The focus of the digital transition with environmental concerns is interpreted as a step towards broader societal changes. However, a more nuanced approach is needed to capture the interrelationship between technological innovation and social change.

Digital change (or digital transformation) has been conceptualised in different ways, reflecting the differences in scope. The definitions presented here are taken from Kraus et al. [8], who summarise the main conceptualisations of digital change in the literature. Some definitions take a technology and business-oriented perspective and emphasise the role of digital tools in improving performance, processes, and customer experience [9]. Others emphasise the customer dimension and see digital transformation as a strategic realignment of business models to better respond to digital consumers [10]. A more systemic view sees digital transition as a transformation of organisational structures, values and cross-sector dynamics that changes the “rules of the game” in industries and economies [11]. Even broader are definitions that place digital transition in a societal context and emphasise its ability to create fundamentally new capabilities and transform social, governmental and economic life [12]. While these perspectives acknowledge the importance of digital technologies, they diverge on whether transformation is primarily about organisational improvements, customer engagement, systemic change or societal developments. Overall, despite attempts by the academic community to understand and interpret digital transformation, there is no established definition [8].

This paper uses the term ‘digital transition’ because numerous socio-economic, political, and cultural preconditions must be met before a transition can be considered a digital transformation [13]. The work of Acemoglu and Johnson [14] provides a comprehensive historical and political economy analysis of the relationship between technological innovation, social change and power structures, offering valuable conceptual tools and historical insights relevant to understanding the varied impacts of technology across different social and spatial domains, including urban and rural regions. In summary, digital transition in agriculture and rural areas is possible, but should not be regarded as inevitable, as its success depends less on the technology itself and more on the political economy and existing inequalities, particularly with regard to who wields power, who sets the agenda, and whose interests are served.

In this context, the paper aims to explore the current landscape, as well as the promises and pitfalls associated with the digital transition in agricultural production and rural areas—focusing on key factors such as demographic capacity, the agricultural labour force, and the social and physical infrastructures that shape rural Greece. This paper analyses the dynamics and challenges of digital change in rural Greece, examining how demographic change and ageing, the structure and size of farms, and dependence on migrant labour relate to gaps and inequalities in digital infrastructure and skills.

The remainder of the paper is organised as follows: First, the theoretical framework on which the main research question is based is briefly introduced, and a critique of the inevitability of technological innovation is made. It then discusses the demographic dynamics and challenges in rural areas (e.g., depopulation, ageing), the situation in Greek agriculture, and the role of migrant labour as a structural determinant of agricultural production. In addition, the digital infrastructure gap in rural Greece is briefly described. This is followed by a presentation of the qualitative material collected to explore digital transition in agriculture and rural areas in Greece. The concluding section presents some of the findings that emerge from the preceding theoretical and empirical discussions, along with policy recommendations.

2. Theoretical Framework

Digital transition in agriculture and rural areas has become a focus of interdisciplinary research, as it has the potential to transform food systems, rural livelihoods and socio-ecological relationships. As with previous technological transitions, the digitalisation of agriculture and rural areas is a complex process based on an interaction between technological innovation, social change and rural development.

In popular discourses, as well as in many progressivist approaches, technology tends to be reduced to machines or inventions; it is usually seen as something solid, created, and not easily decipherable by the ordinary mind; and it is often mixed with fictional or futuristic narratives of how life is imagined [15,16]. There is a long discussion in science and technology studies (STS) [17] that emphasises the social thickness and complexity of technological systems, recognising their historicity and the fact that they are socially constructed [15] (pp. 2–3). According to this view, digital tools—from precision-farming systems to data platforms—are shaped by, and in turn shape, the norms, values and power structures within agricultural systems. This framework emphasises the importance of co-creation, stakeholder engagement and institutional adaptation for the successful adoption of digital innovations. In this context, the politics of technology as a dialectic between competing claims about risk, design, standards and ethical constraints has become a challenging arena for civic engagement and participation [18].

A key element in understanding technological change is the dynamics of expectations, as they play a mediating role across scales, levels, times and communities. In short, expectations are essential for the coordination of different communities of social actors and groups, and have strategic importance for achieving interactions between different scales or organisational levels [19]. The complexity of interactions related to technological change and transformation needs to be addressed beyond a tantalising discourse of technological progress that remains elusive and fragmented. The promise of technology is reflected in the importance of expectations as “imperatives” or statements about the future in the structure of the present [19] (p. 293). However, these statements about the future cannot be associated with a prescribed and definitive future, only with plural futures that represent variable types of modernity [20]. In the meantime, shared visions of technology are as powerful as the technology itself, even if it is important to find ways to share the benefits of technological progress more broadly [21]. Narratives about technology remain dominant even when technological changes, such as automation, have a negative impact on people’s lives [14].

In the digital age, inequalities in access to and the use of digital technologies can be observed at different levels and in different places. The observed and underlying digital inequalities are reflected in social, economic, political and cultural differences. From this perspective, information and communication technologies (ICTs) can be seen as accelerators of economic growth that reinforce inequalities [22]. Despite its promising potential, digital agriculture harbours the risk of exacerbating existing inequalities between urban and rural areas, as well as within rural areas. It is often argued that there is a “rural penalty” for realising rural development, due to the “digital divide” between urban and rural areas. In this way, ICTs cannot be seen as a “quick fix” for rural development, as the desired improvements remain limited to a fraction of rural areas [23]. Different scholars emphasise the persisting digital divide, which is reflected in both access to infrastructure and digital literacy [24,25,26].

However, other scholars propose moving beyond the notion of the ‘digital divide’ and focusing on digital social inequalities, which are not only presented in terms of accentuating previous hierarchical types of inequalities, but take into account complex relational identities in which different social actors and groups are constructed [27]. Indeed, rural residents are doubly disadvantaged when trying to access online and/or physical social services. Thus, the observed gaps in the availability and use of digital technologies clearly disadvantage rural residents, who lack access to online services and have poorer opportunities for well-being than their urban and suburban counterparts [28]. In addition, social scientists are increasingly growing aware both of a new digital capital arising from the advantages some people have from participating in digital technology and, conversely, of the disadvantages associated with a lack of access to digital infrastructure and skills. The term digital capital was coined to emphasise the unequal distribution of skills and resources required for effective use of digital technology [29]. These inequalities are particularly pronounced among smallholder farmers, older farmers, migrant workers, and marginalised rural communities, raising concerns about inclusivity and the equitable distribution of digital benefits.

Based on the premise that the social world cannot be conceived independently of the material world [27] (p. 947), it becomes clear that technology cannot be regarded as a mere object produced by human action. According to actor-network theory (ANT), we need to consider the qualities, characteristics and agencies of particular technologies. Therefore, we should refer to socio-technical networks that are the result of heterogeneous actors (e.g., servers, protocols, users, websites, fibre optic cables, etc., which form an assemblage and interact through repetitive and transformative actions [27]. Within this framework, sensors, drones and algorithms are seen not only as tools, but as non-human actors that influence decision-making processes, labour processes, and environmental interactions [30]. For example, a digital twin in agriculture can combine sensor inputs, simulation models, and automated controls to influence irrigation or greenhouse management [31]. In contrast, a neural network is a narrower computational tool used for prediction or classification, which can be embedded in larger systems such as digital twins or farm decision-support platforms. Both can be considered actors in the ANT framework, insofar as they structure possible actions, mediate choices, and redistribute agency between humans and technologies. This perspective highlights that agricultural decision-making is not reducible to the farmer alone, but is the outcome of distributed human–technology assemblages. Moreover, digital technologies mean new spatialities and timescales for human action [32].

Rural areas, due to their low population density and territorial extensiveness, are considered “deficient areas” for the development of digital infrastructures and the skills and capacities of their inhabitants, while at the same time ICTs have long been presented as a means to overcome the disadvantages of rural areas in development projects and, in particular, to reduce the feeling of remoteness [33]. This paradoxical situation must be related to the way technological innovation is conceptualised, i.e., as a choice or as an inevitable outcome of a socio-economic process. Various economists and economic historians have emphasised that technological change and innovation should not be seen as inevitable, but rather as the result of power structures and social and economic arrangements in different societies [14,34,35].

To understand how digital technologies emerge and spread in agriculture and rural areas, we need to adopt a multi-level perspective that allows us to contextualise the process of digitalisation in a broader systemic change [36]. In this context, digital change unfolds through the interactions between niche innovations, socio-technical systems and landscape influences such as climate change and globalisation. Digital transition is not a novelty; its disruptive patterns are reminiscent of earlier periods of technological change, and mechanisation in particular [37,38,39]. In the current period, however, digital transition in agriculture and rural areas can be seen as forming part of two broader, interrelated dynamics: platformisation and datafication [40,41,42]. Critical political economy and agrarian studies question the growing concentration of power in agricultural technology companies [40,43,44,45].

Platformisation refers to the increasing dominance of digital platforms—such as marketplaces, data hubs or service ecosystems—in the intermediation of agricultural activities and rural services [40,42]. These platforms act as intermediaries that bring users (i.e., farmers, agribusinesses, input suppliers, consumers) together and offer tools or services via a digital infrastructure. Digital platforms are a relatively new business model that is part and parcel of digital capitalism [46]. Datafication, on the other hand, is the process of converting agricultural practises, environmental variables, and social interactions into quantifiable digital data that can be stored, analysed and acted upon. Datafication has immense implications for precision agriculture, which utilises sensors, drones and IoT (Internet of Things), while also feed into farm management software. Finally, satellites and remote sensing are central to providing macro-level data on weather patterns, land use and productivity [7,47,48,49].

In fact, platformisation and datafication can be found in combination and therefore have an important impact through their reshaping of agricultural value chains, labour relations and governance structures in rural areas [13,39,50,51,52]. As digital platforms mediate who can buy/sell, they create new winners and losers. Τraditional and/or local knowledge are displaced by data-driven decision-making models. Land use decisions are increasingly based on algorithmic assessments of “efficiency” or “risk management”. Control over the data and the rules of the platform often lies with large companies and not with local actors or farmers. At the same time, digital technologies based on automation and remote monitoring are leading to a reduction in labour requirements or the deskilling of work, while creating new tech-oriented jobs [38,53,54,55,56].

As far as agricultural labour, and migrant labour in particular, is concerned, the digital transition means an expansion of digital capitalism into agriculture and rural labour markets. Rather, digital platforms and big data are leading to a greater control of migrant labour to promote capital accumulation and productivity. Platformisation subsumes migrant labour and reproduces Taylorist principles as tasks are broken down, controlled and optimised through digital surveillance (e.g., GPS tracking of workers, productivity dashboards), creating an algorithmically managed workforce that increasingly relies on low-wage, unskilled labour and abolishes social and safety-related labour rights. Finally, the spread of digital technologies that drive automation, and thus the substitution of migrant workers (e.g., by robots), is another disciplinary mechanism for controlling agricultural labour and reducing labour demands (e.g., for higher wages) [57,58,59,60,61,62].

3. Demographic Dynamics, Agriculture, and Migrant Labour in Rural Greece

The study of demographic dynamics is based on an understanding of various factors that influence the size, structure and composition of the population in a given area. Demographic change is primarily influenced by the birth rate and life expectancy, but other factors such as migration patterns can also have an impact on the phenomenon [63]. When analysing demographic dynamics, it is important to consider the characteristics and structure of the population and, at the same time, its mobility and settlement patterns. When looking at the demographic profile of specific areas/regions, it remains essential to consider both stocks and flows. In addition, there are complex interactions between demographic factors and the socio-economic, cultural, political, and spatial characteristics of regions [64].

In this context, demographic change in Greece is the result of two seemingly contradictory trends: namely, the low birth rate and increasing life expectancy. These two factors contribute significantly to the ageing of the population and, depending on net migration, can also lead to a decline in the population. Demographic changes in Greece reveal considerable spatial differences, with urban, rural and remote regions, such as mountainous areas and islands, experiencing different trends and intensities of change. For example, the country’s population declined by 3.1% between the 2011 and 2021 censuses, while some island regions and urban areas experienced population growth, showing that demographic change is not a homogeneous process. This process is not new, as it has been developing for decades, but it has intensified in recent years [65].

The population of Greece is heavily concentrated in two key regions: Attica, which includes the greater Athens area, and Central Macedonia, where Thessaloniki, the country’s second largest urban centre, is located. This concentration of population reflects the continued dominance of urban centres as economic and social hubs. Thus, the population decline observed at national level is not equally severe in all regions. Two regions—the South Aegean and Crete—are bucking the national trend and experiencing population growth (see Figure 1). These regions not only show positive demographic dynamics; they also have the highest total fertility rates in Greece. They also have the lowest proportion of older residents, with only around 20% of the population aged 65 and over, compared to the national average of 22.8%. This suggests that while fertility and ageing trends are driving national demographic change, specific regional factors, related to socio-economic developments and infrastructures, can counterbalance these general demographic patterns.

Demographic ageing, an important consequence of the decline in the birth rate and rising life expectancy, is more pronounced in rural areas than in urban centres. A detailed spatial analysis of Greece’s NUTS 3 regions shows that ageing patterns vary greatly depending on geographical characteristics such as altitude and proximity to urban centres. Urban municipalities generally have a lower proportion of older inhabitants, often below 20%. In rural areas, especially in mountainous regions, the ageing rate is much higher, often exceeding 30% (see Figure 2). This discrepancy can be attributed to the long-term exodus of the younger population from rural areas in search of better economic prospects in the cities, leaving behind an increasingly ageing population. Rural areas on the coast and at lower altitudes tend to have a relatively younger population than their counterparts inland and at higher altitudes. The higher proportion of older inhabitants in mountainous regions illustrates the impact of geographical isolation on demographic sustainability. These areas often experience greater population decline, exacerbated by a lack of economic opportunities, infrastructural deficits and limited access to health and social services.

Migration is a key factor in demographic change in Greece, mitigating population decline in some areas and accelerating it in others. In urban centres and economically dynamic regions, net migration has helped to offset the effects of low birth rates and ageing. Attica and Central Macedonia, despite some population decline in central urban areas, continue to attract migrants who contribute to demographic stability in suburban and peri-urban areas. Conversely, rural and mountainous regions, which in the past relied on net migration to maintain their population, are finding it increasingly difficult to attract and retain residents. The depopulation of these areas has been exacerbated by internal migration patterns favouring urban centres and out-migration to other countries, particularly among younger age groups, a process linked to the impact of the economic recession that affected the country in the period 2009–2017. Analysing the sex ratio (men per 100 women) in the younger age groups (25–45 years) shows significant discrepancies in rural areas, where the number of women is limited due to their search for better employment opportunities, infrastructure and well-being in urban areas (see Figure 3a–d). Rural areas are apparently quite attractive for tourist activities, but not so attractive when it comes to permanent residence. Consequently, the population decline in these regions is not only a consequence of natural demographic processes, but also of broader socio-economic dynamics.

The presence of international migrants has been observed since the 1990s, when considerable flows of migrants from the Balkan countries came to Greece after the fall of the Berlin Wall. For many years, until the outbreak of the great financial crisis of 2008/9, the contribution of migrants in Greece’s construction, agriculture and tourism sectors was immensely important, as it ensured the availability of labour, kept production and service costs low, and improved the (low) competitiveness of the economy to a certain extent [67,68]. According to the latest census of 2021, despite the effects of the economic recession and the outflow of Greek nationals and migrants observed in the years prior to it [69], the proportion of migrants (with foreign nationality) remains significant at 7.3% of the population and 8.9% of the country’s labour force. Based on these figures, it becomes clear that many rural areas, especially island, coastal, and lowland areas (near the coast), attract a higher proportion of migrants due to the availability of jobs and livelihood security (see Figure 4a,b). It should be noted that the proportion of migrants is higher (11.2% of the population) if people born in another country are included. This is due to the fact that many first-generation Albanians, and a smaller number of other nationalities, have been naturalised and are part of the permanent population. Many rural areas, which are economically more attractive, have benefited from the naturalisation of former migrants who have chosen to take advantage of the available policy options and not return to their country of origin.

Particularly in rural areas, the agricultural sector has been a ‘sector of departure’ for Greek nationals, who are confronted with the difficult conditions in agriculture, strong competition in the markets for their agricultural products, and the growing attractiveness of non-agricultural activities. At the same time, the agricultural sector has been a ‘sector of arrival’ for irregular international migrants in search of employment opportunities, lower living costs, and livelihood opportunities in Greece [70]. The contribution of the agricultural sector to the Greek economy has continued to decline. By 2024, the primary sector’s contribution to the country’s GDP had declined to 3.3%, compared to 7.4% in the mid-1990s. In addition, primary sector employees account for 10% of the labour force in 2024, compared to around 18% in the mid-1990s [71]. The proportion of people employed in agriculture varies greatly from region to region, because, barring urban and tourist regions, agriculture is still an important activity in most rural areas (see Figure 5a,b).

Despite improvements in Greek agriculture, the average farm size is 5.3 ha, showing that most agricultural units in Greece are small and medium size [72,73]. The number of farms has decreased significantly from over 861,000 in 1991 to almost 525,000 in 2020, a 40% fall. At the same time, the number of family members employed on family farms has fallen by 48% over the same period [74]. Against the backdrop of the decline in the number of farms and family members employed on them, non-family wage labour—largely consisting of migrant workers—has become a structural component of Greek agriculture. Figure 6 shows that migrant labour has played an important role in replacing the decreasing number of family members and meeting the need for stable and/or seasonal labour [59]. Their share of the total agricultural labour force increased from 8.6% in 1991 to 19.4% in 2003, followed by a slight decrease, before reaching 21.2% in 2020. A comparison of changes in the share of non-family labour and/or migrant labour over the last ten years shows significant differences at regional level, as well as an expansion of wage labour in agriculture in a larger number of rural areas (see Figure 7a,b). In recent years, however, ELSTAT estimates that the demand for migrant labour has increased significantly and is not being met by the available supply of wage labour, leading to an increase in real wages for workers in agriculture [71].

Overall, demographic and socio-economic challenges in the countryside pose significant barriers to digital transition in agriculture and rural areas [69,75,76,77], which are often neglected due to the prevailing progressivist approach that presents technology as a catalyst for socio-economic change and economic development. More specifically, migrant labour is mainly understood as a factor of production that can be replaced and/or eliminated through technological innovations that further rationalise the economic system in rural areas.

4. The Gap in Digital Infrastructures and Digital Skills in Rural Greece

Greece has not fully recovered its 2009 GDP since the economic recession, and there are clear signs that the country has embarked on a path of “growthless employment” for its economic activity [78]. The average number of hours actually worked per week in the main job in Greece is 39.8 h, the highest of all EU27 countries, and well above the EU average of 36 h [79]. The country’s dependence on labour-intensive sectors of the economy has become a major disadvantage for wage earners, as wage levels have remained low and the gap between the average and minimum wage has narrowed over time [80]. In this context, and despite employment growth, wage moderation as an economic strategy favoured by austerity measures during the long economic recession, continued government policies and the structure of the economy, has been a major driving force restricting the distribution of the benefits of economic recovery.

Greece ranks near the bottom among EU countries in terms of connectivity, human capital, and use of internet services, integration of digital technologies by businesses and digital public services [81]. In the 2024 edition of the Digital Economy and Society Index (DESI), Greece ranks last among the EU Member States for numerous key digital indicators. This applies to most indicators, particularly to the percentage of small and medium-sized enterprises (SMEs) that have at least a basic level of digital intensity. Despite improvements across almost all index dimensions in recent years, the values are still below the EU average [82]. The Greek National Recovery and Resilience Plan (RRP) (2021–2027) earmarks EUR 7.1 billion (22%) for the digital transition, of which EUR 6.8 billion is intended to contribute to the realisation of the Digital Decade goals. According to the Digital Transformation Roadmap 2020–2025, one of the main challenges (No. 9) for Greece is the fact that not all citizens have equal access to digital technologies and the internet [83].

Rural areas, in particular, lag far behind in terms of digital connectivity, which is hampering the introduction of smart technologies into agriculture and rural development. There is evidence of a digital infrastructure gap in rural Greece, supported by national statistics, EU reports and academic research [82,84,85]. More to the point, digital connectivity between urban and rural areas can be analysed using broadband coverage indicators such as the availability of fixed broadband services, the availability of high-speed broadband networks and broadband speed. According to recent findings, Greece is in line with the EU average in terms of overall fixed broadband coverage at both national and rural level, with 97.2% and 93.7% of households covered, respectively. Meanwhile, in terms of Next-Generation Access (NGA) broadband, 86.4% of Greek households had access to high-speed broadband services by mid-2024, including more than half of rural households (56%). In addition, Greece had the lowest coverage among the Member States in the Very High Capacity Network fixed broadband (VHCN) category. Despite an increase of 7.7 percentage points, only 46.1% of Greek households had access to Fiber-To-The-Premises (FTTP)/Fiber-to-the-Home (FTTH) services in mid-2024, while coverage in rural areas stood at just 3.3% [85] (p. 126). According to a recent report, Greek average fixed broadband speeds are among the lowest in the EU and there is a clear urban-rural divide [82] (p. 122).

This disparity in broadband speeds between urban and rural areas is also evident in mobile services. In urban areas, the average fixed and mobile broadband speeds in the EU are 205.68 and 145.63 mb/s, respectively, while in rural areas they are 144.61 and 81.1 mb/s [86]. The significant digital divide can be observed not only between urban and rural areas, but also between rural areas in the EU. In particular, rural areas in northern European countries such as Denmark and Sweden benefit from extensive fibre optic infrastructure which provides for average speeds of over 100 mb/s and 85 mb/s, respectively. In contrast, in southern countries such as Greece and Cyprus, average fixed broadband speeds in rural areas are often below 40 mb/s. This situation is mirrored in mobile broadband speeds in EU rural areas: Northern countries such as Finland (60 mb/s), Sweden (55 mb/s) and Estonia (50 mb/s) benefit from extensive 4G and emerging 5G networks, while southern countries such as Greece (20 mb/s), Bulgaria (25 mb/s) and Romania (30 mb/s) suffer from low mobile broadband speeds. These differences highlight the ongoing challenges in achieving consistent broadband connectivity across the EU, especially in rural areas [86].

There is a clear divide in digital skills between urban and rural areas [84]. The Digital Skills Indicator (DSI), which measures people’s skills in various digital areas in the European Union, is significantly lower in rural areas than in urban areas. In 2021, just over a quarter (26%) of the EU population aged 16 to 74 reported having basic digital skills. The proportion of people living in cities was higher (33%), while the proportion of people living in rural areas with above-average basic digital skills was lower (20%). The Nordic countries show consistently high levels of digital literacy in all regions, including rural areas. Digital literacy in rural areas is also relatively low in Greece (11%), Hungary (14%) and Poland (14.3%). Despite efforts to improve digital literacy, the rural population continues to lag behind the urban population in acquiring basic digital skills. In recent years, the gap has remained significant, with rural areas consistently showing lower levels of digital literacy [87].

The new Common Agricultural Policy (CAP) 2021–2027 gives member states the opportunity to develop digitalisation strategies as part of their national CAP strategic plans. These strategies describe how each Member State intends to promote digitalisation in the agricultural sector and rural areas through the introduction of new technologies, the creation of digital infrastructures and the development of skills [88]. Digital technologies serve both as enablers for other CAP objectives, and as a means to improve the development of digital skills and bridge the digital divide [89]. The plans may include key actions to support research and development in agriculture, forestry and rural areas, digitalisation and smart agriculture through the development of digital technologies (AI, IoT, big data) in agriculture and the development of digital infrastructures in rural areas. In addition, they can promote the training of farmers and cooperation between farmers, researchers and policy makers through knowledge exchange and advisory services, and finally the networking of rural communities.

The European Innovation Partnership on Agricultural Productivity and Sustainability (EIP-AGRI) promotes interactive innovation projects that combine research and practise and address real challenges in agriculture. Since 2014, more than 3700 EIP-AGRI operational groups have been established and over 6600 projects are planned for the period 2023–2027. With the support of the CAP plans, the European Innovation Partnership [90] will reach a total of 6 million participants for advice, training and knowledge exchange or participation in innovation projects. For the previous period (until 2022), expenditure on such projects varied greatly from Member State to Member State. The Netherlands, Portugal and Slovakia show the highest percentage of RTD funding allocated to these activities at over 8–9%. In other countries, including Greece, Cyprus, the Czech Republic, and Romania, spending was minimal at less than 1%.

All in all, this discussion shows a clear difference between EU countries and between rural and urban areas. In most cases, Greece ranks at the lower end of the digital transition indicators. However, this national average mask significant internal disparities—particularly in rural areas and the agricultural sector—where access to digital infrastructure and technologies is uneven and, in many cases, limited.

5. Methodological Approach and Research Design

The analysis that follows is part of a broader research project examining the digital transition and the participation of diverse population groups [91]. Particular attention is paid to the digital transition’s effects on employment in agriculture, migrant labour and rural development. The study examines different forms of integration into the digital labour market, and seeks to capture the complexity of digitalisation in population groups with different socio-demographic characteristics, with a focus on local communities. Empirical research has been conducted in several rural areas, particularly in predominantly agricultural areas where a significant number of migrants work seasonally or permanently in agriculture. In many of these areas, agriculture remains the main source of household income [70].

The methodological approach adopted a mixed-method design that integrated statistical and cartographic analyses of available census data, an online survey, and a set of qualitative methods. The qualitative component was particularly important, as it combined different approaches to capture diverse opinions, experiences and practices, while also amplifying marginalised perspectives that might otherwise remain silenced [92,93]. In this paper, the cartographic analysis used absolute figures from the Hellenic Statistical Authority (ELSTAT), mainly from the 2011 and 2021 population censuses, supplemented by labour force and agricultural statistics. Based on these official datasets, a set of demographic and labour market indicators was calculated to capture structural dynamics in rural Greece. Spatial processing and cartographic outputs were produced using QGIS (version 3.44.1-Solothurn). Standard GIS procedures were applied, including data cleaning, value classification, and choropleth mapping at the NUTS3 regional level. Base maps and administrative boundaries followed Eurostat’s NUTS3 shapefiles. This methodological approach ensured transparency and reproducibility: the use of official ELSTAT data secured robustness, while the derived demographic, gender, and labour market indicators enabled regional and temporal comparability.

In this paper, the cartographic analysis was complemented by a qualitative component. Semi-structured interviews were conducted with farmers and agricultural experts to examine the transformations associated with the digital transition in agricultural production and the employment conditions of migrant workers. These interviews were combined with ethnographic observation in fields and villages, providing contextual insights into everyday practices and labour dynamics. In total, four key informants and three farmers participated in the interviews. Interviews with stakeholders lasted approximately one hour, while those with farmers were longer, averaging around two hours. All participants were male, reflecting the prevailing gender distribution in the agricultural sector across many rural regions of Greece, where most farmers and key industry actors are men. Participants’ ages ranged from their early 40s to early 60s, and their educational backgrounds included both secondary and tertiary levels.

Additionally, a focus group discussion on digital transition in the agricultural sector and rural areas was held. This event brought together eight participants, including agronomists, agricultural policy specialists, and professionals from the agricultural supply chain, such as providers of plant protection products. The participants were active in various agricultural regions across Greece, with a particular focus on the rural areas of Attica, Central Greece, Crete, and the Western and Southern Peloponnese. The discussion centred on the impact of digital technologies on agricultural production, labour dynamics, and the restructuring of rural areas. Although the number of interviews was limited, the study emphasises in-depth qualitative insights rather than statistical generalisation. Participants were selected for their expertise, and findings were triangulated with ethnographic observations in the rural research sites in Central Greece, to enhance validity. Despite the relatively small sample size, the results from both the interviews and the focus group are consistent with findings reported in other rural regions of Greece, notably the Western and Northern Peloponnese [94], indicating that the trends observed in this study may reflect broader patterns within the Greek agricultural sector.

The thematic analysis of the collected material reveals that the opportunities and challenges of digitalisation unfold at two main levels. At the micro level, it is about the experiences, adaptations and innovative strategies of farmers and rural communities integrating digital technologies into their practise. At the macro level, the discussion is characterised by a broader, often top-down narrative that presents the digital transformation of rural life as not only necessary, but also environmentally sustainable and, to some extent, inevitable in the context of climate change. This dual lens enables a comprehensive examination of digitalisation that goes beyond its technical and economic aspects. It brings into focus the social, cultural, and political dimensions of digital change, highlighting how these dynamics vary across different rural contexts.

6. Interrogating the Data: An Analytical Approach

6.1. Digital Transition in Greek Agriculture: Adoption, Farm Size Dynamics, and Sectoral Implications

Although discussions about digital transition as part of the ongoing modernisation of Greek agriculture began more than a decade ago, experts in the field have observed that the pace of change has accelerated significantly in the last five to seven years. However, this change is still uneven across different types of farming and agricultural sectors. The interviews and focus group have shown that, while the digitalisation of agriculture has many facets—including smart farming, precision agriculture, and Agriculture 4.0—these terms, though conceptually different, are often used interchangeably by farmers and the general public [50]. This confusion reflects a lack of clear understanding or standardised terminology, which can hinder the effective adoption and integration of these technologies. In addition, as the theoretical discussion in this paper reveals, differences in technological literacy, infrastructure and access to digital tools further exacerbate the uneven adoption of digital technologies in Greek agriculture.

According to some participants, digitalisation in the broader sense has been most prominent in greenhouse cultivation, particularly in so-called “active greenhouses”—large-scale operations where nearly every process, from spraying to temperature control, are managed digitally. From this perspective, the focus of technological adoption in agriculture is currently primarily on prevention and the optimised use of inputs, thus contributing to the preservation of biodiversity and the protection of the environment. Equally important is the integration of various technologies that enable data-driven decision-making and the implementation of effective targeted measures. Meteorological stations form the basis of this system by providing the environmental data required for planning. Building on this, drones are used—when permitted—to optimise agricultural use, particularly of water and pesticides, and to enable more efficient and precise spraying methods. In addition, specialised machinery that can perform soil analysis enables site-specific application of fertilisers, promoting a more balanced and sustainable use of nutrients. Technologies such as electronic insect traps also contribute to better pest control by providing real-time data on insect population dynamics. This helps farmers to plan their spraying more accurately, increasing the effectiveness of treatments while reducing the unnecessary use of chemicals. In addition to these more general tools, advanced technologies such as GIS and satellite imagery are also being explored, more often in collaboration with universities and research organisations. These systems are used to create colour-coded field maps showing problem areas—such as areas affected by pests, nutrient imbalances or diseases—allowing for highly targeted intervention. New technologies, such as autonomous robots are still in the early stages, but promise to further revolutionise crop management. These robots are designed to identify and treat specific areas that are infested with weeds or pests, eliminating the need for the blanket spraying of large areas. This shift towards localised, precision-based approaches represents a broader shift in EU policies aimed at sustainability which seek to reduce input costs, improve resource efficiency and minimise the environmental impact [6]. The aim is therefore to reduce the costs of crop management, improve efficiency and, ultimately, to protect the environment. In parallel, the integration of data-driven decision-making processes and sensor technologies is gaining momentum, enabling real-time monitoring and precise intervention in agricultural practises—while also incorporating and complementing other forms of knowledge such as experiential, local and traditional agricultural expertise [95]. This change reflects a broader effort to balance productivity with sustainability in Greek agriculture, aligning at least in principle, with both economic needs and environmental priorities.

This digital transition has wider implications for the agricultural sector in general which, as various interviewees state, may ultimately benefit both the farmers themselves and consumers. Often, the role digital tools play in improving product quality and environmental sustainability is emphasised, marking a shift towards practises that allow Greek farmers to access more competitive, higher-value markets. The focus is on the spread of advanced agronomic practises that were previously common abroad and are now becoming accessible in Greece, offering benefits to both the farming industry as a whole and to individuals in terms of efficiency, product differentiation and market reach. For instance, one interviewee argued: “Τhe farming industry in general, (…) there seems to be support for advancing methods and practices that lead to better product quality, especially in terms of organoleptic characteristics. That is, we’re seeing better fruit size, better taste. There’s also improved protection for the fruit from entomological, mycological, and nutritional issues. (…) At the same time, we’re seeing the application of methods that were widely used abroad years ago and are now becoming feasible in Greece. This gives us a competitive advantage, and it means that the cost of production can eventually be offset more effectively by the resulting benefits. The same applies for producers. What holds true for the sector also applies to the individual farmer. They can bring a more competitive product to market, potentially accessing markets that don’t currently favour Greek products.” (Interview 2c).

At the same time, it is important to emphasise a significant differentiation in the adoption of digital technologies, both in terms of farm size and type of production—whether intensive or extensive. As a policy expert argued: “There is significant variation in the path of digital transformation; the size of the farm is a decisive factor in whether a producer will be able to participate” (Interview 1c). Interestingly, both larger farms and capital-intensive small farms seem to invest more actively in digitalisation, compared to medium-sized farms. It is worth noting that both large and small farmers, who produce intensively, seem to show greater awareness and willingness to invest in digital tools and technologies, but for different reasons. Larger farms often seek innovation to optimise their scale and efficiency, while capital-intensive smaller farms see digital solutions as a way to innovate and remain competitive. There is a complex relationship between farm size and farmers’ mentality, which can either favour the introduction of digital technologies or pose obstacles to digitalisation. Large farms are more likely to embrace technological innovation, as these farmers are well aware of the cut-throat competition in agricultural markets. For their part, small farms with an intensive focus are looking for better ways to utilise their resources and technologies, since these promise improved production despite the high economic risk involved. Finally, at present, medium-sized farms are often more inclined to maintain their production capacities using conventional technology and pursue more defensive strategies vis-à-vis digital change.

6.2. Ageing Populations, Evolving Identities, and the Challenge of Digital Literacy

Inevitably, the socio-demographic profile of the Greek farmer engaging in the digital transition emerges as a prominent theme in the interviews. This aspect becomes especially relevant when participants are asked to describe the typical user of digital technology in Greek agriculture. One interviewee noted: “The profile of the farmer who uses digital technologies in Greece today—based on age and educational level—is male, under 50, and with an above-average education. They are not agronomists, but the user definitely has an entrepreneurial or business-oriented profile.” (Interview 1c). This observation reflects a broader trend where relatively younger, more educated and business-oriented individuals seem to be more inclined to adopt innovations in the sector, often seeking to modernise operations and gain a competitive edge. At the same time, the use of digital technologies in agriculture also leads to farmers taking a different approach to agricultural tasks. The requirements in terms of agricultural knowledge are also shifting, as the farmer no longer needs to personally determine the optimum time for spraying or irrigation. The farmer no longer has to make decisions manually, as the system provides this information automatically.

“Young farmers can generally [use the technology]. The real issue is the mentality; that’s what needs to change. In practice, yes, you can show someone how to use a manual, how to operate the drone, (…) just like we used to do with tractors and so on. But what becomes clear on a deeper, more social level is the mindset. There needs to be a shift in how Greek farmers think about production and the process of farming.” (Interview 2c).

In other words, although younger farmers have the technical skills to use digital tools such as drones and automated systems, the main obstacle remains a deep-rooted mentality that in some cases resists change. The emphasis is on the need for a cultural change in agricultural practises, as the introduction of technology alone is not enough, if it does not also change the way some Greek farmers perceive and approach production.

“In the end, the final product isn’t sold at a higher price than it would be with more conventional practices. It’s not better paid. But what many haven’t understood is that, if you look at the entire cultivation cycle from start to finish, the product you produce, and the yield you can achieve per stremma, show that you actually come out ahead, even if the market price doesn’t change. That is, both the quality and the quantity of the product by the end of the cultivation period can—depending on the crop—benefit the farmer. But this is very difficult for most people to grasp, because the average farmer doesn’t have the mentality to sit down and assess things properly. No one—or at least not the vast majority—takes the time to calculate their expenses from start to finish and finally ask themselves: “So, what did I gain in the end? What did I achieve?” A proper ROI—return on investment—as we call it in practice. (…) the farmer still tends to think: “I spray the way I always have, or I apply something, and I want to see results the same day.” That’s still the dominant mindset. Even the younger generation—who are theoretically better equipped to handle the technology side of things, and certainly more so than an 80-year-old farmer—still don’t show a fundamentally different mentality.” (Interview 2c). In other words, there is a critical mismatch between technological potential and perceived economic benefit, as farmers often fail to evaluate yields over the entire crop cycle. Despite the availability of precision technologies and their ability to improve both yield and product quality, the prevailing short-term mindset of growers remains a major barrier to adoption. Although there is an obvious shift in younger generations of farmers, the persistence of traditional expectations—such as instant results—reflects a broader cultural resistance to the long-term, data-driven thinking required for digital transition.

6.3. Labour, Migrants and Digital Transition in Agriculture

For all respondents, labour is considered an indispensable factor for the survival and economic success of the farm—especially in labour-intensive cultivations, where just-in-time labour is crucial during peak periods such as the harvest or picking season. The availability, cost and reliability of labour have a direct impact on the overall productivity, efficiency and profitability of the farm. A substantial body of research has shown that migrant labour has served as a crucial catalyst in Greek agriculture since the 1990s, contributing to the survival, expansion and gradual modernisation of farms [70,96,97,98]. However, the shortage of agricultural labour is becoming increasingly acute, with the problem worsening significantly over the last two years. This increasing scarcity threatens the viability of certain crops and exacerbates planning and operational challenges across the sector. As an interviewee argued: [Labour scarcity] is “a huge, huge issue—the last two years, across all sectors. Everywhere. There isn’t a single producer—from the Peloponnese to Northern Greece, excluding the islands—who is not in the same position. Ask any producer ‘What’s the biggest problem in your cultivation?’, and they’ll reply ‘the lack of workers’. Absolutely. Everything else—diseases, pests, nutrition, exports, marketing—they’ll say, I’ll manage. I’ll spray, I’ll take care of it, I’ll find a way. But labour? That’s different”. (Interview 2c).

In a similar vein, another interviewee explains how better-paid opportunities in other sectors of the economy, both within and beyond rural areas, can leave producers vulnerable and unable to plan effectively: “Let me tell you something specific, so you can understand the magnitude of the situation and the sense of desperation right now. A producer with 60 stremmata of greenhouse peppers had been paying two skilled workers €30 a day for years. At one point, the wage increased to €45. And then, overnight, they left to work in construction in Lefkada, because a construction project there needed to be completed quickly—for €80 a day” This caused a shock among daily wage labourers at the time. How can I plan anything on the farm, when the people I rely on are suddenly leaving me?” (Focus group participant FGR_2).

However, labour shortages are not only a challenge for farms; they also affect a wide range of activities across the agri-food sector in rural areas. In regions where the population is shrinking and ageing, the impact of this shortage can be particularly severe, threatening the sustainability of the local economy, food processing and rural development in general. For instance, one participant highlighted: “This problem, apart from being very serious for agricultural farms, is also significant in food processing units. It extends to industries, as well. For example, in Ilia [Western Greece] this year, the two tomato processing factories had no workers. For the first time in twenty years, they had to bus workers in from thirty or forty kilometres away—and they still couldn’t find any” (Focus group participant FGR_3).

Farmers, depending on the characteristics of their farm and their capacities, elaborate different strategies to mitigate the challenge of labour shortages. In some cases, the lack of labour has forced growers to cut back on certain crops, especially those that require intensive manual labour. In others, some growers are switching to less labour-intensive crops or even reducing the total area under cultivation. As one interviewee stated: “Some crops are being reduced—for example, tomatoes—which require a lot of manual labour for tying, spraying, and monitoring due to their cultivation method. These are now being planted on fewer stremmata, or not at all, and being replaced with crops that need less labour. (…) I have a friend who manages about 50 to 100 stremmata. Last year, he didn’t plant 25 of those stremmata at all. He simply decided not to, and reduced his crop (…). So that’s one part of it. The other is that producers are increasingly doing more of the work themselves. They’re stepping in, trying to cover the gaps. It’s a dead end” (Interview 2c).

Inevitably, the discussion about the shortage of labour available in agriculture—and in rural areas in general—brings to the forefront the notion of replacing human labour with technological solutions. While digitalisation in agriculture and agricultural production has indeed led to a reduction in the use of labour in some cases, the process is still a long way from completely replacing human labour with machines [59]. The use of technology complements manual labour rather than making it redundant, especially for tasks that require adaptability, local knowledge, or dexterity—such as harvesting delicate products like strawberries. Therefore, digital tools currently serve more as a tool for increasing efficiency rather than completely replacing labour in agriculture. As one participant explained: “Of course, food processing units experiencing labour shortages responded quickly by investing in equipment—purchasing robotic machines for transport, packaging, and standardisation. This is relatively easy for a processing unit or a cooperative to do. But for a farm producer? In the field, it’s not so easy to quickly replace one or two workers with robotic machinery. Of course, it may not be long before that becomes more feasible.” (Focus group participant FGR_3). While another participant added: “It’s also about farm size, I think. A producer with a large farm can adopt such technologies—especially in greenhouses—and we’ve clearly seen this happening abroad. Indeed, the need for digital transition is partly driven by labour shortages. However, in our country, small producers won’t be able to implement these solutions so easily. So, the need for workers in the fields, particularly migrants—to harvest, transport, and so on—is unlikely to change, given the demographic and economic characteristics of Greek rural areas. This may only alter in a few specific categories of farms. For the rest, labour shortages will continue to be an issue. And of course, in my view, there’s no real chance that these people—the migrants—will be trained in anything related to digital skills. It has never been the goal of farm owners to invest in that kind of training for migrant workers.” (Focus group participant FGR_4).

There thus appears to be a structural divide in the digital transition in agriculture and rural areas more broadly: While processing units and large-scale farms are more capable of adopting automation, smaller farmers still rely heavily on manual labour. However, both large and smaller farms still rely on permanent and/or seasonal migrant labour depending on the scale, the type of tasks required on the farm, and the crop cultivated. The assumption that digitalisation can universally solve the labour shortage overlooks the geographical diversity of agriculture and the deep inequalities in access to capital, technical knowledge, and scalability. Furthermore, the limited digital literacy of farmers, and the systematic exclusion of migrant workers from digital training pathways, illustrates how technological change reinforces rather than dismantles existing digital divides and labour hierarchies and perpetuates dependence on low-skilled, precarious labour in key segments of the agri-food chain.

7. Conclusions

The paper examines the current landscape and dynamics of digital change in terms of demographic capacity, infrastructures, agricultural production and labour migration in rural Greece. Despite the high expectations of digital technology and the socio-technical imaginary of the so-called “digital transformation”, digital change in rural Greece faces significant challenges and obstacles due to depopulation, socio-economic inequalities, the lack of digital infrastructures, and the low digital literacy of the rural population. The existing digital divide between urban and rural areas, and between different rural areas in Greece, is highlighted by EU indicators and statistics. The digital divide reflects not only geospatial differences, but also individual and group characteristics that affect the ability of different population groups to adopt and fully utilise digital tools. The demographic deficit in rural areas is evident in depopulation, ageing, and gender imbalances, which progressively reduce the number of younger, often better-educated people most able to adopt and spread digital practices. The concept of digital capital can be used to capture the low concentration and accumulation of digital infrastructure and also the low capacity of the rural population to upgrade their digital skills.

Greece’s path to economic recovery, which emphasises “growthless employment” based on low-wage employment (for both migrants and non-migrants), stands in stark contrast to the widely celebrated digital transition. Both the public and policy makers present digital transition as a necessity in the face of holistic climatic, technological and global changes. Digital tools are usually constructed and presented as facilitating social change, while also being integrated into progressivist narratives that propose win–win situations. The promises of digital technology often result in the neglect of the institutional, infrastructural, and socio-economic preconditions required for its adoption and valorisation. In recent discussions, many rural areas are described as “places that don’t matter” or “areas left behind”, given the limited attention they receive from regional or central administration, and their inhabitants feel dissatisfied and unfairly treated as a result. Yet the question remains whether this “left behindness” can viewed as a problem to be addressed or a stigma of deprivation which requires intervention.

In addition, digital technology fosters a range of improvements in communications, service delivery, surveillance practises and remote working, but it also brings with it a range of socio-economic, political and cultural demands. Investment in physical and social infrastructures is seen as essential, as is the acquisition of digital skills and competences that are constantly updated and improved, along with the adoption of cultural relativism and cosmopolitanism combined with the rapid exchange of information and the ability to act in a changing socio-cultural environment. In this context, the digital transition in agriculture and rural areas implies a broader change that affects attitudes, values, behaviours and social practises. Digital transformation, whose full implementation will have a growing impact on energy consumption, as currently pursued, will lead to increasing social and spatial inequalities. Social polarisation and deprivation will affect already marginalised rural areas, while social segregation will become more evident in the more prosperous regions.

The combined impact of platformisation and datafication in agriculture and rural areas has raised significant concerns about the changes triggered by the processes of digital transition. It is important to create a framework for the data sovereignty of farmers and communities to counter the data ownership of large agricultural and digital corporations. The emancipation and autonomy of farmers and communities must be strengthened and supported, while, to ensure a fair digital transition, efforts must be made to prevent a concentration of power. A more nuanced approach to the increasing digital dependency on digital platforms and big data should be developed, affording better access to basic citizenship rights and promoting fairness in rural areas.

Finally, the research design underpinning this paper’s critical reading of apparent digital changes in rural Greece requires support from other local and regional studies that examine improved policies for revitalising rural areas, based on enhanced public digital infrastructures that enable business relocation. The digital transition should aim to improve the quality of life in rural areas and facilitate living and working there, eradicating social exclusion and segregation.