Digital transformation affects economies and societies in complex and interrelated ways. A solid mix of foundational, information communication technology (ICT) and complementary skills help empower individuals to navigate an increasingly digital world, participate in the global economy and compete in job markets. With the breathtaking technological progress in automation, robotics and artificial intelligence combined with the power of data, businesses rely more than ever on ICT specialists to develop applications and manage networks. There is also a rising premium placed on skills such as communication, emotional intelligence and problem solving in today’s job markets. Staying updated with future skills needs is an ongoing process and requires engagement of individuals and businesses in up- and re-skilling activities. Governments have a key role in helping them to develop and use skills effectively to thrive in an increasingly interconnected and rapidly changing world.
OECD Digital Economy Outlook 2024 (Volume 2)
Abstract
The effective use of digital technologies and data requires a wide range of skills that need to be acquired, maintained and upgraded throughout a person’s lifetime. Individuals of all ages need to be well equipped to make the most of digital technologies The young need to be able to use digital technologies effectively to learn and prepare for the world of work. The middle-aged must continually up- and re-skill as the demand for skills changes. Finally, older populations must learn how to live in a highly digital economy and society or risk being left behind.
The acquisition of skills needed in the digital age takes place through multiple channels, at various places and at different times. Digital technologies play an increasingly prominent role in education and training. The use of generative artificial intelligence (AI) might revolutionise teaching and learning, changing the ways in which students explore topics, ask questions and develop understanding. Stronger connectivity facilitates “flipped” classrooms where students are introduced to content at home and practise working through it at school. Meanwhile, teachers rely on different mobile applications to communicate with parents. As learning goes digital across the globe – a phenomena accelerated by the COVID-19 pandemic – an enormous innovation potential that had been dormant in education systems has come to the fore in many countries (OECD, 2021[1]).
The pandemic further accelerated the pace of digital transformation, shifting an increasing number of activities and services from the physical world on line. In the labour market, teleworking became a common feature in many workplaces. While the base is relatively small, online platform workers (OECD, 2019[2]) represent an increasing share in the overall workforce in many OECD countries (Urzì Brancati, Pesole and Fernández-Macías, 2020[3]; Kim, 2021[4]; Anderson et al., 2021[5]).
Trends such as globalisation and advances in AI are also changing the demands of the labour market and the skills needed for workers to thrive (Bakhshi et al., 2017[6]). Individuals rely even more on their uniquely (so far) human capacity for creativity, initiative and the ability to “learn to learn” throughout their life (OECD, 2019[7]; Samek, Squicciarini and Cammeraat, 2021[8]). In parallel, as individuals live and work longer, they also face more frequent job changes and the risk of skills obsolescence (OECD, 2019[9]).
Governments play an important role in fostering acquisition of skills at all ages, facilitating just transitions in the labour market and incentivising businesses to invest in their workers. Building on the OECD Skills Strategy (OECD, 2019[10]) and the OECD Jobs Strategy (OECD, 2018[11]), this spotlight presents trends and raises policy challenges that need to be addressed to prepare for the skills needs of tomorrow. It first sheds light on the range of skills needed to live and work in a highly digital economy and society. It also discusses changes in the demand for skills from the business perspective. Finally, it explores how individuals, businesses and governments can best respond to the changing skill needs raised by digital transformation, highlighting the need to closely monitor evolving AI capabilities. As the field of AI develops further in the years to come, possibly very rapidly, understanding what AI can and cannot do will be increasingly important to inform responsive policies (OECD, 2023[12]).
In a fast-moving digital landscape, individuals need a wide range of skills to thrive. These skills can be considered as follows: first, foundational skills that enable all people to participate in a digital economy and society; second, basic skills level – such as basic computer skills, communication and information search skills and proficiency in using office productivity software; and advanced skills (e.g. AI skills, software programming). In addition, complementary skills such as teamwork, autonomy, problem solving, creative thinking, communication, collaboration and emotional intelligence enable high-performance work practices and a strong ability to continue learning.
Foundational skills are a prerequisite for the effective use of digital technologies
Foundational skills such as in science, numeracy and reading are essential for everyday activities (OECD, 2019[14]). Evidence from the first round of the OECD Programme for the International Assessment of Adult Competencies (PIAAC) shows that high levels of proficiency in literacy and numeracy, and in problem solving in digital environments, go hand in hand. On the other hand, low levels of proficiency in literacy, and particularly in numeracy, may be significant barriers to using ICT applications to manage information effectively (OECD, 2013[15]).
Figure 1.S.1 shows the share of top performers1 in science, mathematics and reading in 2012 and 2022. These students can draw on and use information from multiple direct and indirect sources to solve complex problems, and can integrate knowledge from across different areas. Such exceptional skills can provide a significant advantage in a competitive, knowledge-based global economy as they allow adapting to the scale, speed and scope of digital transformations. Between 2012 and 2022, the share of top performers in science, mathematics and reading decreased in most countries with available data. Despite a drop of about four percentage points in 2022, Japan remained the country with the highest share of top performers (7.6%), followed by Korea, Australia and New Zealand.
Top performers in science, mathematics and reading, 2022
Source: Authors’ calculations based on OECD (2024[16]) PISA 2022 Database, https://www.oecd.org/pisa/data/2022database (accessed on 11 March 2024).
Recent OECD evidence also shows that individuals well equipped with strong foundational skills use digital technologies in a diverse and more complex way (OECD, 2019[17]), and also have a more positive attitude towards lifelong learning (OECD, 2021[18]). Experts emphasise the importance of deriving pleasure from reading at an early age as a marker for their adulthood (Sanacore, 2002[19]). Cross-country evidence from PISA survey shows that 15-year-old students with higher reading skills generally better distinguish facts from opinions on line, a critical skill to navigating the digital environment (OECD, 2021[20]).
As the share of academic all-rounders (i.e. top performers in science, mathematics and reading) has been decreasing over time, the performance of AI systems has been advancing quickly in tasks engaged by students across the board. This includes core reading, mathematical and scientific reasoning tasks commonly taught to 15-year-olds at school (OECD, 2023[21]; OECD, 2023[22]).
ICT skills strengthen the ability to cope with change and keep learning
In addition to foundational skills, individuals also need basic ICT skills to prosper in a digital economy and society. These include basic computer skills, communication and information search skills, as well as proficiency in using productivity software such as operational and information-navigation. Such skills enable access to information, facilitate communication, support civic participation and enhance employability and well-being (Burns and Gottschalk, 2019[23]; OECD, 2022[24]; OECD, 2019[17]). Yet, according to data from the first round of PIAAC, 25% of adults on average in OECD countries lacked the most basic digital skills and another 14% could only perform basic functions on a computer or other digital device (Verhagen, 2021[25]).
A more advanced level of ICT skills (e.g. software programming, AI skills) strengthens the ability to cope with change (e.g. in work organisation) and keep learning (e.g. new programming languages). It also allows people to leverage the wealth of open-source information available on line.
Programming skills are highly versatile and applicable in a wide range of fields. They enhance problem-solving abilities, promote creativity and innovation, and offer numerous career opportunities. Additionally, in today’s technology-driven world, a basic understanding of programming is increasingly valuable for individuals in various aspects of life. The skill is useful for troubleshooting technical issues or changing the privacy settings of a personal device, building a customised website, analysing personal expenditures to make informed decisions about spending and saving, etc. According to the OECD ICT Usage by Households and Individuals data, only about 7% of 16-64 year-olds in OECD countries reported having written computer code in 2021.
More specifically, AI skills refer to the abilities and knowledge required to develop or undertake an advanced use of AI systems. Some key AI skills include programming, understanding and implementing machine-learning algorithms; data mining and data processing; deep learning; natural language processing; and understanding computer vision concepts, such as image processing and object detection (OECD, 2024[26]).
Complementary skills are becoming as essential as cognitive skills
When combined with a minimum level of ICT skills, complementary skills can significantly enhance an individuals’ effectiveness and productivity in digital environments. Complementary skills include teamwork, autonomy, problem solving, creative thinking, communication, collaboration, emotional intelligence and a strong ability to continue learning. These are valuable assets across sectors and increasingly sought in today’s technology-driven world that enables high-performance work practices in the digital age. The OECD’ Skills for 2030 project identifies two types of complementary skills. “Meta-cognitive skills” include critical thinking, creative thinking, learning-to-learn and self-regulation, while “social and emotional skills” include empathy, self-efficacy, responsibility and collaboration (OECD, 2019[7]).
Demographic and societal changes such as ageing populations increase the demand for a variety of occupations related to health care. These require both scientific skills, and social and emotional skills, such as caring, sociability and respect (OECD, 2021[27]). In addition, social and emotional skills, such as empathy, self-awareness, respect for others and the ability to communicate, are becoming essential as classrooms, workplaces and societies become more ethnically, culturally and linguistically diverse.
In parallel, increasing reliance on AI and sophisticated machines may lead people to devalue the work of others. Indeed, some researchers are convinced this devaluation is already occurring (Turkle, 2017[28]). If this observation is generalised, then it will be increasingly important for people to learn how to recognise the value of their own humanity and that of others (Putnam, 2000[29]). Valuing the contributions of people to society is necessary not only for individual and societal well-being, but also for the health and relevance of institutions (Berkowitz and Miller, 2018[30]).
Finally, achievement at school also depends on social and emotional skills, such as perseverance, self-control, responsibility, curiosity and emotional stability. Some social and emotional skills are a prerequisite for successful participation and performance in academic settings. In other words, poor social and emotional skills can impede the development and use of cognitive skills (OECD, 2019[7]).
The introduction of new digital technologies in businesses changes the nature of work by reducing the demand for routine jobs and increasing the demand for ICT specialists in the labour market. Strong foundational skills are needed for the digital economy, including basic skills to live and work in increasingly digitalised environments. These complement advanced digital competencies, such as software programming and skills related to the design and deployment of AI systems.
This section discusses the shortage of ICT specialists through labour market indicators on occupations, job vacancies and wages. It draws on official statistics but also some private-sector data to provide a more complete picture with timely metrics. It then focuses on small and medium-sized enterprises (SMEs) for which investments in skills are a longstanding challenge. Finally, the section discusses the potential impact of digitalisation on skill demand by considering evidence on evolving AI capabilities and the exposure of different job tasks to automation.
The demand for ICT specialists is growing
The introduction of new digital technologies in businesses is changing the nature of work. Digital technologies are reducing the demand for routine jobs and increasing the demand for ICT specialists needed to programme, develop applications and manage networks. A high number of job vacancies for ICT specialists have made them among the most dynamic occupations in recent years. Yet shortages of ICT specialists also persist in several sectors (Censorii, 2021[31]). In 2021, more than 60% of EU enterprises that recruited or tried to recruit ICT specialists struggled to fill vacancies. In response, the European Commission announced an ambitious target for 20 million IT specialists within the European workforce by 2030 (European Commission, 2023[32]).
Spiezia, Koksal-Oudot and Montagnier (2016[33]) propose several proxy indicators based on occupations, job vacancies, vacancy duration and wages to assess potential shortages in a given occupation on the demand for ICT specialists. Based on labour force statistics, the OECD’s Going Digital Toolkit shows that ICT specialists in 2021-22 accounted for 8% of all jobs in Sweden and Israel, about 4% in EU27 and only 1.4% in Türkiye.
Table 1.S.1 displays the most in-demand jobs on LinkedIn™ where “Salesperson” ranked first in Q2 2024. More broadly, customer service and sales roles dominate this list, especially in retail, which accounts for four of the top ten jobs. For recruiters, this shift underscores the rising premium placed on complementary skills such as communication, emotional intelligence and problem solving in today’s job markets. It also suggests a need for talent professionals to focus on defining, assessing and evaluating these skills, as service-oriented jobs continue to attract higher demand (Lewis, 2024[34]). Interestingly, the only ICT specialist occupations on this list are software engineers but they rank third at a stable place as compared to the previous quarter.
Roles with the greatest number of paid LinkedIn job posts, Q2 2024
Note: The results are based on global LinkedIn data on all premium job posts from January 2024 up to June 2024 (inclusive). The analysis excludes roles with fewer than 1 000 job posts in either quarter and roles for which most job posts come from a single company. The most in-demand jobs are those with the highest number of job posts in the most recent quarter (1 April - 30 June 2024).
Source: (Lewis, 2024[34]).
Alternative sources of information can be leveraged to provide timely information about trends in international labour demand, in particular for rapidly evolving fields like AI (OECD, 2024[35]). Based on Lightcast™ data on online job vacancies, AI-related online vacancies represent a small but growing share of all vacancies posted on line (Borgonovi et al., 2023[36]; Green and Lamby, 2023[37]; OECD, 2023[38]). Workers with AI skills are particularly in demand due to the growing influence of AI in various industries such as health care, finance, manufacturing, automotive, and entertainment (Borgonovi et al., 2023[36]) and they earn relatively high wages (OECD, 2023[39]).
Increases in real wages for the occupations using these skills intensively represent another indicator of labour shortage of specific skills. If ICT skills are scarce in the labour market, firms have to pay higher real wages to attract workers with such skills. Changes in real wages, however, are not always a good measure for skills shortage. On the one hand, skill shortages may not translate immediately to higher wages due to adjustment lags (e.g. collective wage bargaining). On the other, wages may increase as a result of both industry-specific and economy-wide productivity shocks. Therefore, an increase in real wages may be regarded as a sign of skills shortage only if: i) it is persistent over time; ii) it exceeds the increase in labour productivity; and iii) it is larger than in the other sectors of the economy (Spiezia, Koksal-Oudot and Montagnier, 2016[33]).
Figure 1.S.2 compares the average growth rates of wages – relative to average labour productivity – in ICT services and the total business sector2 over 2013-22. In about two-thirds of the 28 countries for which data are available, wages grew more in ICT services than in the total business sector. In the remaining countries, differences in wages growth were limited, i.e. less than 1% a year. These trends confirm that the demand for ICT specialists is growing faster than supply in European countries.
Changes in wages relative to labour productivity 2013-22, annual averages
Source: Authors’ calculations based on (Eurostat, 2023[40]) Annual National Accounts Statistics, https://ec.europa.eu/eurostat/web/national-accounts (accessed on 5 March 2024).
For SMEs in particular, investments in ICT skills are a longstanding challenge (OECD, 2021[41]). In Europe, the percentage of large enterprises employing ICT specialists (76%) was more than five times higher in 2020 than that of SMEs employing ICT specialists (14%) (Censorii, 2021[31]). This gap can be explained by examining the broader challenges faced by small firms that struggle to offer competitive salaries and benefit packages that can attract experienced ICT professionals.
Furthermore, SMEs often lack brand recognition or visibility in the job market compared with larger companies. This can make it harder for them to attract talent in competitive areas like ICT skills. In the case of niche skill requirements like cybersecurity, AI or specific programming languages, finding candidates with the right combination of skills and experience can be even more challenging.
As a result, SMEs often outsource ICT functions to larger organisations that often offer well-established career paths, mentorship programmes and opportunities for professional growth. SMEs, especially very small ones, may struggle to provide the same level of career advancement prospects, which can limit their attractiveness. Finally, lack of formal training programmes and uncertain job security may explain part of the difficulties to attract ICT talents.
Technological progress in AI and robotics will further transform skills demand
Digital transformation will have further implications for skills demand as the capabilities of AI and robotics continue to advance and transform many tasks performed by humans. Several recent studies explored the potential of AI to automate work tasks across jobs and occupations. Based on evaluations from computer scientists, these studies identify tasks that machines are unlikely to perform within a sample of occupations or jobs. The studies then develop a model of automatability and predict how susceptible jobs across the entire economy are to automation. According to one study, nearly 14% of jobs in OECD countries were likely to be automated in 2019, while 32% were at high risk of being partially automated (Nedelkoska and Quintini, 2018[42]).
More recently, based on data across 21 OECD countries over 2012-21 (Georgieff and Milanez, 2021[43]), all countries experienced employment growth over the past decade with no evidence for net job destruction at the broad country level. Within countries, however, employment growth was much lower in jobs at high risk of automation (6%) than in jobs at low risk (18%).
Low-educated workers, already more concentrated in high-risk occupations in 2012, have become even more prominent in these occupations. Yet, the low growth in jobs in high-risk occupations has not led to a drop in the employment rate of low-educated workers relative to that of other education groups. This is largely because the number of low-educated workers has fallen in parallel with the demand for these workers.
Looking ahead, the risk of automation will increasingly fall on low-educated workers. Moreover, the COVID-19 crisis may have accelerated automation, as companies reduce reliance on human labour and contact between workers, or re-shore some production (Georgieff and Milanez, 2021[43]). Importantly, these findings highlight that jobs requiring lower skill levels face the greatest automation risk, implying a decrease in automation vulnerability with higher educational attainment.
Other studies have investigated the potential impact of AI by focusing on skills rather than job tasks. For instance, Lassébie and Quintini (2022[44]) exploited an original dataset on the potential automatability of approximately 100 skills and abilities gathered through a survey of AI experts. Their findings show that skills related to complex problem solving, high-level management and social interaction remain hard to automate given the state of technological developments. However, the study also shows that some skills and abilities previously identified as “bottlenecks” to automation are more susceptible to automation with recent advances in AI. These skills include knowledge of fine arts and some psychomotor abilities such as the ability to work in cramped workspace and awkward positions, finger dexterity and manual dexterity.
In parallel, the authors also show that recent advances in AI increase the demand for several skills required in high-skilled jobs susceptible to automation. These include reading comprehension, deductive and inductive reasoning, fluency of ideas and scheduling skills typically associated with high-skilled occupations.
As a result, most jobs at highest risk of automation are not at risk of being entirely automated. This is because they involve bottleneck tasks and even jobs preserved from the risk of disappearing involve a small set of automatable tasks. For example, only about 18-27% of skills and abilities required by the most at risk occupations are highly automatable and these occupations still require around 5% of bottleneck skills. In other words, even the occupations at highest risk of automation are not likely to be entirely substituted by automated solutions. Instead, the work organisation will have to be adapted and workers in these jobs may need up- and re-skilling as technologies replace workers for several tasks (Lassébie and Quintini, 2022[44]).
In parallel, a survey of workers and employers in the manufacturing and financial sectors in Austria, Canada, France, Germany, Ireland, the United Kingdom and the United States aimed to capture perceptions of the current and future impact of AI on the workplace (Lane, Williams and Broecke, 2023[45]). It showed that as the AI becomes more pervasive, individuals may need a broader range of (social) skills to work with such technologies. This finding is consistent with previous literature, which also suggests the adoption of AI requires not just AI expertise but also (or rather) skills in creative and social intelligence, reasoning skills and critical thinking (OECD, 2019[7]; Samek, Squicciarini and Cammeraat, 2021[8]; Squicciarini and Nachtigall, 2021[46]).
Finally, using alternative data sources such as online job postings, Manca (2023[47]) explored the impact of AI on labour markets. It asked six questions, including those related to the impact of such technologies on the demand for “routine” (i.e. general administrative and clerical tasks) and “non-routine cognitive” skills (i.e. creativity, problem solving). The analysis suggests that AI and routine skills are not complementary. AI is adopted more widely, more demand for AI skills is likely to be associated with less demand for routine skills, all else being equal. On the contrary, the relationship between AI skills and high-level cognitive skills appears to be positive.
To thrive in an increasingly digital economy and society, and a rapidly evolving business environment, individuals need to continually acquire new skills. This requires flexibility, openness towards lifelong learning and curiosity. This section shows how individuals, businesses and governments can address these challenges through joint action.
Individuals must be aware of their skill needs and engage in learning activities throughout their life
In an increasingly digital economy and society, the business environment is rapidly evolving. To adapt and thrive in this environment, individuals first need awareness of the associated risks and opportunities. Digital transformation can empower individuals to seize new opportunities, stay connected with loved ones and lead more fulfilling lives. On the other hand, a more digital world brings potential risks in terms of well-being and mental health, mis- and disinformation, and privacy and security incidents. In 2020, 52% of European citizens reported they felt fairly or very well informed about cybercrime compared to 46% in 2017. However, confidence in their ability to protect themselves sufficiently from this type of crime went down from 71% in 2017 to 59% in 2020 (European Commission, 2020[48]).
Awareness increases with knowledge. In 2023, two-thirds of individuals in the European Union (67%) asked for more education and training to develop their digital skills (European Commission, 2023[49]). In this respect, lifelong learning appears as a key tool for individuals to tackle skill challenges. However, it also requires a change in mindset. Learning is no longer compartmentalised in different phases of life. Rather, it evolves over the lifecycle (OECD, 2021[18]). Lifelong learning involves formal learning in official settings like schools or training centres, but also informal and non-formal learning (such as learning from co-workers and workplace training). In addition, spontaneous social interactions creates opportunities for unintentional learning.
Today, digital technologies revolutionise traditional learning mechanisms. OECD (2021[1]) shows that smart technologies improve education systems and education delivery in different ways. They enhance access to education, improve its quality for learners and enhance its cost efficiency for societies. Advances in large language models could unlock a future of increasingly personalised learning for students in all disciplines and age groups. As education and training go digital, learning takes place everywhere, and becomes less costly and more accessible for individuals. In this respect, Figure 1.S.3 shows the percentage of Internet users that followed an online course in OECD countries has more than doubled over the past decade3 in almost all countries.
Individuals using the Internet for an online course as a percentage of all individuals, 2023
Source: Authors’ calculations based on (OECD, 2024[50]) ICT Access and Usage Database, https://oe.cd/dx/ict-access-usage (accessed on 31 January 2024).
In the EU27 more specifically, 16.4% of individuals followed an online course in 2022; 20.7% used online learning material other than a complete course such as video tutorials, webinars, electronic textbooks, learning apps or platforms; and 18.1% communicated with educators or learners using audio or video online tools like Zoom, MS Teams and Google Classroom.
This said, research findings show a number of personal and professional characteristics affects adults’ engagement in learning activities. These include age, gender, educational attainment or type of professional contract, tenure etc. Importantly, the self-directed nature of many online learning opportunities becomes a barrier for learners lacking the skills and dispositions to engage independently and fruitfully. OECD (2021[18]) argues that educational attainment is one of the strongest predictors of the willingness to continue learning. On average, tertiary-educated adults were less likely to be disengaged from adult learning than workers with lower-secondary education or below.
Containment and mitigation strategies related to the COVID-19 pandemic have also had direct and indirect effects on participation in adult learning among those willing to participate. Non-formal learning opportunities may have decreased by an average of 18% and informal learning opportunities by 25% in OECD countries (OECD, 2021[18]). Other factors, such as the availability of high-quality services, high training costs and personal constraints (e.g. lack of time or childcare responsibilities) also affect the decision of individual to engage in training.
Businesses should continuously engage in up- and re-skilling of employees
From a business perspective, digital technologies allow the automation of many routine tasks, give employees access to real-time data, provide them with the ability to telework, facilitate collaboration and communication, improve customer service, create a more engaging and personalised work experience and provide employees with mobile and social tools (Franke, 2022[51]). These changes cannot take place without a skilled workforce. Therefore, businesses should create a conducive environment for continuous learning and skill development, empowering their employees to thrive in the digital era. This not only benefits individual employees but also contributes to the overall success and competitiveness of the organisation in a rapidly evolving digital landscape.
To this end, employers need to invest in employees to help them gain and maintain the skills needed in the workplace (OECD, 2019[7]); some skills relevant today will be obsolete tomorrow. Yet, many adults do not participate – or wish to participate – in workplace learning. The pandemic also further reduced their opportunities to do so. This is especially true for low-skilled individuals lacking skills to engage in remote learning. In 2021, only 11.2% of EU enterprises provided their ICT specialists with professional training and 19.7% provided ICT training for other staff.
In addition to regular age- and skill-inclusive training programmes, businesses need to provide employees with access to online learning platforms, and subsidise or cover the costs of relevant courses. They must also foster a culture of continuous learning and skill development by inviting employees to take ownership of their own learning and providing resources to support them. Employees should be encouraged and supported to try out new digital tools and technologies in their work and benefit from a safe environment for experimentation and learning from failures.
Such work practices may sound disruptive or not affordable in all firms, in particular within an SME context which often needs specific skills. SMEs typically face a longstanding challenge in accessing and developing talent. They have limited connections to networks that may give access to qualified workers. They also lack formalised human resource management strategies to identify skills gaps and retain trained and skilled staff. In addition, SMEs may not be able to use the numerous financial incentives available to cover training costs, either because they are unaware of them, or because they are not eligible (OECD, 2023[52]).
To overcome such barriers, OECD (2023[52]) underlines the relevance of “skills ecosystems”.4 Facilitators can access bundles of skills, including transversal ones, without internalising them and fully bearing the related costs. Instead, skills can be accessed through the specialised labour pool or in the form of knowledge services. These positive externalities can enable SMEs to tap more easily into relevant expertise and respond to the need for “non-core” skills in a sustainable manner.
SMEs can also consider creative recruitment strategies, such as offering flexible work arrangements. These can showcase opportunities for growth and skill development, as well as emphasising the unique benefits of a smaller, close-knit team. Additionally, SMEs can look for candidates with a strong willingness to learn and adapt, as they may be more open to a broader range of responsibilities.
Co-operative coaching and learning sessions can consider each firm’s history and context, making them especially effective in improving the take-up of digital technologies in SMEs (OECD, 2021[41]). However, firms also require continuous and operational support to implement solutions. Consequently, measures that combine peer learning and individual support services – through subsidised consulting/coaching services, for example – seem best placed to help SMEs invest in the key competences for digital transformation.
Well-designed policies will help individuals and businesses to best prepare for future skill needs
Given the abovementioned challenges, governments need to co-ordinate their action. On the one hand, they must adopt an agile approach to national up-skilling initiatives by working with businesses, non-profit organisations and the education sector. They also need to engage in social dialogue with trade unions to continually monitor and improve the effective functioning of skill ecosystems. On the other, governments need to facilitate labour market transitions to ensure no one is left behind.
Today, several OECD countries (e.g. Australia, Ireland, Luxembourg, Sweden) and key partners (e.g. India, South Africa) have one or more national skills strategies. These aim to design and deliver in a cross-government approach and accompany the twin transitions. In addition, they seek to align efforts across a range of policies and with strong stakeholder involvement. These include social partners; civil society and labour market actors; and the education and training sector. The European Union has its own Skills Agenda that sets out five-year targets for all its member states (European Commission, 2020[53]).
In addition to skill strategies, governments also put in place policies to address various challenges discussed in this Spotlight. For example, most national AI strategies include significant education and labour market elements (OECD, 2024[54]). Policies in this regard can be grouped as follows:
Investing in the quality, equity and labour market relevance of education and training systems by allocating funding programmes that focus on in-demand skills and technologies and supporting vocational training, apprenticeships and on-the-job training opportunities and providing the relevant training to teachers (e.g. Education 4.0. CARNET Strategy 2022-2025 in Croatia, “Future Skills for Future Society” in Latvia).
Promoting lifelong learning by advocating for a culture of continuous learning and development among workers and employers, and encouraging individuals to take advantage of online courses, workshops and other learning resources (e.g. “Digital Competences in Education program” in Croatia, “The Strategy for Lifelong Guidance 2020-2023” in Finland, “Digital throughout Life Strategy” in Norway).
Facilitating of access to training resources by providing access to affordable or free training programmes and scholarships, especially for people on low income, and support initiatives such as public libraries, community centres and online platforms that offer educational resources (e.g. “Digitize for Work Program” in Chile, Digital learning platform for basic skills “vhs-Lernportal.de” in Germany, “Digital Literacy Program” in Mexico).
Recognising and certifying new skills by establishing mechanisms for recognition of non-traditional forms of learning, such as micro-credentials, badges or competency-based assessments and encouraging development of certifications recognised by the industry (e.g. “National Digital Education Policy (PNED)” in Brazil, “Pix” platform in France).
Attracting talents through specific visa programmes and scholarships to foster knowledge spill-over effects (e.g. “National AI Strategy” in the United Kingdom).
Engaging in public-private partnerships to identify current and future skill needs and encourage companies to participate in training programmes and offer internships or apprenticeships (e.g. “Personal Training Account of a Private Sector Employee” in France).
Providing tax incentives and subsidies by providing tax returns or subsidies to companies that invest in employee training and development, and creating incentives for individuals to pursue further education or training.
Promoting digital inclusion and diversity by ensuring that up- and re-skilling initiatives are accessible to all segments of the age pyramid and implementing targeted programmes to support diversity (e.g. “Fondo Repubblica Digitale” in Italy).
Evaluating and measuring policy impact by regularly assessing the effectiveness of programmes in terms of employment outcomes, wage growth and industry relevance, and using data-driven insights to refine and improve such initiatives over time.
Ensuring these policy measures remain relevant in a context of rapid technological development calls for closely monitoring how AI systems evolve. Anticipating shifts in skill demand caused by technology will be key for education and training systems to respond to the changing needs of individuals and businesses. Robust measurements of AI capabilities will hence be increasingly helpful to inform responsive social policies in the years to come (OECD, 2023[22]).
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← 1. Top performers (also called “academic all-rounders”) are defined as students who have the highest level of proficiency in PISA as they achieved Level 5 or 6 in science, reading and mathematics concomitantly.
← 2. Due to data availability, business sector is defined as the aggregation of the following NACE Rev.2 activity classes:
[B-E]: Industry (except construction)
F: Construction
[G-I]: Wholesale and retail trade, transport, accommodation, and food service activities
J: Information and communication
K: Financial and insurance activities
L: Real estate activities
[M-N]: Professional, scientific and technical activities; administrative and support service activities
[R-U]: Arts, entertainment and recreation; other service activities; activities of household and extra-territorial organizations and bodies.
← 3. For Canada and Japan, data refer to 2012 and 2022. For Chile, data refer to 2012 and 2017. For Colombia and Iceland, data refer to 2013 and 2021. For Costa Rica, data refer to 2018. For Israel, data refer to 2020 and 2021. For Egypt, data refer to 2022. For Colombia and Korea, data refer to 2013 and 2022. For Mexico, data refer to 2013 and 2022, and include “conducting job training”, “taking courses to supplement education”, “taking tutorials on any topics of interest”, and “other types of training”. For Poland, data refer to 2011 and 2023. For Switzerland, data refer to 2017 and 2023. For the United Kingdom, data refer to 2013 and 2020. For the United States, data refer to 2015 and 2021.
← 4. A skill ecosystem can be defined as a community (businesses, industry/sector, education and training providers, non-governmental organisations, local or regional stakeholders, etc.) in which individuals and organisations connect and interact to address skill needs and develop, use and transmit, in an autonomous way, knowledge, abilities and competences.