The ability of global companies to harness the growth potential of new technological adoption is hindered by skills shortages. Figure 26 shows that skills gaps in the local labour market and inability to attract the right talent remain among the leading barriers to the adoption of new technologies. This finding is consistent across 20 of the 26 countries covered by the Country Profiles presented in Part 2 of the report. In the absence of ready talent, employers surveyed through the Future of Jobs Survey report that, on average, they provide access to reskilling and upskilling to 62% of their workforce, and that by 2025 they will expand that provision to a further 11% of their workforce. However, employee engagement into those courses is lagging, with only 42% of employees taking up employer-supported reskilling and upskilling opportunities.
Skills shortages are more acute in emerging professions. Asked to rate the ease of finding skilled employees across a range of new, strategic roles, business leaders consistently cite difficulties when hiring for Data Analysts and Scientists, AI and Machine Learning Specialists as well as Software and Application Developers, among other emerging roles. While an exact skills match is not a prerequisite to making a job transition, the long-term productivity of employees is determined by their mastery of key competencies. This section of the report takes stock of the types of skills that are currently in demand as well as the efforts underway to fill that demand through appropriate reskilling and upskilling.
Note: Cross-cutting skills are those skills that are applicable and easily transferable across many occupations and roles.
Note: The gap measure has been capped at 1.00.
Note: The gap measure has been capped at 1.00.
Since its 2016 edition, this report has tracked the cross-functional skills which are in increasing demand. Figure 27 shows the top skills and skill groups which employers see as rising in prominence in the lead up to 2025. These include groups such as critical thinking and analysis as well as problem-solving, which have stayed at the top of the agenda with year-on-year consistency. Newly emerging this year are skills in self-management such as active learning, resilience, stress tolerance and flexibility. In addition, the data available through metrics partnerships with LinkedIn and Coursera allow us to track with unprecedented granularity the types of specialized skills needed for the jobs of tomorrow. Figure 28 demonstrates the set of skills which are in demand across multiple emerging professions. Among these ‘cross-cutting’ skills are specialized skills in Product Marketing, Digital Marketing and Human Computer Interaction.
This report reveals in further granular detail the types of insights that can guide job transitions through to appropriate reskilling and upskilling. Figures 29 and 30 demonstrate those metrics. Figure 29 presents the set of high-growth, emerging roles that are currently covered by the Data and AI job cluster, and the typical skills gap between source and destination professions when workers have moved into those roles over the past five years. Figure 30 presents the typical learning curriculum of Coursera learners who are targeting a transition into Data and AI and the distance from the optimal level of mastery in the relevant job cluster, and quantifies the days of learning needed for the average worker to gain that level of mastery. Figure 29 and 30 together demonstrate that it is common for individuals moving into Data and AI to lack key data science skills—but that individuals seeking to transition into such roles will be able to work towards the right skill set through mastery of skills such as statistical programming within a recommended time frame, in this case, 76 days of learning.
In addition to skills that are directly jobs-relevant, during the COVID-19 context of 2020, data from the online learning provider Coursera has been able to identify an increasing emphasis within learner reskilling and upskilling efforts on personal development and self-management skills. This echoes earlier findings on the importance of well-being when managing in the remote and hybrid work: demand for new skills acquisition has bifurcated. Figure 31 A illustrates the changing demand for training by employment status, comparing the April-to-June period this year with the same period last year. This data reveals a significant increase in demand for personal development courses, as well as for courses in health, and a clear distinction between those who are currently in employment and those who are unemployed. Those in employment are placing larger emphasis on personal development courses, which have seen 88% growth among that population. Those who are unemployed have placed greater emphasis on learning digital skills such as data analysis, computer science and information technology. These trends can be observed in more granular detail in Figures 31 B and C. In particular, self-management skills such as mindfulness, meditation, gratitude and kindness are among the top 10 focus areas of those in employment in contrast to the more technical skills which were in-focus in 2019. In contrast, those who are unemployed have continued to emphasize skills which are of relevance to emerging jobs in Engineering, Cloud Computing, Data and AI.37
When it comes to employers providing workers with training opportunities for reskilling and upskilling, in contrast to previous years, employers are expecting to lean more fully on informal as opposed to formal learning. In the Future of Jobs Survey, 94% of business leaders report that they expect employees to pick up new skills on the job, a sharp uptake from 65% in 2018. An organization’s learning curricula is expected to blend different approaches—drawing on internal and external expertise, on new education technology tools and using both formal and informal methods of skills acquisition. According to data from the Future of Jobs Survey, formal upskilling appears to be more closely focused on technology use and design skills, while emotional intelligence skills are less frequently targeted in that formal reskilling provision. Data from Coursera showing the focus areas of workforce recovery programmes and employer-led reskilling and upskilling activities confirms that finding. In-focus courses are primarily those in technical skills alongside a cohort of managerial skills in strategy and leadership.
On average, respondents to the Future of Jobs Survey estimate that around 40% of workers will require reskilling of six months or less. That figure is higher for workers in the Consumer industry and in the Health and Healthcare industry, where employers are likely to expect to lean on short-cycle reskilling. The share of workers who can be reskilled within six months is lower in the Financial Services and the Energy sectors, where employers expect that workers will need more time-intensive reskilling. These patterns are explored more deeply in the Industry Profiles in Part 2.
According to Future of Jobs Survey data, employers expect to lean primarily on internal capacity to deliver training: 39% of training will be delivered by an internal department. However, that training will be supplemented by online learning platforms (16% of training) and by external consultants (11% of training). The trend towards the use of digital online reskilling has accelerated during the restrictions on in-person learning since the onset of the COVID-19 pandemic. New data from the online learning platform Coursera for April, May and June of 2020 (quarter 2) signals a substantial expansion in the use of online learning. In fact, there has been a four-fold increase in the numbers of individuals seeking out opportunities for learning online through their own initiative, a five-fold increase in employer provision of online learning opportunities to their workers and an even more extensive nine-fold enrolment increase for learners accessing online learning through government programmes.
Through focused efforts, individuals could acquire one of Coursera’s top 10 mastery skills in emerging professions across People and Culture, Content Writing, Sales and Marketing in one to two months. Learners could expand their skills in Product Development and Data and AI in two to three months and if they wish to fully re-pivot to Cloud and Engineering, learners could make headway into that key skill set through a 4-5 month learning programme.38 Such figures suggest that although learning a new skill set is increasingly accessible through new digital technologies,to consolidate new learning, individuals will need access to the time and funding to pursue such new career trajectories. LinkedIn data presented in section 2.2 indicates that although many individuals can move into emerging roles with low or mid skills similarity, a low-fit initial transition will still require eventual upskilling and reskilling to ensure long term productivity.