History has seen several industrial revolutions that have each dramatically changed the labour market, as means of production and levels of productivity have continually evolved with the introduction of new technologies. Today, new technologies are converging to make for even faster progress and more disruptive changes to the nature of work. Automation will change the kinds of jobs needed in the future, while digital technologies and societal preferences will change how and where we work. Thus, not only is the definition of ‘workforce’ changing, but the scope and focus of what a human resource department does may be shifting from being ‘workforce focused’ to ‘human capital focused’.

Society trends

Effects of automation

The increasing automation of industry is already a very observable and well-studied trend. With advances in ‘‘, ‘’, and ‘’, the ability of machines to perform tasks more effectively than people is steadily increasing. This will have enormous consequences for the global employment landscape, with some studies predicting that, at the global level, ‘automation could eliminate 9% of existing jobs and radically change approximately one-third in the next 15 to 20 years”.[1] What sets this industrial transformation apart from those that came before it is the speed at which it is occurring. This ‘Fourth Industrial Revolution’, as it is often known, is happening so rapidly that careful governance will be required in order to maximize its potential benefits.

While many studies focus on the potential job losses that could result from automation, it is important to keep in mind that, at least in the longer term, automation will also result in significant job creation. It will create new kinds of jobs, removing the need for humans to do unsafe, boring, and repetitive tasks, while increasing productivity and giving workers more flexibility and leisure time than in the past.[2,3] These new jobs will likely require higher-level technical skills and more social and/or creative skills than the jobs that will disappear.[4]

Of course, the ability of individual countries to benefit from automation varies significantly depending on several factors:

  • Demographics: Countries with ageing populations will likely promote faster adoption of automation to replace and augment their ageing workforces, especially in sectors such as health, aged care, mining, and agriculture.[1,5] Automation in countries with younger populations and a growing workforce could, on the one hand, have more disruptive effects and potentially exert a downward pressure on wages. On the other hand, these countries could also be more agile in responding to changes brought about by automation, as long as they can provide the required education to train new workers.[1]
  • Level of industrialization: There is some concern that automation could disadvantage developing countries, as these countries tend to have a high number of jobs in manufacturing. What’s more, a lot of manufacturing could be ‘re-shored’ back to developed countries by using robots, which would decrease opportunities for developing countries to grow their economies through export-led manufacturing.[2] But advanced economies will not be unchallenged either – they may see revenue shortages as the number of workers paying tax decreases, and they may be more susceptible to societal upheaval as segments of their populations who are used to experiencing a steady growth in living standards become more disadvantaged.[6]
  • Education systems: The skills present in a country’s workforce plus its ability to provide access to continuing education will strongly influence how well it can adapt to increased automation. In countries where women tend to have lower education levels and fewer technical skills than men, their jobs may be at greater risk from automation, and this may lead to women being disproportionately excluded from the workforce.[2] Therefore policymakers will need to ensure that sufficient retraining and upskilling initiatives are put in place to make the transition as smooth as possible, in particular for low and medium-skilled workers and (in some cases) women.[7]

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Reinventing the workplace

While automation is changing the kind of jobs that dominate the employment landscape, other new technologies and societal pressures are transforming workplace culture and how we work. Digital technology is allowing more people to work remotely and with much more flexible schedules. This trend did not begin with the COVID-19 pandemic but has certainly been accelerated by it – the pandemic led to a dramatic increase in the number of people working remotely and in the use of videoconferencing and virtual meetings, alongside a large decrease in business travel and the use of physical office space.[8] Surveys show that these trends align with the preferences of the great majority of millennials (92% want to work remotely and 87% want to work according to their own schedule[9]) and allow people to better balance their work and home lives. However, there are also potential negatives – some workers may suffer increased stress levels due to being continually connected to work[6], while others may become disengaged and less productive, as they lose their physical connection to co-workers and a dedicated workspace.[10] Organizations are therefore facing the double challenge of investing in the necessary technologies to enable a hybrid or remote work environment in order to attract and retain the best talent, while also developing strategies to combat increased employee stress or fragmentation and disengagement of their workforce.

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References

  1. (US National Intelligence Council, 2021)
  2. (UN Conference on Trade and Development, 2019)
  3. (Commonwealth Scientific and Industrial Research Organisation, 2019)
  4. Future outlook. 100 Global trends for 2050 (UAE Ministry of Cabinet Affairs and the Future, 2017)
  5. (Commonwealth Scientific and Industrial Research Organisation, 2019)
  6. (UK Ministry of Defence , 2018)
  7. (World Bank, 2019)
  8. (McKinsey Global Institute, 2021)
  9. (Allianz, 2019)
  10. (Deloitte, 2017)