How the world of work will evolve has fascinated economists, educators, workers, and planning and policy professionals for many decades – more so in recent years due to globalisation and the exponential growth of technological innovation. That said, there is a great difficulty in attempting to forecast the impact of such factors on individual workers and the labour market as a whole. Events such as the COVID-19 pandemic can also suddenly accelerate trends that have been reshaping the labour markets for decades.

Unsurprisingly, there are many views on the future of work, some of which are complementary and others that are divergent and conflicting.

There are two widely shared views about automation. One view held by researchers and economists is that policies will need to be put into place to address the challenge of labour shortages as technology and innovation creates a high demand for high-skilled workers. Another view is that advances in technology will gradually reduce the demand for low and medium skilled workers in jobs that are easily automated.

The underlying narrative of these views is similar – as the world becomes more dependent on technology and reliant on global supply chains there will be a net increase in the demand for more highly skilled workers to meet the challenges and opportunities of the future. Therefore, it is imperative that policies prepare the current and future workforce to make meaningful transitions to jobs that are in demand with the skills that are in-demand.

There are many divergent views and research methodologies in the future of work debate. There are also a number of myths and misconceptions. Much of the debate centres around the single issue of how automation will threaten jobs in the future – however this is not new. In 1921, The New York Times featured a book review entitled ‘Man devoured by his machines’, and in 1928 the same publication ran the headline ‘March of the machine makes idle hands; farm employment less with increased output’ ⁶⁷.

Narratives suggesting automation will wipe out large numbers of jobs were prevalent in the 1960s, 1980s and 2010s, each time suggesting the world was reaching a tipping point where machines would take over the majority of jobs ⁶⁸. More recently, narratives in 2010 responded to concerns that even highly skilled knowledge-based jobs soon would be threatened by advancements in AI, robotics, software bots and autonomous vehicles.

Popular debates often cite Frey and Osborne’s estimates as forecasting an impending employment apocalypse. Their research published in 2013 estimated 47% of jobs could be exposed to automation from a technological capabilities point of view. They did this by analysing tasks, but then used a binary approach to determine whether an entire job would be replaced or not ⁶⁹.

Frey and Osborne’s estimates have been contested, and other models have examined a greater breadth of variables and are more nuanced in describing task replacement rather than job replacement. For example, the OECD found that only 14% of jobs are exposed to automation while ‘a further 32% of jobs have a risk between 50 and 70% pointing to the possibility of significant change in the way their jobs are carried out as a result of automation’ ⁷⁰.

The NSC has analysed the prominent future of work models across Australia, the United Kingdom, New Zealand and United States. Six of the models reviewed are described briefly in Figure 74. The figure highlights two main approaches used to predict the future of work. One approach assessed automation risk at the occupation level and the second assessed automation impacts at the job-task level.

The divergence between the occupational and task-based models is substantial – with variations of between 7% and 77% in the level of automation predicted for selected occupations. For nursing support, AlphaBeta predicts 30% of the job to be automated compared with 74% by Frey and Osborne. The difference between the models is not always in the same direction. AlphaBeta, with a task-based model, predicts 22% of secondary school teachers’ roles will be automated compared with 1% across occupational based models.

Even within the task-based models developed in 2019 by the OECD and McKinsey & Company there is divergence, both in the framing of the high-level results and methodologies used.

In summary, it is difficult to predict the future level of automation of the workforce. All models have inherent limitations in their methodologies and approaches. The Frey and Osborne model has gained much media attention without acknowledgement of the substantial variation in predictions from other models, especially task-based approaches, and the merits and drawbacks of each approach.

Narratives focusing on job losses often do not account for the net employment effects of automation. Implicitly, this focus on job destruction reflects the fallacy that there is only a fixed number of jobs, or a ‘lump of labour’, and that any job losses arising from automation cannot be offset by job creation. It is also easier to identify the jobs lost due to automation and the effects of global trade links. New jobs are less visible and can be spread out across different sectors.

The reality is that automation is not destroying human work. Neither is it always creating new jobs and tasks ⁷¹. Automation has varying effects within occupations and industries. It can replace labour in some jobs and replace tasks humans used to perform as well as creating new tasks and demand for labour. For example, software and computers replaced labour in some white-collar jobs. They also created new tasks including programming, software and application development, and more specialist tasks within existing occupations related to administrative assistance.

When technology complements the work humans do, it can lift the productivity of workers, lower costs and increase demand for new products and services. New business models can increase multi-factor productivity, but realising these gains requires innovation and the right supply of skills, as well as other factors ⁷².

We must also consider that the net number of jobs lost or gained is a deceptively simple metric to measuring the true impact of automation and new technologies on the labour market. For example, eliminating one million jobs and creating the same number of new jobs would appear to have a negligible impact. In practice, however, this causes huge economic disruption for the country and for workers – with flow-on effects to the economy as a whole ⁷³. A comprehensive understanding of the implications of automation and technology on the economy requires a deeper look at the broader effects of change, and the following sections seek to unpack these in greater detail.

An important goal of future of work research is to explore how the way we undertake our work will change. This includes increased access to flexible and remote working arrangements, facilitated by new technology, and the likelihood that workers may change jobs more regularly in future. There is also much debate about the rise of precarious working arrangements – about whether job polarisation will see ‘middle jobs’ decline in favour of both high and low skilled jobs, and whether the proportion of casual workers, gig workers, and underemployed workers will rise.

In 2018, Bankwest and Curtin University reported analysis from their index of precarious employment in Australia using data from the Household income and labour dynamics in Australia survey (HILDA). They found that between 2009 and 2018, precarious employment had increased for both men and women, but more rapidly for men. For both genders, the lowest levels of precariousness were for professionals and managers, and the highest were for labourers and machinery operators. There were differences between genders within occupations – for example female sales workers or community and personal services workers had significantly higher levels of precariousness then their male equivalents ⁷⁴. At an industry level, workers in ‘public administration and safety’, ‘agriculture’, and ‘accommodation and food services’ had the highest levels of precarious employment across all occupations. Among these, ‘accommodation and food services’ was the most precarious industry – with precariousness extending even to managers in the sector ⁷⁵. These trends are driven by multiple factors, which illustrates how future of work issues such as automation, globalisation and technological advancement cannot be considered in isolation. They arise in the context of other factors driving changes in the labour market. Other data, however, suggest that these concerns might be overdone. As an example, the extent of casualisation in the workforce has been little changed for the past 20 years according to data on employee leave entitlements produced by the ABS.

What is clearer is the rise in part-time employment. Part-time employment has become more common for both men and women over the 40 years to 2018, with part time employees growing to represent 31% of the workforce – double the level of around 15% in the late 1970s ⁷⁶. For men, the prevalence of part-time work arrangements has increased almost four-fold over this time, with the proportion of employed men working part-time growing from 5% to 18%. While the proportion of employed women working part-time has traditionally been larger than the proportion of men (about 50% of employed women in 2018), the reasons for working part-time are changing. The number of women citing caring responsibilities as the main reason for undertaking part-time work dropped to 30% in 2015 (from around 35% in 2002) ⁷⁷.

Much of the literature predicted increases to rates of working from home over the coming years, even prior to the COVID-19 pandemic. An increase in remote working arrangements put in place during the pandemic may persist, particularly as employers capitalise on potential benefits such as lower rent for smaller hybrid office spaces, and lower travel and meeting expenses. According to the World Economic Forum, in a report published in 2020, 84% of employers were aiming to further digitalise working processes. This included a significant expansion of remote work, with the potential to move 44% of their workforce to operate remotely ⁷⁸.

The future of work may increase access to work for some cohorts. For example, more flexible hours and alternative ways of working facilitated by technology can allow workers with mobility or accessibility requirements, or caring responsibilities, to undertake work at a place or time that accommodates their personal circumstances. In 2019, McKinsey & Company found that automation had the potential to boost workforce participation and create opportunities particularly for women with children, workers over the age of 65 and people with a disability ⁷⁹.

The opportunities for women stemming from the future of work and the need to support low skilled men has been highlighted in a range of recent literature. Bankwest and Curtin University analysis found that the rise in job insecurity in recent years has affected men more than women, and low-skilled females have had higher employment than low-skilled males for most of the last 15 years. Men have been working fewer hours and are more likely to be working in occupations where growth in hourly pay has stalled, and which are at high risk of technological disruption, while women currently dominate the fastest growing jobs ⁸⁰.

As the skills profile of the Australian labour market moves toward a greater proportion of higher skilled jobs, it will be important to ensure that workers, and lower-skilled men in particular, have access to education and reskilling opportunities to help them move into higher skilled, less automatable jobs.

The literature also points to the growing importance of core competencies, or ‘employability skills’, to ensuring workers’ continued success in the labour force. Core competencies are the basic building blocks common across most occupations and industries. They describe a set of non specialist skills, such as oral communication, teamwork and problem solving, gained in early life and schooling. They provide a base to further develop skills and specialties.

NSC analysis reveals that these skills are already highly valued by employers. A 2019 employer survey found that 75% of employers considered employability skills to be as, if not more, important than technical skills ⁸¹. AlphaBeta analysis also found these kinds of skills to be the fastest growing in the labour market, and the World Economic Forum found that the top skills employers see as important in coming years include critical thinking, analysis and problem-solving skills and skills in self management such as active learning, resilience, stress tolerance and flexibility ⁸². In the future of work discourse these ‘human’ skills are regarded as being less automatable than manual skills, and occupations that heavily rely on these skills may be less susceptible to task change and obsolescence ⁸³. McKinsey & Company estimate that by 2030, workers will spend 43% more time on work interactions that require well developed social and emotional skills. Deloitte estimates that two thirds of jobs will be soft-skill intensive in the same timeframe ⁸⁴.

Across the literature, recommended responses to the future of work centre around the need for businesses to capitalise on technological advances to ensure their competitive success, and for workers to be prepared to reskill and retrain throughout their lives to meet changing skills demands.

AlphaBeta estimates that Australian workers will be likely to change jobs 2.4 times over the next two decades, but that even workers who stay in their jobs will need to frequently refresh their skills to navigate changes to their jobs. The tasks within Australian jobs are estimated to be changing by an average of 18% every decade, and Australians are predicted to spend 33% more time on education and training across their lifetime by 2040 – an additional 8,000 hours, or three hours per week
until retirement ⁸⁵. 

Workers must be prepared to reskill and retrain, businesses must be prepared to invest in workforce planning and learning and development, and policy makers and education providers must provide the necessary information and infrastructure to enable these investments.

The literature concurs that skills and reskilling are key to success in the future of work, yet levels of preparedness and action in Australia are low. In 2019, Andrews and Friday published the results of a series of 34 executive conversations and over 2000 survey interviews with employers and workers across Australia’s and New Zealand’s largest organisations ⁸⁶. 

Andrews and Friday broadly concluded that there is widespread complacency about the future of work among employers and employees alike. They found that 60% of workers have given little to no consideration to the impact of digital technology on their job, and 61% of employers believe they can rely on the market to deliver the digital capabilities they require – despite a number of these skills already being in undersupply.

Further, only 56% of employers surveyed reported that they understood the requisite skills to continue their business into the future, and 63% were still in the early stages of developing skills-forecasting and workforce-planning capabilities. In the absence of adequate long-term workforce planning, training tended to be for today’s needs rather than future needs.

Andrews and Friday found that leaders were held back from proactively responding to technological change in the workforce by an inability to predict when and how digital technology would impact their work, and tended to invest more in automation than in reskilling their workers.

Perhaps the biggest lesson about the future of work is that technological change is not looming over a distant and undefined horizon – the future of work is now. Globalisation, technological change and automation are already changing the way we work and the makeup of jobs, and are driving the creation of new jobs.

Occupations are already evolving to capture new opportunities in innovation – and this is affecting all job types and skill levels. For example, construction workers may have relied on operating physical tools and measurement techniques to plan and follow construction projects; however, more and more workers in these occupations are now relying on the use of drones, visualisation software and satellite imagery to plan and execute projects ⁸⁷. This also demonstrates how occupations that are considered medium-skilled are increasing their scope to include more high-skilled tasks due to the augmentation, increased safety, and productivity gains of technology.