Embracing the Inevitable

Increased automation in the workforce is happening. While projecting the precise impacts of automation on employment is highly challenging, published estimates range from 2-5 million Australian jobs will be lost over the next 10-15 years.¹

In our own industry, we have seen the exponential rise in AI to handle ‘big data’ collection and modelling which have either augmented or replaced the roles in data collection and processing which were traditionally entry points to a career in private sector economics. Largely automated ‘off the shelf’ modelling and reporting of economic and demographic data has also come to dominate sectors of the economic consulting market.

The impacts of COVID 19 have turbo-charged the pace of workforce automation, with health risks to human staff on-site, and forced restrictions on business operations and travel key drivers favouring increased automation and augmentation of roles by AI.  A recent study by Honeywell Intelligrated (2020) highlighted that around half of companies surveyed indicated they were increasing their investment in automation to assist in surviving the challenges brought on by the pandemic.

Sectors at Risk

The rapid and simultaneous nature of digital transformation means that large portions of the workforce, particularly lower-skilled workers will be increasingly susceptible to having their roles automated.

All sectors are impacted, with retail trade among the susceptible sectors, with projected losses of 450,000 of the nation’s 1.6 million workers (approximately 30%) in the sector due to automation. This trend has been occurring for some time, with the prevalence of self-serve checkouts and continued move to online retailing compounding the broader technological and workforce trends.

Other highly impacted industries include the transport and administrative services sector, with the standardised and rules-based tasks common in these industry roles making them prime candidates for automation.  Around one-third of jobs in these sectors are projected to be automated within 10-15 years.

Figure 1: Projected Impact of Automation by Industry (2035)

Susceptibility of Occupations

In terms of occupations, the susceptibility to augmentation is similarly driven by the level of complexity and human interaction/ judgement required within the role. The most susceptible occupations include those involved with process-based tasks including accounting and bookkeeping, retail cashiers and manufacturing process workers.

Key roles with more limited projected automation impacts include patient facing medical professionals, ICT specialists, sales roles, and sections of the legal and education professions.

The rapidly changing employment landscape has the potential to cause wide-scale unemployment if large sections of workers are caught unawares. Large sections of the workforce will need to be re-trained, and the longer we wait to undertake this large reskilling need, the bigger the issue will become.

Table 1: Top 15 Least and Most Vulnerable Occupations to Automation

Productivity Gains and Shift in Skills Demand

The risks and inevitable job losses associated with increased automation need to be considered alongside the significant business and potential community benefits which can be realised. These include improved productivity and lower operating costs, improved worker safety, lower environmental impacts, greater flexibility and adaptability, and improved production and service quality.

As processes become increasingly automated, the opportunities will grow for specifically human skills like creativity, design, interpersonal relations.

Other types of higher cognitive skills such as advanced literacy and writing, and quantitative and statistical skills are unlikely to see a similar increase in demand and indeed have the potential to decline over the next 10 years. AI already takes a significant role in areas such as editing and basic news reporting. However, this is likely to be offset by increased need in areas such as complex information processing and interpretation which will occur alongside the automation of more routine functions.

The continued projected shift in worker skills demand will see competition for high-skill workers increase, with job displacement disproportionately concentrated on lower-skilled workers. This in turn will further exacerbate trends of income inequality and place pressure on low to middle income jobs.

Figure 2: Projected Change in Skills Demand (2016-2030)

The Impacts will be Different

As the impacts of workforce automation continue to transpire, they will also have significant economic development implications for local economies.

Metropolitan areas, with their high proportion of knowledge jobs and roles based on human/interpersonal relationships will likely experience less negative impacts and capture a greater share of the benefits of the growth in automation as an industry (approximately 20% of positions are projected to be automated in Sydney and Melbourne Local Government Areas).  However, the potential to operate remotely and/or autonomously will likely see some activities continue to relocate away from expensive city centres to more affordable lifestyle based centres.

Conversely, rural/remote areas which rely heavily on transport and construction/trade roles (which have traditionally offered high salaries to attract workers to the remote locations) are particularly at risk to the potential for roles to be filled remotely or replaced through investment in automation. Up to 30% of roles are susceptible to automation in regional and remote areas such a Mount Isa, The Pilbara, Mackay, and Isaac.

The key for these and other regional areas will be to position themselves to take advantage of the new opportunities presented by technology through innovation into areas such as digital agriculture and remote working alongside growth opportunities that align with their natural advantages of available and affordable land. The opportunities vary by region but include green energy, tourism, mining and agricultural value adding, and advanced manufacturing,

The net transition of employment over the coming years at an individual, regional and national level will depend on our ability to keep pace with the rate of automation adoption and the capacity to re-skill in order to share in the productivity gains and financial benefits that automation and augmentation of human tasks will achieve.

Reference

1. Fathem AI, 2020; McKinsey and Co.; 2018; CEDA, 2015; Regional Australia Institute, 2018