About 20 percent of jobs throughout the U.S. economy are in the high vulnerability category, according to Nico Palesch, a senior economist of Oxford Economics, claiming that the technology to handle most of the work in those jobs has already been developed and is commercially ready.
That caution falls upon a labour market on which the headline figure may appear reassuringly peaceful. The U.S. Bureau of Labor Statistics will see total employment grow by 3.1 percent 2024 to 2034, compared to the 10 percent growth in the previous decade, in part due to slowed labour-force expansion related to demographic changes. The issue of the economic problem is not a mere lack of employment, but an increasing dislocation between the places where jobs are growing and the places where automation must strike first.
The report by Oxford Economics positions robotics as an “incremental revolution” and not an explosion. Adoption usually starts in areas where the business case is best defined: structured environment, repeatable activities, measurable throughput. It is engineering, not science fiction robots and software systems that previously managed discrete processes can now be coordinated into end-to-end processes, and those processes are becoming more and more tied to artificial intelligence. As Palesch had it: Robotics and automation adoption, like most technologies, even major revolutions, will be a slow, steady, and gradual process. It will not be a big bang…Instead we anticipate that adoption will initially be found in those spheres where people have the most potential…where adoption is most evident, feasible, and economical.
The logistics and transportation are close to the head of that line. Oxford Economics estimated that some 60 per cent of the work in the industry is highly vulnerable to at least partial automation, which is the rate of instrumentation, standardisation and automation of warehouses, depots, and routing. The same tension can be supported by the BLS projections: e-commerce is helping to drive up the growth of delivery and distribution jobs but warehousing companies are turning increasingly to robots, automated guided vehicles, and artificial intelligence to reduce labour requirements despite the increase in the volume of parcels.
A second and more observable example of “automation plus reorganisation” is retail. BLS anticipates that the retail trade will lose employment between 2024-34, where employment in cashiers will be reduced by approximately 314,000 jobs, which is attributed to the self-checkout and the offloading of the scanning and bagging work to consumers. Simultaneously, the online purchase is transforming the geography of work: the number of workers in tills is decreasing, the number of workers in fulfilment centres and last-mile delivery is increasing, and the software between inventory, staffing, and pricing is more prevalent.
Office work, which is always thought to be safer than physical labour, is no exception. BLS forecasts the office and administrative support group to be the quickest shrinking significant job classification to 2034. Jobs that are created around information processing, like word processors and typists, telephone operators, and data entry keyers, occupations in which information processing is the core business, now systematically taken over by software, appear on the list of BLS table of fastest declining occupations.
With the same projections, it is also seen as to where the system forms work by destroying tasks. Healthcare and social assistance is projected to create about 2.0 million jobs by 2034, which is caused by aging and chronic disease. Professional and technical services also increase such as engineering, IT, and consultancy services that design, implement and govern the same systems that actually perform the automating. In this regard, automation is not such a wave as a collection of currents in motion: work out of shopfloor and out of back office toward maintenance, integration, troubleshooting and supervision.
Skills are important in determining who is sucked in those widening streams. The OECD reports that the basic skills of literacy, numeracy and adaptive problem solving are not well-distributed among communities, which has defined who is able to retrain and who ends up being left behind. In an incremental revolution, the determining factor is not the coming of machines, but the mobility of workers with them.
