The path to automation requires robots to collaborate with people, as opposed to simply replacing them completely. Vast majority of jobs will still need human intervention to a degree.
The possibility of job automation is greatest in predictable, manual, and repetitive work environments and in industries with reduced regulations.
The danger of automation is reduced in unstructured, dynamic, and unpredictable work environments and in businesses involving large regulatory scrutiny.
U.S. investment bank Goldman Sachs, as an instance, employed over 600 stock dealers at its peak. As a result of machine-learning algorithms capable of making complex transactions, these 600 dealers are reduced to two. Instead, about one-fifth of its workforce is currently employed as engineers.
But at exactly the exact same time, it’s creating thousands of new jobs for people in its fulfillment centers.
We know that robots are bad at gripping, choosing, and managing items in unstructured environments.
Risk of job automation is greatest in predictable work environments and in industries with reduced regulations. This includes tasks or jobs that are repetitive and manual.
It’s currently impacting over 10.5 million jobs in pubs, janitorial roles, and warehouses.
In hospitality, the ease of automation is high for manual and repetitive jobs like making coffee or preparing particular dishes. This is especially true in environments with highly organized menus and processes.
Many startups are working on electronic payment and tabletop-ordering applications to replace the activities of cashiers and servers.
The fantastic thing is that the danger of automation is reduced in unstructured or unpredictable work environments.
In health care, dynamic decision making in unpredictable work surroundings makes these patient-facing jobs hard to automate, particularly if there’s a high level of emotional intelligence required.
Although trucking is at high risk of automation, this is not likely to happen widely within the next decade as a result of regulatory challenges. While technology has the potential to reduce manual labour, it faces regulatory challenges as it still takes an individual driver for non-highway driving.
The construction industry, as an instance, is dynamic and unstructured.
Retraining and reskilling employees is going to be a recurring motif at the long run of work. Future-proofing jobs will require continuous re-skilling, re-learning, and obtaining updated skills and expertise so that we could be constantly future-ready and job-ready and being protected from automation.