An increase in the productivity and pace of business processes can be expected, owing to the use of artificial intelligence (AI) and machine learning (ML), says cloud service firm Oracle South Africa MD Niral Patel.
An autonomous enterprise requires less time for manual tasks and lower margins of human error because of labour-intensive work. These productivity-increasing technologies are helping to transform traditional roles and create new forms of employment.
“It is about improving the decision-making capabilities of people by arming them with rich, relevant, topical and timely data,” he explains.
Autonomous systems can accelerate tasks that take more time than businesses want to allow and can enable them to achieve greater profitability through efficiency. This means employees focus on higher-value tasks and improve their decision-making capability by using relevant and timely data.
“AI, ML, automation technologies and greater computing power lead to an autonomous revolution, making machines increasingly capable of accomplishing activities that were once considered beyond their capabilities, such as making judgment calls, sensing emotion or even driving.”
The technology might help the transition, as its aim is to augment human skills and help free them up to do higher-value work, but not replace them, he adds.
Autonomous systems are an evolution of automation, which require users to intervene and dictate their operations. Autonomous solutions can operate independently to make decisions that are efficient but, owing to the use of AI, might suggest a better decision than those made previously, he avers.
“For example, an autonomous database does not require human intervention for routine tasks, such as patching and protecting the data from security vulnerabilities. These changes can lead to a change in the job scope, and an opportunity to upgrade oneself.”
There is a need for more government-led research on the impact of automation on employment and targeted programmes to support the retraining of existing workforces and university students, as well as an emphasis on continuous learning, he adds.
“Policymakers need to collaborate with the business community to help the employers and employees of tomorrow while they are in transition, enabling them to boost productivity and stay relevant.
“Organisations should start by deploying nonmission-critical workloads to determine how quickly they reap the rewards and are able to reskill workers. We are only at the start of the autonomous revolution, and early adopters are more likely to harness the full benefits,” concludes Patel.