Autonomous Operations: Four Key Use Cases to Understand the Future

Autonomous Operations: Four Key Use Cases to Understand the Future

Real-world applications of this emerging paradigm in industries such as financial services, manufacturing, healthcare, and logistics.

We are entering the era of autonomous operations (AO): processes supported by a combination of technologies (such as artificial intelligence, the Internet of Things, advanced analytics, etc.), without human intervention, capable of making autonomous decisions and continuously learning.

Although this concept is still in its early stages in the market, some of its proposed benefits are already visible. Some of the most notable include eliminating subjectivity in decision-making processes (for example, to determine whether a person is qualified to perform an activity or to hold a new role), minimizing errors due to manual data entry or manipulation, an unprecedented increase in productivity, and the ability to provide customers with highly satisfactory and personalized experiences.

This could remain just a set of words or definitions, but at NTT DATA, we are working on projects that allow us to explain, with examples, the positive impact of AO on companies and also on our daily lives.

Mortgages in Minutes

Contrary to popular belief, AO is not restricted to the automation of factory production lines; it is a phenomenon that applies to any industry and function within a company’s value chain.

For instance, the financial industry can apply it to simplify home buying. The evolution of regulations and processes in the sector has made obtaining a mortgage very complex, with risk screening and all the documents required to complete the client’s file.

AO can use an intelligent agent supported by AI to capture the necessary data (using the mortgage system, the user’s banking history, and property information), validate it in real time, and offer an online solution.

Lower Costs, Lower Risks, Less Friction

Examples like these can be seen in many different fields. In manufacturing, a network of intelligent agents can be implemented to handle material transfers between plants, plan and execute production, and solve problems that may arise along the way, improving delivery times, reducing inventory, lowering transportation costs, and avoiding errors.

One of the major challenges for hospitals in healthcare is having perfectly disinfected operating rooms, chemotherapy rooms, and other treatment areas. The traditional method often relies on portable ultraviolet light devices that staff must move and operate. Besides the cost, ultraviolet light poses health risks. With AO, autonomous robots are used to disinfect facilities economically (with a cost reduction of up to 96% over five years) and without risks to workers.

Furthermore, a logistics company can use AO for preventive fleet maintenance. The automaker from whom the trucks are purchased connects to the vehicle database and analyzes each vehicle’s maintenance history and associated issues to schedule repairs before problems occur. By implementing this solution, you can reduce unexpected service interruptions by up to 90% and extend the average lifespan of each vehicle by two and a half years.

These are just a few use cases of a paradigm expected to dominate in the coming years. They will bring about a true revolution in the business world and offer a glimpse into the future already upon us.