By Phanikishore Burre, Vice President & Global Head – Cloud, Infrastructure & Security Services, CSS Corp
Intelligent automation is the use of artificial intelligence technologies (including natural language processing, machine learning, and other technologies) to automate tasks otherwise performed by humans, including both physical tasks and decision making. They may range from the regular to the disruptive: from simply collecting, analyzing, and making decisions based on available information, to guiding robots and driverless vehicles.
Intelligent automation (IA) system differ significantly from traditional automation in their ability to constantly evolve and learn. IA systems sense and synthesize huge amounts of information and develop insights about the processes they are performing. They can use these insights to predict the outcomes of potential actions, such as changes made to the underlying enterprise infrastructure or application updates to business processes.
There are numerous examples of the commercial use of intelligent automation. Credit card processing systems can identify and block fraudulent transactions. Marketing systems can make offers to clients depending on the analyses of their profile and market demands. E-discovery systems that can identify document meaning for litigation purposes.
Demand for Intelligent Automation
The range of business problems to which intelligent automation can be applied is expanding as advanced technologies improve and become usable by non-specialists. Demand continues to be driven by:
• Tight Labor Markets:A shortage of workers in sectors like retail, customer support, manufacturing, and insurance have led companies to seek out alternatives. By automating routine tasks, available human resources are freed up.
• Exponential Growth of Data and Information: On an average, human knowledge is doubling every 13 months. IBM estimates that the build out of the Internet of Things will lead to the doubling of information every 12 hours. IA, like power tools, enables knowledge workers—from plant supervisors to investment analysts to physicians—to process, understand, and effectively use huge volumes of information.
• Prebuild IA Solutions: Software firms, technology firms, and private equity are all betting big on all things AI. One result is the growth of industry-specific IA solutions and IA-as-a-service. These pre-built tools decrease costs, mitigate risks, and increase ease-of-use. From tech companies like EdTech Foundry’s chatbots that assist students in higher education to software firms like Lytic’s IA-based personalized marketing solutions for healthcare companies, niche IA solutions are being developed for every conceivable use.
Use of Intelligent Automation to Automate Decision Making
A potent use of IA involves automation of analysis and decision making. The complete workflow often includes humans for reviewing and approving decisions made by machines but removing most of the analysis work can produce better decisions more efficiently.
Tech manufacturers use IA for monitoring customer infrastructure and application for risks and enabling service agility. IA can extract key metrics from IT operations, and dynamically set thresholds and drive operational excellence.
In the public sector, a network of sensors, cameras, and data feeds linked to an AI-powered system can automatically flag images for a human analyst watching for potential threats. Londonhas deployed a large citywide network of video cameras and leverages intelligent technologies for identifying crime suspects.
Automation of Physical Tasks through Collaborative Robots
The new generation of intelligent robots can perform much more sophisticated physical tasks than their traditional counterparts and can even learn from human coworkers.
Kiva Systems’ famous “mobile-robotic fulfillment system” automates retail distribution centers for organizations. Robots travel around a distribution center to automatically transport shelving units loaded with products to workers who are preparing customer orders for shipment. Amazon acquired Kiva Systems last year for nearly $800 million.
Volkswagen implemented “collaborative robots” in an engine production plant in Germany that work side by side with humans. Volkswagen’s motivation for implementing the robot was to prevent “long-term burdens” on its employees by having machines take over tasks that are “ergonomically unfavorable.”
Given the breakneck pace of automation technology, there is no tried and true path for organizations to follow. It will not be a natural act, and will require effort from each one of us. But that should not stop today’s leaders. To benefit from intelligent automation, organizations need to ensure that their teams are fully equipped to take the advantage of the changes that lie ahead. It also means investing in innovation and new skills, and creating an environment of experimentation, opportunity and growth. But first, it requires a shift to a digital mindset and culture where the relationship between people and machines can fulfill its potential as essential co-workers for the digital age.