Insights

Companies begin to turn to bots- to manage their other bots

Automation Intelligence is emerging as a model for legacy companies hoping to take a step-by-step approach to digitization.

Network Intelligence Platform contributors

Automation Intelligence, an approach to digital transformation that uses AI to supervise and coordinate simpler automated and human tasks, is emerging as a model for legacy companies hoping to take a step-by-step approach to digitization. Will it be able to keep up with new competitors that are digital from the ground up?

“What is the best way to combine many different human inputs and automation technologies to get things done?”

This remains one of the great unanswered questions of the so-called “Fourth Industrial Revolution,” and there is a lot riding on the answer. The fact that information industries such as publishing and professional services are likely to be open to automation. This has become apparent to many analysts. However, unlike in assembly-line automation, where production is typically broken down into a series of standardized steps, the production of information is more fluid and even chaotic at times.

One approach that has gained some traction is Robotic Process Automation, which uses individual software “bots” to take over small manually intensive parts of projects, for example gathering patient details before a healthcare appointment or classifying receipts submitted for an expense account. Robotic Process Automation has been one of the fastest growing enterprise software markets, and today many companies and businesses already utilize robotic process automation practices to some extent.

The problem with these tools is that they are often fragmented. Navigating a workflow that has been heavily outfitted with RPA can be like navigating a factory with machinery in place, but no assembly line processes. In order to develop more efficient and digitized methods of conducting business operations and practices, many organizations are seeking to scale these solutions and practices of automation with artificial intelligence to go beyond the routine to the innovative.

The development and implementation of intelligent automation systems can help the organizations and businesses to improve and enhance various processes such as training and developing the workforce, finding and recruiting talent, improving customer experiences, and increasing productivity and efficiency.

But as these bots accumulate, what approach can be used to keep them in alignment with overall process goals? This is where the emerging Automation Intelligence space hopes to have an impact, by applying artificial intelligence to the management of Robotic Process Automation. When compared to the RPA processes, it has been said that the Automation Intelligence systems are more concerned with the ‘thinking’ part of the job, and less with the “doing.” And over the last two years, there has been a notable increase in the number of enterprises adopting end-user process automation via the robotics process automation (RPA) route.

The Automation Intelligence approach got its start in manufacturing processes and later as bits and pieces in other functions. But now, it is increasingly becoming an part of various enterprise functions across the board. Organizations are putting in place a comprehensive architecture of Automation Intelligence systems because of its crucial potential to be the critical vehicle for effecting enterprise-wide transformation.

To automate or not to automate is no longer a question anymore.

Examples

Case 1: Goldman Sachs

Goldman Sachs entered into a partnership to use real-time statistical computing and analytics technology across the firm developed by Kensho.

https://www.prnewswire.com/news-releases/goldman-sachs-leads-15-million-investment-in-kensho-300000102.html

Case 2: UBS Group AG

The UBS group uses AI to help deliver personalized advice to the bank’s wealthy clients.

https://www.bloomberg.com/news/articles/2014-12-07/ubs-turns-to-artificial-intelligence-to-advise-wealthy-clients

Case 3: Genworth Financials

Genworth Financials developed an automation system for underwriting long-term life insurance applications by utilizing AI techniques.

https://www.researchgate.net/publication/220604860_Automating_the_Underwriting_of_Insurance_Applications

Implications

Some of the most important implications of Automation Intelligence are concerned with change management, the displacement effects of labor replacement, the change in the nature of jobs, and the development and training of employees and executives. The implementation of automation intelligence has a direct impact on labor and human employees to an extent as it replaces them by performing the routine tasks in an effective and efficient manner.

Innovation would require the creation and development of new and effective training programs for the employees and of the managers in order to fully utilize the potential of these automation intelligence systems and policies. It also indicates that the nature of jobs and duties will change. The companies will need to develop and establish an effective change management process as well. The strategies and objectives of such a program should be aimed at getting the employees on board with the new technological changes within the organization.

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