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23 May 2018

The low-down on intelligent automation

Digital transformation is now a core aspect of corporate strategies for the vast majority of Global 2000 companies, according to research by IDC. Intelligent automation has quickly emerged as one of the key drivers for unlocking the power of digital change in the workplace.

Intelligent automation can be defined as the unification of artificial intelligence and automation to aggregate, extract and analyze large volumes of data with the aim of streamlining decision making and automating processes and workflows. Business use cases are broad and plentiful. Indeed, the benefits are not just limited to the largest enterprises, as even SMEs and microenterprises can unlock real, lasting value from it.

Machine learning and robot reports

Intelligent automation goes beyond the simple practice of processing data sets, as the “intelligence” factor means it can make decisions and then learn as it develops and grows. This is a groundbreaking development, as the ability to analyze and understand a situation and then determine the correct course of action was previously limited to human beings. In fact, machines can often do it better and more quickly.

“Decision making” tasks refer to one of two primary outlets for the applications of intelligent automation in business. Smart machines are being used by financial institutions to study the consistency of research notes, which is something a human being would be incapable of at scale in such a short space of time. Meanwhile, Credit Suisse has been using the tech to write research reports and glean insights and conclusions from the mass of data sources it has to analyze. All of this is done without human intervention.

 Everyday applications

This new form of automation can take care of all the basic “heavy lifting” that a business has to do every single day. Large-scale manual analysis is laborious, slow and often error-prone. Intelligent software can, for example, drive productivity in call centers and customer-facing departments as it will perform low to medium complexity tasks with ease. This frees up time for agents to develop other customer-centric skills. Consequently, the bar is raised for customer experience.

Intelligent automation is also filling in the gaps between quarterly financials so that enterprises can better evaluate a company’s creditworthiness. It does this by monitoring thousands of data sources and identifying risks and opportunities. Beyond decision making, the tech can also be deployed for physical tasks that have traditionally been performed manually, such as distribution and logistics. In this context, robots travel around warehouses, think for themselves, and streamline the fulfillment and shipping process.

Robotic process automation (RPA) tools are central to the new way of working. Enterprises that leverage RPA and other technologies will maximize business benefits in the long term. This requires a close integration of machine learning, natural language and dynamic flow. Those that can combine and manage this tech effectively will see more than just productivity gains. Organizations have already experienced savings of up to 65% for onshore operations when implementing rules-based automation. This figure and other tangible benefits will only strengthen as the tech and the approach to RPA and intelligence matures.

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