Cognitive Automation: Committing to Business Outcomes

Karev said it’s important to develop a clear ownership strategy with various stakeholders agreeing on the project goals and tactics. For example, if there is a new business opportunity on the table, both the marketing and operations teams should align on its scope. They should also agree on whether the cognitive automation tool should empower agents to focus more on proactively upselling or speeding up average handling time.

The automation solution also foresees the length of the delay and other follow-on effects. As a result, the company can organize and take the required steps to prevent the situation. Having workers onboard and start working fast is one of the major bother areas for every firm.

Evaluating the right approach to cognitive automation for your business

The next step is, therefore, to determine the ideal cognitive automation approach and thoroughly evaluate the chosen solution. Let’s break down how cognitive automation bridges the gaps where other approaches to automation, most notably Robotic Process Automation (RPA) and integration tools (iPaaS) fall short. Besides conventional yet effective approaches to use case identification, some cognitive automation opportunities can be explored in novel ways.

A digital workforce, like a human workforce, is pre-trained and ready to work for you. These bots specialize in their field just as an Underwriter, Loan Officer, or Accounts Payable Specialist does. With 80% of their needed knowledge already pre-developed, they can plug-and-play in just a few weeks, teaching itself what it doesn’t know. Since the technology can adjust itself, maintenance is near non-existent. This significantly reduces the costs across every stage of the technology life cycle. Compared to the millions required in RPA and IPA, Cognitive Process Automation can often be implemented for as little as the cost of adding one person to your workforce, but with the output of four to eight headcount.

Cognitive automation in finance

The setup of an IPA algorithm and technology requires several million dollars and well over a year of development time in most cases. Cognitive automation tools are relatively new, but experts say they offer a substantial upgrade over earlier generations of automation software. Now, IT leaders are looking to expand the range of cognitive automation use cases they support in the enterprise.

Cognitive automation simulates human thought and subsequent actions to analyze and operate with accuracy and consistency. This knowledge-based approach adjusts for the more information-intensive processes by leveraging algorithms and technical methodology to make more informed data-driven business decisions. The value of intelligent automation in the world today, across industries, is unmistakable. With the automation of repetitive tasks through IA, businesses can reduce their costs as well as establish more consistency within their workflows. The COVID-19 pandemic has only expedited digital transformation efforts, fueling more investment within infrastructure to support automation. Individuals focused on low-level work will be reallocated to implement and scale these solutions as well as other higher-level tasks.

Cost savings

And as technological advancement continues, this experience becomes increasingly blurred with chatting with a human representative. With predictive analytics, bots are enabled to make situational decisions. To manage this enormous data-management demand and turn it into actionable planning and implementation, companies must have a tool that provides enhanced market prediction and visibility.

In addition, if data is incorrect, unstructured, or blank, RPA breaks. Your team has to correct the system, finish the process themselves, and wait for the next breakage. CIOs are now relying on cognitive automation and RPA to improve business processes more than ever before. « Cognitive automation is not just a different name for intelligent automation and hyper-automation, » said Amardeep Modi, practice director at Everest Group, a technology analysis firm. « Cognitive automation refers to automation of judgment- or knowledge-based tasks or processes using AI. »

Enhanced Customer Experience

Another important use case is attended automation bots that have the intelligence to guide agents in real time. Cognitive automation, unlike other types of artificial intelligence, is designed to imitate the way humans think. Until now the “What” and “How” parts of the RPA and Cognitive Automation are described.

Any other format, such as unstructured data, necessitates the use of cognitive automation. Cognitive automation also creates relationships and finds similarities between items through association learning. It is mostly used to complete time-consuming tasks handled by offshore teams. Here, the machine engages in a series of human-like conversations and behaviors. It does so to learn how humans communicate and define their own set of rules.

Since cognitive automation can analyze complex data from various sources, it helps optimize processes. Claims processing, one of the most fundamental operations in insurance, can be largely optimized by cognitive automation. Many insurance companies have to employ massive teams to handle claims in a timely manner and meet customer expectations.

It also helps organizations identify potential risks, monitor compliance adherence and flag potential fraud, errors or missing information. Automated processes can only function effectively as long as the decisions follow an “if/then” logic without needing any human judgment in between. However, this rigidity leads RPAs to fail to retrieve meaning and process forward unstructured data. Itransition offers full-cycle AI development to craft custom process automation, cognitive assistants, personalization and predictive analytics solutions. One example of cognitive automation in action is in the healthcare industry. Hospitals and clinics are using cognitive automation tools to automate administrative tasks such as appointment scheduling, billing, and patient record keeping.

Benefits the Organization

It can use all the data sources such as images, video, audio and text for decision making and business intelligence, and this quality makes it independent from the nature of the data. When introducing automation into your business processes, consider what your goals are, from improving customer satisfaction to reducing manual labor for your staff. Consider how you want to use this intelligent technology and how it will help you achieve your desired business outcomes. IA is capable of advanced data analytics techniques to process and interpret large volumes of data quickly and accurately. This enables organizations to gain valuable insights into their processes so they can make data-driven decisions.

• Cognitive automation may also play a role in automatically inventorying complex business processes.
• Traditional automation requires clear business rules, processes, and structure; however, traditional manpower requires none of these.
• When it comes to choosing between RPA and cognitive automation, the correct answer isn’t necessarily choosing one or the other.
• Middle managers will need to shift their focus on the more human elements of their job to sustain motivation within the workforce.

Basic language understanding makes it considerably easier to automate processes involving contracts and customer service. For instance, the call center industry routinely deals with a large volume of repetitive monotonous tasks that don’t require decision-making capabilities. With RPA, they automate data capture, integrate data and workflows to identify a customer and provide all supporting information to the agent on a single screen.

Many of them have achieved significant optimization of this challenge by adopting cognitive automation tools. Cognitive automation describes diverse ways of combining artificial intelligence (AI) and process automation capabilities to improve business outcomes. This approach ensures end users’ apprehensions regarding their digital literacy what is cognitive automation are alleviated, thus facilitating user buy-in. Typically, organizations have the most success with cognitive automation when they start with rule-based RPA first. After realizing quick wins with rule-based RPA and building momentum, the scope of automation possibilities can be broadened by introducing cognitive technologies.

Customers submit claims using various templates, can make mistakes, and attach unstructured data in the form of images and videos. Cognitive automation can optimize the majority of FNOL-related tasks, making a prime use case for RPA in insurance. RPA is referred to as automation software that can be integrated with existing digital systems to take on mundane work that requires monotonous data gathering, transferring, and reformatting. Cognitive automation is rapidly transforming the way businesses operate, and its benefits are being felt across a wide range of industries.

This “brain” is able to comprehend all of the company’s operations and replicate them at scale. Intelligent automation streamlines processes that were otherwise comprised of manual tasks or based on legacy systems, which can be resource-intensive, costly, and prone to human error. The applications of IA span across industries, providing efficiencies in different areas of the business. Like any first-generation technology, RPA alone has significant limitations. The business logic required to create a decision tree is complex, technical, and time-consuming.