Shifting from RPA to Cognitive Automation

It requires a platform that digitizes the entire decision-making process and does it at the speed your business requires today, and in the future. Meanwhile, you are still doing the work, supported by countless tools and solutions, to make business-critical decisions. Let’s deep dive into the two types of automation to better understand the role they play in helping businesses stay competitive in changing times.

• Explore the cons of artificial intelligence before you decide whether artificial intelligence in insurance is good or bad.
• Processing the paper is required to automate any process end to end.
• Comidor’s Cognitive Automation software includes the following features to achieve advanced intelligent process automation smoothly.
• Some examples of mature cognitive automation use cases include intelligent document processing and intelligent virtual agents.
• Therefore, companies rely on AI focused companies like IBM and niche tech consultancy firms to build more sophisticated automation services.
• A task should be all about two things “Thinking” and “Doing,” but RPA is all about doing, it lacks the thinking part in itself.

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.

Different Underlying Technologies, Methodologies, and Processing Capabilities

Here is where AIOps simplifies the resolution of issues, even proactively, before it leads to a loss in revenue or customers. Generally speaking, sales drives everything else in the business – so, it’s a no-brainer that the ability to accurately predict sales is very important for any business. It helps companies better predict and plan for demand throughout the year and enables executives to make wiser business decisions.

You can also check our article on intelligent automation in finance and accounting for more examples. These tasks can be handled by using simple programming capabilities and do not require any intelligence. To bring intelligence into the game, cognitive automation is needed. Cognitive automation combined with RPA’s qualities imports an extra mile of composure; contextual adaptation. It can accommodate new rules and make the workflow dynamic in nature. By eliminating the opportunity for human error in these complex tasks, your company is able to produce higher-quality products and services.

Demystifying the two technologies: Three key differences

He focuses on cognitive automation, artificial intelligence, RPA, and mobility. 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 what is cognitive automation 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 issues faced by Postnord were addressed, and to some extent, reduced, by Digitate‘s ignio AIOps Cognitive automation solution. Their systems are always up and running, ensuring efficient operations. Deliveries that are delayed are the worst thing that can happen to a logistics operations unit. The parcel sorting system and automated warehouses present the most serious difficulty. They make it possible to carry out a significant amount of shipping daily.

How Cogito improves the claims management process

At the other end of the continuum, cognitive automation mimics human thought and action to manage and analyze large volumes with far greater speed, accuracy and consistency than even humans. It brings intelligence to information-intensive processes by leveraging different algorithms and technological approaches. There are a number of advantages to cognitive automation over other types of AI. They are designed to be used by business users and be operational in just a few weeks. Unlike other types of AI, such as machine learning, or deep learning, cognitive automation solutions imitate the way humans think.

In that way, they empower businesses to achieve Cognitive Automation and Autonomous Process Optimization. They can identify inefficiencies and predict changes, risks or opportunities. You should expect AI to make its way into every industry, every product, every process. But do keep in mind that AI is not a free lunch — it’s not going to be a source of infinite wealth and power, as some people have been claiming. Intelligence is to automation as a new lifeform is to an animated cartoon character.

Cognitive Automation: Smarten Your Processes with Comidor AI/ML

Employee onboarding is another example of a complex, multistep, manual process that requires a lot of HR bandwidth and can be streamlined with cognitive automation. Processors must retype the text or use standalone optical character recognition tools to copy and paste information from a PDF file into the system for further processing. Cognitive automation uses technologies like metadialog.com OCR to enable automation so the processor can supervise and take decisions based on extracted and persisted information. 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.

It provides additional free time for employees to do more complex and cognitive tasks and can be implemented quickly as opposed to traditional automation systems. It increases staff productivity and reduces costs by taking over the performance of tedious tasks. Cognitive automation has a place in most technologies built in the cloud, said John Samuel, executive vice president at CGS, an applications, enterprise learning and business process outsourcing company. His company has been working with enterprises to evaluate how they can use cognitive automation to improve the customer journey in areas like security, analytics, self-service troubleshooting and shopping assistance.

Sales experience (Bookmyshow & Splunk)

It is possible to use bots with natural language processing capabilities to spot any mismatches between contracts and invoices. When these are found, you are alerted to the issue to make the necessary corrections. Cognitive automation, unlike other types of artificial intelligence, is designed to imitate the way humans think. It now has a new set of capabilities above RPA, thanks to the addition of AI and ML. Some of the capabilities of cognitive automation include self-healing and rapid triaging. These are some of the best cognitive automation examples and use cases.

ServiceNow’s onboarding procedure starts before the new employee’s first work day. It handles all the labor-intensive processes involved in settling the employee in. These include setting up an organization account, configuring an email address, granting the required system access, etc. For instance, Religare, a well-known health insurance provider, automated its customer service using a chatbot powered by NLP and saved over 80% of its FTEs. The organization can use chatbots to carry out procedures like policy renewal, customer query ticket administration, resolving general customer inquiries at scale, etc.

Is cognitive automation each and every step pre-programmed?

By simplifying this data and maneuvering through complex tasks, business processes can function a bit more smoothly. You’ll also gain a deeper insight into where business processes can be improved and automated. Compared to other types of artificial intelligence, cognitive automation has a number of advantages. Cognitive automation solutions are pre-trained to automate specific business processes and require less data before they can make an impact. They don’t need help from it or data scientist to build elaborate models and are intended to be used by business users and be up and running in just a few weeks. In most scenarios, organizations can only generate meaningful savings if the last mile of such processes can be handled .

• In retail, it can be used to automate the analysis of customer data to better predict customer behavior.
• Such processes include learning (acquiring information and contextual rules for using the information), reasoning (using context and rules to reach conclusions) and self-correction (learning from successes and failures).
• A cognitive automation solution is a positive development in the world of automation.
• It can carry out various tasks, including determining the cause of a problem, resolving it on its own, and learning how to remedy it.
• Notably, we adopt open source tools and standardized data protocols to enable advanced automation.
• In banking, RPA can be used for a variety of retail branch activities, commercial underwriting, anti-money laundering, and loan processing.