Using enterprise intelligent automation for cognitive tasks

Cognitive automation is the current focus for most RPA companies’ product teams. However, simply automating rote tasks is not sufficient to deal with the continuous changes those enterprises face. In order to provide greater value, these automation tools need to step up the ladder of cognitive automation, incorporating AI and cognitive technologies to see increased value. Cognitive automation integrates AI and machine learning to perform complex tasks that require cognitive abilities.

In addition, businesses can use cognitive automation to create a more personalized customer experience. For example, businesses can use AI to recommend products to customers based on their purchase history. For example, businesses can use chatbots to answer customer questions 24/seven. Automation of various tasks helps businesses to save cost, reduce manual labor, optimize resource allocation, and minimize operational expenses.

It means that the way we work is changing, and businesses need to adapt in order to stay competitive. One of the most important aspects of this digital transformation is cognitive automation. For maintenance professionals in industries relying on machinery, cognitive automation predicts maintenance needs. It minimizes equipment downtime, optimizes performance, and allowing teams to proactively address issues before they escalate. Cognitive automation enhances the customer experience by providing accurate responses, round-the-clock support, and personalized interactions. This results in increased customer satisfaction, loyalty, and a positive brand image, ultimately leading to business growth and a competitive advantage in the market.

What Are the Benefits of Cognitive Automation?

First, a bot pulls data from medical records for the NLP model to analyze it, and then, based on the level of urgency, another bot places the patient in the appointment booking system. 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 an umbrella term for software solutions that leverage cognitive technologies to emulate human intelligence to perform specific tasks. When it comes to repetition, they are tireless, reliable, and hardly susceptible to attention gaps. By leaving routine tasks to robots, humans can squeeze the most value from collaboration and emotional intelligence.

But as those upward trends of scale, complexity, and pace continue to accelerate, it demands faster and smarter decision-making. There are a lot of use cases for artificial intelligence in everyday life—the effects of artificial intelligence in business increase day by day. It gives businesses a competitive advantage by enhancing their operations in numerous areas. Deliveries that are delayed are the worst thing that can happen to a logistics operations unit.

What makes cognitive automation the “cheat engine” for businesses?

This enables homeowners to save energy, enhance security, and improve convenience by automating tasks that were once manually managed. Cognitive automation may also play a role in automatically inventorying complex business processes. 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. “The biggest challenge is data, access to data and figuring out where to get started,” Samuel said. All cloud platform providers have made many of the applications for weaving together machine learning, big data and AI easily accessible. In the incoming decade, a significant portion of enterprise success will be largely attributed to the maturity of automation initiatives.

Cognitive automation is the strategic integration of artificial intelligence (AI) and process automation, aimed at enhancing business outcomes. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month. Cem’s work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

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. In addition, businesses can use cognitive automation to automate the data collection process. This means that businesses can collect data from a variety of sources, including social media, sensors, and website click-streams.

This is why robotic process automation consulting is becoming increasingly popular with enterprises. By using chatbots, businesses can provide answers to common questions quickly and efficiently. This frees up employees to focus on more complex tasks, such as resolving customer complaints. RPA is limited to executing preprogrammed tasks, whereas cognitive automation can analyze data, interpret information, and make informed decisions, enabling it to handle more complex and dynamic tasks. Deloitte explains how their team used bots with natural language processing capabilities to solve this issue.

A large part of determining what is effective for process automation is identifying what kinds of tasks require true cognitive abilities. While machine learning has come a long way, enterprise automation tools are not capable of experience, intuition-based judgment or extensive analysis that might draw from existing knowledge in other areas. Because cognitive automation bots are still only trained based on data, these aspects of process automation are more difficult for machines.

“With cognitive automation, CIOs can move the needle to high-value, high-frequency automations and have a bigger impact on the bottom line,” said Jon Knisley, principal of automation and process excellence at FortressIQ. These areas include data and systems architecture, infrastructure accessibility and operational connectivity to the business. This article dispels fear and provides tools to control AI-enabled automation. The concept alone is good to know but as in many cases, the proof is in the pudding. The next step is, therefore, to determine the ideal cognitive automation approach and thoroughly evaluate the chosen solution.

The issues faced by Postnord were addressed, and to some extent, reduced, by Digitate‘s ignio AIOps Cognitive automation solution. The automation solution also foresees the length of the delay and other follow-on effects. As a result, the company cognitive automation meaning can organize and take the required steps to prevent the situation. Let’s see some of the cognitive automation examples for better understanding. Make your business operations a competitive advantage by automating cross-enterprise and expert work.

This can be a huge time saver for employees who would otherwise have to manually input this data. Let’s take a look at how cognitive automation has helped businesses in the past and present. We still have a long way to go before we have freely thinking robots, but research is producing machine capabilities that assist businesses to automate more work and simplify the operations that employees are left with. In sectors with strict regulations, such as finance and healthcare, cognitive automation assists professionals by identifying potential risks. It ensures compliance with industry standards, and providing a reliable framework for handling sensitive data, fostering a sense of security among stakeholders.

For example, in an accounts payable workflow, cognitive automation could transform PDF documents into machine-readable structure data that would then be handed to RPA to perform rules-based data input into the ERP. RPA is best deployed in a stable environment with standardized and structured data. Cognitive automation is most valuable when applied in a complex IT environment with non-standardized and unstructured data. IA or cognitive automation has a ton of real-world applications across sectors and departments, from automating HR employee onboarding and payroll to financial loan processing and accounts payable. Cognitive automation has the potential to completely reorient the work environment by elevating efficiency and empowering organizations and their people to make data-driven decisions quickly and accurately. A cognitive automation solution for the retail industry can guarantee that all physical and online shop systems operate properly.

For example, accounts payable teams can automate the invoicing process by programming the software bot to receive invoice information — from an email or PDF file, for example — and enter it into the company’s accounting system. In this example, the software bot mimics the human role of opening the email, extracting the information from the invoice and copying the information into the company’s accounting system. “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.

This could involve the use of a variety of tools such as RPA, AI, process mining, business process management and analytics, Modi said. Cognitive automation is an extension of existing robotic process automation (RPA) technology. Machine learning enables bots to remember the best ways of completing tasks, while technology like optical character recognition increases the data formats with which bots can interact. Cognitive automation adds a layer of AI to RPA software to enhance the ability of RPA bots to complete tasks that require more knowledge and reasoning.

While basic tasks can be automated using RPA, subsequent tasks require context, judgment and an ability to learn. Cognitive automation can use AI techniques in places where document processing, vision, natural language and sound are required, taking automation to the next level. These skills, tools and processes can make more types of unstructured data available in structured format, which enables more complex decision-making, reasoning and predictive analytics. Facilitated by AI technology, the phenomenon of cognitive automation extends the scope of deterministic business process automation (BPA) through the probabilistic automation of knowledge and service work. By transforming work systems through cognitive automation, organizations are provided with vast strategic opportunities to gain business value. However, research lacks a unified conceptual lens on cognitive automation, which hinders scientific progress.

Cognitive automation involves incorporating an additional layer of AI and ML. TalkTalk received a solution from Splunk that enables the cognitive solution to manage the entire backend, giving customers access to an immediate resolution to their issues. Identifying and disclosing any network difficulties has helped TalkTalk enhance its network. As a result, they have greatly decreased the frequency of major incidents and increased uptime. The cognitive solution can tackle it independently if it’s a software problem. If not, it alerts a human to address the mechanical problem as soon as possible to minimize downtime.

• One of the foremost challenges before cognitive automation adoption is organizations need to build a culture that encourages the human workforce to accept, adapt, and work alongside the digital workforce.
• Now, with cognitive automation, businesses can take this a step further by automating more complex tasks that require human judgment.
• Advantages resulting from cognitive automation also include improvement in compliance and overall business quality, greater operational scalability, reduced turnaround, and lower error rates.
• We still have a long way to go before we have freely thinking robots, but research is producing machine capabilities that assist businesses to automate more work and simplify the operations that employees are left with.
• For example, they might only enable processing of one type of document — i.e., an invoice or a claim — or struggle with noisy and inconsistent data from IT applications and system logs.
• For example, employees who spend hours every day moving files or copying and pasting data from one source to another will find significant value from task automation.

Most businesses are only scratching the surface of cognitive automation and are yet to uncover their full potential. A cognitive automation solution may just be what it takes to revitalize resources and take operational performance to the next level. 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. Businesses are increasingly adopting cognitive automation as the next level in process automation.

What is Cognitive Automation? How It Can Transform Your Business

But at the end of the day, both are considered complementary rather than competitive approaches to addressing different aspects of automation. SS&C Blue Prism enables business leaders of the future to navigate around the roadblocks of ongoing digital transformation in order to truly reshape and evolve how work gets done – for the better. The human brain is wired to notice patterns even where there are none, but cognitive automation takes this a step further, implementing accuracy and predictive modeling in its AI algorithm.

AI and machine learning enable systems to learn and decide independently, paving the way for smarter, autonomous processes. IoT integration enhances connectivity and real-time data exchange, improving efficiency and enabling predictive maintenance across industries. In industries such as marketing, companies use automated systems to analyze consumer behavior and preferences based on data collected from various sources. This data-driven automation helps target specific audiences with personalized advertisements or recommendations, enhancing the overall customer experience. Whether it be RPA or cognitive automation, several experts reassure that every industry stands to gain from automation. According to Saxena, the goal is to automate tedious manual tasks, increase productivity, and free employees to focus on more meaningful, strategic work.

Even if the RPA tool does not have built-in cognitive automation capabilities, most tools are flexible enough to allow cognitive software vendors to build extensions. Another benefit of cognitive automation lies in handling unstructured data more efficiently compared to traditional RPA, which works best with structured data sources. It infuses a cognitive ability and can accommodate the automation of business processes utilizing large volumes of text and images.

It identifies processes that would be perfect candidates for automation then deploys the automation on its own, Saxena explained. “One of the biggest challenges for organizations that have embarked on automation initiatives and want to expand their automation and digitalization footprint is knowing what their processes are,” Kohli said. Exponential Digital Solutions (10xDS) is a new age organization where traditional consulting converges with digital technologies and innovative solutions. We are committed towards partnering with clients to help them realize their most important goals by harnessing a blend of automation, analytics, AI and all that’s “New” in the emerging exponential technologies. RPA and Cognitive Automation differ in terms of, task complexity, data handling, adaptability, decision making abilities, & complexity of integration.

Asurion was able to streamline this process with the aid of ServiceNow‘s solution. The Cognitive Automation system gets to work once a new hire needs to be onboarded. The Cognitive Automation solution from Splunk has been integrated into Airbus’s systems.

Automation serves as the bedrock of efficiency, transforming industries by reducing mistakes, speeding up processes, and enhancing resource utilization. Its paramount importance lies in freeing human potential from mundane tasks, fostering innovation, and enabling businesses to adapt to dynamic market landscapes swiftly. Automation catalyzes growth and competitiveness in today’s fast-paced world by streamlining operations and enhancing precision. You can foun additiona information about ai customer service and artificial intelligence and NLP. RPA combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications.

Cognitive automation tools can handle exceptions, make suggestions, and come to conclusions. While automation is old as the industrial revolution, digitization greatly increased activities that could be automated. However, initial tools for automation, which includes scripts, macros and robotic process automation (RPA) bots, focus on automating simple, repetitive processes. However, as those processes are automated with the help of more programming and better RPA tools, processes that require higher level cognitive functions are next in the line for automation.

• Supervised learning is a particular approach of machine learning that learns from well-labeled examples.
• If any are found, it simply adds the issue to the queue for human resolution.
• This means using technologies such as natural language processing, image processing, pattern recognition, and — most importantly — contextual analyses to make more intuitive leaps, perceptions, and judgments.
• What’s important, rule-based RPA helps with process standardization, which is often critical to the integration of AI in the workplace and in the corporate workflow.

Many organizations have also successfully automated their KYC processes with RPA. KYC compliance requires organizations to inspect vast amounts of documents that verify customers’ identities and check the legitimacy of their financial operations. RPA bots can successfully retrieve information from disparate sources for further human-led KYC analysis. In this case, cognitive automation takes this process a step further, relieving humans from analyzing this type of data. Similar to the aforementioned AML transaction monitoring, ML-powered bots can judge situations based on the context and real-time analysis of external sources like mass media. Essentially, cognitive automation within RPA setups allows companies to widen the array of automation scenarios to handle unstructured data, analyze context, and make non-binary decisions.

One of the foremost challenges before cognitive automation adoption is organizations need to build a culture that encourages the human workforce to accept, adapt, and work alongside the digital workforce. Cognitive automation can also help businesses minimize the amount of manual mental labor that employees have to do. For example, businesses can use optical character recognition (OCR) technology to convert scanned documents into editable text. And if you are planning to invest in an off-the-shelf RPA solution, scroll through our data-driven list of RPA tools and other automation solutions. Make automated decisions about claims based on policy and claim data and notify payment systems. You can check our article where we discuss the differences between RPA and intelligent / cognitive automation.