What is Intelligent Automation?

In the insurance industry, cognitive automation has multiple application areas. It can be used to service policies with data mining and NLP techniques to extract policy data and impacts of policy changes to make automated decisions regarding policy changes. 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.

IBM’s cognitive Automation Platform is a Cloud based PaaS solution that enables Cognitive conversation with application users or automated alerts to understand a problem and get it resolved. It is made up of two distinct Automation areas; Cognitive Automation and Dynamic Automation. These are integrated by the IBM Integration Layer (Golden Bridge) which acts as the ‘glue’ between the two. 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.

In simpler words, cognitive automation uses technology to solve problems with human intelligence. The company implemented a cognitive automation application based on established global standards to automate categorization at the local level. The incoming data from retailers and vendors, which consisted of multiple formats such as text and images, are now processed using cognitive automation capabilities. The local datasets are matched with global standards to create a new set of clean, structured data.

All of these have a positive impact on business flexibility and employee efficiency. The coolest thing is that as new data is added to a cognitive system, the system can make more and more connections. This allows cognitive automation systems to keep learning unsupervised, and constantly adjusting to the new information they are being fed.

Evolving from Robotic Process Automation to Cognitive Automation

For example, businesses can use chatbots to answer customer questions 24/seven. And you should not expect current AI technology to suddenly become autonomous, develop a will of its own, and take over the world. This is not where the current technological path is leading — if you extrapolate existing cognitive automation systems far into the future, they still look like cognitive automation.

New insights could be revealed thanks to cognitive computing’s capacity to take in various data properties and grasp, analyze, and learn from them. These prospective answers could be essential in various fields, particularly life science and healthcare, which desperately need quick, radical innovation. The way RPA processes data differs significantly from cognitive automation in several important ways. You can foun additiona information about ai customer service and artificial intelligence and NLP. It now has a new set of capabilities above RPA, thanks to the addition of AI and ML.

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. It’s as simple as pressing the record, play, and stop buttons and dragging and dropping files around. To execute business processes across the organization, RPA bots also provide a scheduling feature. Advantages resulting from cognitive automation also include improvement in compliance and overall business quality, greater operational scalability, reduced turnaround, and lower error rates.

Its systems can analyze large datasets, extract relevant insights and provide decision support. Thus, cognitive automation represents a leap forward in the evolutionary chain of automating processes – reason enough to dive a bit deeper into cognitive automation and how it differs from traditional process automation solutions. RPA helps businesses support innovation without having to pay heavily to test new ideas.

Processing claims is perhaps one of the most labor-intensive tasks faced by insurance company employees and thus poses an operational burden on the company. Many of them have achieved significant optimization of this challenge by adopting cognitive automation tools. Deloitte explains how their team used bots with natural language processing capabilities to solve this issue. You can also check our article on intelligent automation in finance and accounting for more examples.

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This task involves assessing the creditworthiness of customers by carefully inspecting tax reports, business plans, and mortgage applications. Given that the majority of today’s banks have an online application process, cognitive bots can source relevant data from submitted documents and make an informed prediction, which will be further passed to a human agent to verify. Accounting departments can also benefit from the use of cognitive automation, said Kapil Kalokhe, senior director of business advisory services at Saggezza, a global IT consultancy. 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. These tasks can range from answering complex customer queries to extracting pertinent information from document scans.

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Aera Technology CEO Frederic Laluyaux leads a panel of experts in a discussion about cognitive automation and the digital transformation. If you want to survive, you have to evolve, and intelligent technologies are the path to enterprise digital transformation. Leverages claims based on policy and claim data to make automated decisions and notifies payment systems. The global RPA market is expected to cross USD 3 billion in 2025 according to a study. Simultaneously, the AI market is projected to reach USD 191 billion by 2024 at a CAGR of 37%. As evident, cognitive automation and RPA are set to redefine the way businesses work.

RPA is a huge boon for the likes of the contact centre industry, with their focus on large volumes of repetitive and monotonous tasks that do not require decision-making. By automating data capture and integrating workflows to identify customers, agents can access supporting details on one screen and avoid the need to tap into multiple systems to gather contextual information. The promise of shorter call durations and an improved experience for customers and agents alike. Put simply, RPA involves automating menial and repetitive tasks; cognitive automation adds an all-important extra layer of AI and machine learning. In addition, businesses can use cognitive automation to create a more personalized customer experience.

This results in improved efficiency and productivity by reducing the time and effort required for tasks that traditionally rely on human cognitive abilities. Traditional RPA is mainly limited to automating processes (which may or may not involve structured data) that need swift, repetitive actions without much contextual analysis or dealing with contingencies. In other words, the automation of business processes provided by them is mainly limited to finishing tasks within a rigid rule set.

While cognitive automation or cognitive computing, on the other hand, impinges on the knowledge base that human beings have as well as on other human attributes beyond the physical ability to do something. Cognitive automation can deal with natural language, reasoning, and judgment, with establishing context, possibly with establishing the meaning of things and providing insights. Certainly, RPA bots are trying to lock down the natural language end of things but there is no requirement for a workbot like Elio, our DevOps sidekick, to make a judgement call. RPA is tasked with completing simpler types of work, specifically those tasks that don’t need knowledge (in its traditional sense), understanding or insight. Those tasks that can be done by codifying rules and instructing the computer or the software to act. RPA is process driven and is able to complete actions based on a specific set of rules and will apply those rules throughout the process to ensure a specific and expected kind of result.

With the ever-increasing complexities of processes across industries, companies are yearning to explore various avenues to develop a smarter assistant that can actually understand and replicate human decision-making. The classic RPA, as you might know, cannot process common forms of data such as natural language, scanned documents, PDFs, and images. But with the introduction of Artificial Intelligence (AI) and Machine Learning (ML), RPA is getting smarter by expanding its capabilities and paving way for cognitive platforms. Cognitive Automation solutions emulate human cognitive processes such as reasoning, judgment, and problem-solving with the power of AI and machine learning. We elevate your operations by infusing intelligence into information-intensive processes through our advanced technology integration. We address the challenges of fragmented automation leading to inefficiencies, disjointed experience, and customer dissatisfaction.

Its ability to address tedious jobs for long durations helps increase staff productivity, reduce costs and lessen employer attrition. Alternatively, Cognitive Automation uses artificial intelligence (AI) and machine learning to mimic human thought and actions to help solve more complex problems and gain key insights from data. Cognitive Automation is a subset of Artificial Intelligence (AI) that is capable of performing complex tasks that require extensive human thinking and activities.

In addition, cognitive automation can help reduce the cost of business operations. Our state-of-the-art AI/ML technology can improve your business processes and tackle those complex and challenging tasks that are slowing your productivity. Contact us today to learn more about cognitive automation technologies and how to implement them in your organization. We’re honored to feature our guest writer, Pankaj Ahuja, the Global Director of Digital Process Operations at HCLTech.

Customers want service when and where they need it, and cognitive automation and AI make it possible. An effective digital transformation means minimizing the guess work, and automating decisions through AI. The digital workforce and artificial intelligence are critical to improving employee engagement. Autonomous delivery service, surveillance of algorithms, AI outperforming humans, and the phone of the future.

Any task that is rule-based and does not require analytical skills or cognitive thinking such as answering queries, performing calculations, and maintaining records and transactions can be taken over by RPA. Most RPA companies have been investing in various ways to build cognitive capabilities but cognitive capabilities of different tools vary of course. The ideal way would be to test the RPA tool to be procured against the cognitive capabilities required by the process you will automate in your company. Companies large and small are focusing on “digitally transforming” their business, and few such technologies have been as influential as robotic process automation (RPA).

There hasn’t been a wave of powerful, cognitive automation tools appearing on the market just yet. However, rather than following a specific set of rules or instructions, cognitive computing uses the algorithms to spot patterns in large amounts of data while RPA makes recommendations and completes actions based on sets of rules. You must start somewhere though and most organisations tend to do so at the more basic end.

This frees up medical staff to focus on patient care, leading to better health outcomes for patients. Cognitive Automation simulates the human learning procedure to grasp knowledge from the dataset and extort the patterns. 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.

Taking the guesswork out of inventory management is a key benefit of moving to intelligent technologies. Digital transformation is not a finite process with a set end point; it’s a mindset shift and the perpetual pursuit of the next set of targets. Cognitive automation enables touchless forecasting that is faster and more accurate than manual processes.

As new data is added to the system, it forms connections on its own to continually learn and constantly adjust to new information. 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. Cognitive automation can help automate the onboarding process by providing the necessary tools, access, and information employees need from day one. For example, cognitive automation can automatically create computer credentials such as Slack logins, business email accounts, and enroll new hires into departmental training and orientation.

According to consulting firm McKinsey & Company, organisations that implement RPA can see a return on investment of 30 to 200 percent in the first year alone. Banking chatbots, for example, are designed to automate the process of opening a new account. Bots can evaluate form data provided by the customer for preliminary approval processing tasks like credit checks, scanning driver’s licenses, extracting ID card data, and more. Likewise, technology takes center stage in driving loan processing initiatives or accelerating back-office processing in the banking & financial services sector. By using cognitive automation to make a greater impact with fewer data, businesses can improve their decision-making and increase their operational efficiency.

In contrast, cognitive automation or Intelligent Process Automation (IPA) can accommodate both structured and unstructured data to automate more complex processes. Partnering with an experienced vendor with expertise across the continuum can help accelerate the automation journey. The custom solution can be tailored as per your organizational needs to deliver personalized services round-the-clock, and leverage predictive insights to anticipate and meet customer needs and expectations. Since Cognitive Automation uses advanced technologies to automate business processes, it is able to handle challenging IT tasks that human users may struggle with. Additionally, this software can easily identify possible errors or issues within your IT system and suggest solutions. Robotic Process Automation (RPA) and cognitive automation are popular tools being employed by CIOs in order to speed up business processes, explains Kulkarni (2022).

Cognitive automation empowers your decision-making ability with real-time insights by processing data swiftly, and unearthing hidden trends – facilitating agile and informed choices. Leia, the AI chatbot, retrieves data from a knowledge base and delivers information instantly to the end-users. Comidor allows you to create your own knowledge base, the central repository for all the information your chatbot needs to support your employees and answer questions.

Cognitive automation – the next frontier of enterprise RPA?

Basic cognitive services are often customized, rather than designed from scratch. This makes it easier for business users to provision and customize cognitive automation that reflects their expertise and familiarity with the business. In practice, they may have to work with tool experts to ensure the services are resilient, are secure and address any privacy requirements. The global RPA market is expected to reach USD 3.11 billion by 2025, according to a new study by Grand View Research, Inc. At the same time, the Artificial Intelligence (AI) market which is a core part of cognitive automation is expected to exceed USD 191 Billion by 2024 at a CAGR of 37%. With such extravagant growth predictions, cognitive automation and RPA have the potential to fundamentally reshape the way businesses work.

The majority of core corporate processes are highly repetitive, but not so much that they can take the human out of the process with simple programming. SS&C Blue Prism enables business leaders of the future to navigate around the roadblocks of ongoing digital transformation what is cognitive automation in order to truly reshape and evolve how work gets done – for the better. Like our brains’ neural networks creating pathways as we take in new information, cognitive automation makes connections in patterns and uses that information to make decisions.

For example, businesses can use machine learning to automatically identify patterns in data. At Aspire, our team of innovative RPA experts is ready to empower your business process operations in terms of both rules-based and intelligence-based automation solutions. Yes, Cognitive Automation solution helps you streamline the processes, automate mundane and repetitive and low-complexity tasks through specialized bots. It enables human agents to focus on adding value through their skills and knowledge to elevate operations and boosting its efficiency. As we covered above, cognitive automation is particularly powered by the use of machine learning and its subfield, deep learning.

It imitates the capability of decision-making and functioning of humans. This assists in resolving more difficult issues and gaining valuable insights from complicated data. Cognitive automation involves incorporating an additional layer of AI and ML.

«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.» For instance, at a call center, customer service agents receive support from cognitive systems to help them engage with customers, answer inquiries, and provide better customer experiences.

For many companies, leapfrogging over RPA and starting with cognitive automation might seem like trying to run before you can walk. Rather than trying to emulate the success stories you see overnight, your business should have a well-thought-out, long-term strategy for RPA and cognitive automation in order to maximise your ROI. Since employee onboarding is an essential and repeated office process across all industries, with predictable roles and procedures, it is a perfect testing ground for the benefits cognitive automation can provide. This can be a huge time saver for employees who would otherwise have to manually input this data. 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.

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. 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. Cognitive automation is a summarizing term for the application of Machine Learning technologies to automation in order to take over tasks that would otherwise require manual labor to be accomplished.

• One of the most important aspects of this digital transformation is cognitive automation.
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• It infuses a cognitive ability and can accommodate the automation of business processes utilizing large volumes of text and images.
• Typically, organizations have the most success with cognitive automation when they start with rule-based RPA first.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School. 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. Therefore, required cognitive functionality can be added on these tools.

Cognitive automation has proven to be effective in addressing those key challenges by supporting companies in optimizing their day-to-day activities as well as their entire business. Learn how to optimize your employee onboarding process through implementing AI automation, saving costs and hours of productive time. Processing these transactions require paperwork processing and completing regulatory checks including sanctions checks and proper buyer and seller apportioning. In this article, we explore RPA tools in terms of cognitive abilities, what makes them cognitively capable, and which RPA vendors provide such tools. The American Medical Association (AMA) has been pushing digital initiatives to ensure its members are able to access the needed support to embrace emerging technologies. There is also a sense of readiness and confidence towards emerging technologies in the healthcare industry, as covered in TechHQ.

Cognitive automation is a cutting-edge technology that combines artificial intelligence (AI), machine learning, and robotic process automation (RPA) to streamline business operations and reduce costs. With cognitive automation, businesses can automate complex, repetitive tasks that would normally require human intervention, such as data entry, customer service, and accounting. These are the solutions that get consultants and executives most excited. Vendors claim that 70-80% of corporate knowledge tasks can be automated with increased cognitive capabilities.

Processes require decisions and if those decisions cannot be formulated as a set of rules, machine learning solutions are used to replace human judgment to automate processes. The remaining 40% of tasks involve massive amounts of data and require human cognitive capabilities such as continuous learning, making decisions based on context, understanding complex relationships and engaging in conversation. By augmenting human cognitive capabilities with AI-powered analysis and recommendations, cognitive automation drives more informed and data-driven decisions.