Find out the power of cognitive automation

Yet roughly 80% of data is unstructured — meaning information is difficult to access, digitize and extract using traditional RPA solutions. Using native AI technologies enable cognitive automation solutions that can process unstructured data. Typical enterprise still relies on multiple resources to process data and increase business agility, accuracy and efficiency. Cognitive automation is a way to bridge the gap between traditional RPA and full-blown AI technologies. Cognitive automation is a subset of AI, using specific AI techniques to mimic the way the human brain works, and assisting in decision making, task completion or meeting goals.

Doctors can use this technology to not only make more informed diagnoses for their patients, but also create more individualized treatment plans for them. Cognitive systems are also able to read patient images like X-rays and MRI scans, and find abnormalities that human experts often miss. Muddu Sudhakar, CEO of tech company Aisera, likens cognitive computing to the process of teaching a child. People also use dictionaries and books to teach children not only what certain words mean, but the entire context of those words — a process known as taxonomy. For instance, “weather” relates to things like temperature, precipitation and seasons. People also teach children by exhibiting behavior they hope the child will replicate and deterring behavior they don’t like.

How does cognitive automation work?

As more studies are conducted and more use cases are explored, the benefits of automation will only grow. With RPA analyzing diagnostic data, patients who match common factors for cancer diagnoses can be recognized and brought to a doctor’s attention faster and with less testing. It improves the care cycle tremendously and streamlines much of the time-consuming research work. Upon receiving invoice files, the Account Receivable specialist’s first step is to classify the documents by type, such as recurring, pro forma, or commercial invoices. Next, he/she will attempt to digitize the forms by performing optical character recognition (OCR) and convert printed text into machine-encoded text. If certain documents fail the OCR attempt, he/she will have to reprocess the failed documents or manually input invoice data into his/her ERP system.

The very nature of cognitive computing could solve some of the problems it currently has. Sudhakar said technological innovation does not mean we no longer need humans anymore. But tractors can do hard manual labor in a fraction of the time humans can, thus giving farmers the time and latitude to be more efficient elsewhere.

Operations optimization

They also have to be able to retain information about situations that have already occurred, ask clarifying questions and grasp the context in which information is being used. From hyperautomation to low-code platforms and increased focus on security, learn about the latest developments shaping the world of automation. “Cognitive automation, however, unlocks many of these constraints by being able to more fully automate and integrate across an entire value chain, and in doing so broaden the value realization that can be achieved,” Matcher said. Robotic Process Automation (RPA) and Cognitive Automation, these two terms are only similar to a word which is “Automation” other of it, they do not have many similarities in it. In the era of technology, these both have their necessity, but these methods cannot be counted on the same page. The scope of automation is constantly evolving—and with it, the structures of organizations.

• Cognitive Automation has a lot going for it but those benefits can come at a cost, the first of which is an additional financial investment.
• 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.
• It can be largely used to drive a degree of process efficiency and reduction in routine manual processing.
• Muddu Sudhakar, CEO of tech company Aisera, likens cognitive computing to the process of teaching a child.
• By nature, AI requires large amounts of data for training machines to accomplish specific tasks, recognize patterns, and make decisions.

Robotic process automation (RPA) – Using software robots to automate repetitive and routine tasks, such as data entry or form processing. Robotic process automation can be used to reduce costs and improve efficiency in areas such as finance, human resources, and supply chain management. Traditionally cognitive capabilities were the realm of data analytics and digitization. Robotic Process Automation (RPA) works best if you have a structured process, involves a large volume of data and is rule based. Indeed, cognitive computing employs a lot of what makes up AI, including neural networks, natural language processing, machine learning and deep learning.

Process automation remains the foundational premise of both RPA and cognitive automation, by which tasks and processes executed by humans are now executed by digital workers. However, cognitive automation extends the functional boundaries of what is automated well beyond what is feasible through RPA alone. Peritus develops tools for IT operations that automate support delivery and problem resolution, including incident categorization, assignments, and much more.

These technologies are growing to emulate every aspect of human thought processes, or direct emulation of our senses. Some categories such as Natural Language Processing (NLP) aim to emulate an entire system, from auditory and visual recognition through to complex language analysis. This is because the type of automation that is gaining in popularity in the healthcare industry is Cognitive Automation. That means that automation works in tandem with healthcare professionals to streamline and optimize processes that are often repetitive. The automation allows human workers to focus on interpreting and analyzing data instead of mindlessly entering that data. Cognitive computing applications link data analysis and adaptive page displays (AUI) to adjust content for a particular type of audience.

Most cognitive technologies are shaped around streamlining operations within a business, creating value from information that was previously locked behind sheer volume or complexity. AI allows for large stores of information to be processed at lightning speed and with pinpoint accuracy. Incorporating machine-learning allows for optical character recognition and even natural language processing — meaning less time is needed to interpret information that comes directly from doctors and patients on forms and charts. AI refers more broadly to any technology that can process massive volumes of data and complete tasks on its own. While cognitive computing incorporates different AI technologies, it is designed specifically to mimic human thought processes and help humans solve complex problems. AI is meant to replace human labor, but cognitive computing complements human labor and thinking.

But combined with cognitive automation, RPA has the potential to automate entire end-to-end processes and aid in decision-making from both structured and unstructured data. Cognitive automation performs advanced, complex tasks with its ability to read and understand unstructured data. It has the potential to improve organizations’ productivity by handling repetitive or time-intensive tasks and freeing up your human workforce to focus on more strategic activities. One example of a cognitive system improving engagement is RoboChat, a system by NAB owned UBank. This IBM Watson-powered Chatbot uses the Watson engine to help customers fill out complex home loan forms. The system is able to handle simple to moderately complex queries, allowing dialogue with the user through natural language such as “what is an interest-only repayment?

How does Robotic Process Automation work?

By submitting this form, you agree that you have read and understand Apexon’s Terms and Conditions. If your business is ready to explore the benefits of RPA and how they can improve agility in your organization, let’s talk. Corporations invest millions of dollars in empowering one and protecting the other. Cognitive automation is fast becoming mainstream and is implemented to develop self-servicing business paradigms. With its limitless technical possibilities and immense scope, it is widely deployed across multiple verticals such as in front, middle and back-office operations, IT, HR, finance as well as marketing and sales.

It also suggests a way of packaging AI and automation capabilities for capturing best practices, facilitating reuse or as part of an AI service app store. This facilitates continuous deployment and integration, allowing for rapid iteration and updates to retail software, keeping you ahead in a fast-changing market. Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”), its network of member firms, and their related entities. DTTL (also referred to as “Deloitte Global”) does not provide services to clients.

With this technology there will be minimum human interference with medicine hence decreasing the likelihood of contamination and also increasing the rate of production. According to a recent survey one-week delay in drug release causes about 2% reduction in company’s profit and also patients do not get their drugs on time, which has some collateral damage for the company on the long-run. 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.

This raises questions about the knowledge worker, task assignments, the division of labor, and when organizations should augment their human capital with machines and cognitive technology. You must start somewhere though and most organisations tend to do so at the more basic end. RPA allows businesses to manage volume quickly and cost-effectively before stepping up to cognitive automation once they are ready to handle volume and complexity. It’s all about getting the right mix for your needs and partnering with a quality vendor for guidance on your automation journey is highly recommended. At the end of the day, embracing RPA and cognitive automation is all about putting oneself in the best position to empower employees and improve customer experience. The most obvious shortfall of RPA compared to cognitive automation is it cannot learn from the data it collects.

Perhaps the most mature set of technologies, this encompasses those systems that are designed to automate repetitive, well-defined processes. These systems generally have a strong set of governing rules and libraries that create cognitive automation meaning a rigid architecture around the “decisions” they make. Cognitive insight technologies are capable of altering their algorithms and resultant outputs over multiple iterations (sometimes millions) without human input.

• For all the good cognitive computing is doing for innovation, ProtectedBy.AI CEO Kostman thinks it’s only a matter of time before bad actors take advantage of this technology as well.
• But as RPA accomplish that without any thought process for example button pushing, Information capture and Data entry.
• It also suggests a way of packaging AI and automation capabilities for capturing best practices, facilitating reuse, or as part of an AI service app store.
• Cognitive technologies have evolved out of the ever expanding artificial intelligence space.

IBM Cloud Pak® for Automation provide a complete and modular set of AI-powered automation capabilities to tackle both common and complex operational challenges. 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.