Instead of coding systems to follow a prescribed set of rules, self-learning systems provide a user-friendly interface for a human operator to interact and manually address an identified exception when it first occurs. Human operators rely on old fashioned mouse clicks, keystrokes and (not so) common sense to sort out why an exception has occurred and how to fix it. As consumers, we’ve been spoiled by the riches of online convenience—much of it delivered by automated systems and process intelligence that’s invisible to us.
Cognitive processes, also called cognitive functions, include basic aspects such as perception and attention, as well as more complex ones, such as thinking. Any activity we do, e.g., reading, washing the dishes or cycling, involves cognitive processing.
For instance, in the healthcare industry, cognitive automation helps providers better understand and predict the impact of their patients health. Cognitive automation can perform high-value tasks such as collecting and interpreting diagnostic results, suggesting database treatment options to physicians, dispensing drugs and more. Cognitive automation techniques can also be used to streamline commercial mortgage processing. 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.
Either way, get your automation right and you too could be enhancing customer experience and staff productivity while cutting operational costs and risk. Intelligent RPA solutions utilize machine learning and artificial intelligence to learn processes, analyze novel datasets, organize data, and make business decisions. There are many workflow automation tools like Zapier, Microsoft Flow, Integromate, etc. You must recruit an experienced conditional programmer who will first learn your business processes.
For example, an enterprise might buy an invoice-reading service for a specific industry, which would enhance the ability to consume invoices and then feed this data into common business processes in that industry. Basic cognitive services are often customized, rather than designed from scratch.
An RPA Studio is an interface where you can configure bots, train them, and execute automated tasks. Furthermore, there are drag-and-drop scenario editors for convenience. The Cognitive Mill™ platform has sophisticated pipeline and process management as well as monitoring, administration, and scaling options for each of our customers and our team. The QBIT (internal name) is the core microservice that is responsible for all business logic of our platform, including pipeline configuration and processing flows.
This of course raises the question, “Who will care for these people”, and the answer is unfolding before our eyes right now. With Robotic Process Automation, healthcare workers can manage to keep up with the growing world population. For instance, considering a use-case where email streamlining is automated.
The concept of RPA is not new, and it has already become a standard for optimizing internal processes in enterprises. However, it only starts gaining real power with the help of artificial intelligence (AI) and machine learning (ML). The fusion of AI technologies and RPA is known as Intelligent or Cognitive Automation.
You can also use both to automate your day-to-day tasks and enable automated business decision-making. With the advent of cognitive intelligence, AI aims to adapt the technology so humans can interact with it naturally and daily. They aim to develop a machine that can listen and speak, understand grammatical context, understand emotion and feelings and recognize images.
A construction company managed to significantly improve the speed of customer issue resolution and CSTA with an intelligent automation platform our team created for them. Feel free to check our article on intelligent automation in the financial services and banking industry. Good IA platforms often include a process discovery and assessment tool to save time and remove the guesswork for automation teams.
Vanguard, for example, is piloting an intelligent agent that helps its customer service staff answer frequently asked questions. The plan is to eventually allow customers to engage with the cognitive agent directly, rather than with the human customer-service agents. SEBank, in Sweden, and the medical technology giant Becton, Dickinson, in the United States, are using the lifelike intelligent-agent avatar Amelia to serve as an internal employee help desk for IT support. SEBank has recently made Amelia available to customers on a limited basis in order to test its performance and customer response. That is why we recommend a bottom-up approach to enterprise automation. Start with employing simpler RPA solutions for redundant, error-prone, and repetitive processes.
Because cognitive technologies typically support individual tasks rather than entire processes, scale-up almost always requires integration with existing systems and processes. Indeed, in our survey, executives reported that such integration was the greatest challenge they faced in AI initiatives. The investment firm Vanguard, for example, has a new “Personal Advisor Services” (PAS) offering, which metadialog.com combines automated investment advice with guidance from human advisers. Vanguard’s human advisers serve as “investing coaches,” tasked with answering investor questions, encouraging healthy financial behaviors, and being, in Vanguard’s words, “emotional circuit breakers” to keep investors on plan. Advisers are encouraged to learn about behavioral finance to perform these roles effectively.
The PAS approach has quickly gathered more than $80 billion in assets under management, costs are lower than those for purely human-based advising, and customer satisfaction is high. One might imagine that robotic process automation would quickly put people out of work. But across the 71 RPA projects we reviewed (47% of the total), replacing administrative employees was neither the primary objective nor a common outcome. Only a few projects led to reductions in head count, and in most cases, the tasks in question had already been shifted to outsourced workers.
When it comes to bringing cognitive automation to enterprises, a major challenge faced by developers/SIs is the lack of expertise across verticals and processes – a bottleneck in adding AI and NLP-powered solutions to their suite of services. While building these capabilities in-house is one way of solving the problem, it’s not preferred by most, given the high cost of acquiring the right talent, skills, and infrastructure. This allows for partners to bring in automation in their area of expertise – building multi-functional AI agents on a single platform. The road to adoption will differ for businesses, depending on the clarity, complexity, and standardization of existing business processes. At the lowest level, we are talking about simple automation of different digital tasks — data entry, records consolidation, or input verification.
In this paper, UiPath Chief Robotics Officer Boris Krumrey delves into the ways RPA and AI can best achieve a powerful digital labor, detailing on implementation and operating challenges. You will also need a combination of driver and irons, you will need RPA tools, and you will need cognitive tools like ABBYY, and you are finally going to need the AI tools like IBM Watson or Google TensorFlow. Reaching the green represents implementing Intelligent Process Automation; the driver is RPA, the irons are the cognitive tools like Abbyy and the putter represents the AI tools like TensorFlow or IBM Watson.
As an example, imagine you're at the grocery store, making your weekly shopping excursion. You look for the items you need, make selections among different brands, read the signs in the aisles, work your way over to the cashier and exchange money. All of these operations are examples of cognitive processing.