Robotic process automation: A path to the cognitive enterprise Deloitte Insights
It must also be able to complete its functions with minimal-to-no human intervention on any level. To manage this enormous data-management demand and turn it into actionable planning and implementation, companies must have a tool that provides enhanced market prediction and visibility. “The problem is that people, when asked to explain a process from end to end, will often group steps or fail to identify a step altogether,” Kohli said. To solve this problem vendors, including Celonis, Automation Anywhere, UiPath, NICE and Kryon, are developing automated process discovery tools. By enabling the software bot to handle this common manual task, the accounting team can spend more time analyzing vendor payments and possibly identifying areas to improve the company’s cash flow.
Cognitive automation creates new efficiencies and improves the quality of business at the same time. As organizations in every industry are putting cognitive automation at the core of their digital and business transformation strategies, there has been an increasing interest in even more advanced capabilities and smart tools. Cognitive automation leverages different algorithms and technology approaches such as natural language processing, text analytics and data mining, semantic technology and machine learning. Besides the application at hand, we found that two important dimensions lay in (1) the budget and (2) the required Machine Learning capabilities. This article will explain to you in detail which cognitive automation solutions are available for your company and hopefully guide you to the most suitable one according to your needs.
The Symphony of Cognitive Process Automation
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. It infuses a cognitive ability and can accommodate the automation of business processes utilizing large volumes of text and images. Cognitive automation, therefore, cognitive process automation marks a radical step forward compared to traditional RPA technologies that simply copy and repeat the activity originally performed by a person step-by-step. RPA tools without cognitive capabilities are relatively dumb and simple; should be used for simple, repetitive business processes. IA is capable of advanced data analytics techniques to process and interpret large volumes of data quickly and accurately.
Attempts to use analytics and create data lakes are viable options that many companies have adopted to try and maximize the value of their available data. Yet these approaches are limited by the sheer volume of data that must be aggregated, sifted through, and understood well enough to act upon. Our global Deloitte firm has a large and growing capability, with a range of thought leaders. For more information within the United States, please contact Peter Lowes at For more information within the UK and Europe, please contact John Middlemiss at
What’s the Difference Between RPA and Cognitive Automation?
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RPA also enables AI insights to be actioned on more quickly instead of waiting on manual implementations. “Cognitive RPA is adept at handling exceptions without human intervention,” said Jon Knisley, principal, automation and process excellence at FortressIQ, a task mining tools provider. “RPA is a technology that takes the robot out of the human, whereas cognitive automation is the putting of the human into the robot,” said Wayne Butterfield, a director at ISG, a technology research and advisory firm. CIOs also need to address different considerations when working with each of the technologies. RPA is typically programmed upfront but can break when the applications it works with change.
An Overture of Benefits
One organization he has been working with predicted nearly 35% of its workforce will retire in the next five years. They are looking at cognitive automation to help address the brain drain that they are experiencing. “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. “Cognitive automation multiplies the value delivered by traditional automation, with little additional, and perhaps in some cases, a lower, cost,” said Jerry Cuomo, IBM fellow, vice president and CTO at IBM Automation. These areas include data and systems architecture, infrastructure accessibility and operational connectivity to the business.
- RPA is typically programmed upfront but can break when the applications it works with change.
- Most businesses are only scratching the surface of cognitive automation and are yet to uncover their full potential.
- As automation becomes a norm in digital businesses, technology professionals are fast embracing it as a tool for creating operational efficiencies.
- “The problem is that people, when asked to explain a process from end to end, will often group steps or fail to identify a step altogether,” Kohli said.
- These are integrated by the IBM Integration Layer (Golden Bridge) which acts as the ‘glue’ between the two.
Cognitive automation requires more in-depth training and may need updating as the characteristics of the data set evolve. But at the end of the day, both are considered complementary rather than competitive approaches to addressing different aspects of automation. You can also check out our success stories where we discuss some of our customer cases in more detail.
Processing these transactions require paperwork processing and completing regulatory checks including sanctions checks and proper buyer and seller apportioning. This shift of models will improve the adoption of new types of automation across rapidly evolving business functions. CIOs will derive the most transformation value by maintaining appropriate governance control with a faster pace of automation.
Thus, Cognitive Automation can not only deliver significantly higher efficiency by automating processes end to end but also expand the horizon of automation by enabling many more use-cases that are not feasible with standard automation capability. Technological and digital advancement are the primary drivers in the modern enterprise, which must confront the hurdles of ever-increasing scale, complexity, and pace in practically every industry. Automating time-intensive or complex processes requires developing a clear understanding of every step along the way to completing a task whether it be completing an invoice, patient care in hospitals, ordering supplies or onboarding an employee. “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. Faster processes and shorter customer wait times—that’s the brilliance of AI-powered automation.
About Deloitte Insights
He counsels Deloitte’s businesses on innovation efforts and is focused on scaling efforts to implement service delivery transformation in Deloitte’s core services through the use of intelligent/workflow automation technologies and techniques. Craig has an extensive track record of assessing complex situations, developing actionable strategies and plans, and leading initiatives that transform organizations and increase shareholder value. As a Director in the U.S. firm’s Strategy Development team, he worked closely with executive, business, industry, and service leaders to drive and enhance growth, positioning, and performance. Craig received a Master of International affairs from Columbia University’s School of International and Public Affairs, and a Bachelor of Arts from NYU’s College of Arts and Science. Deploying cognitive tools via bots can be faster, easier, and cheaper than building dedicated platforms. By “plugging” cognitive tools into RPA, enterprises can leverage cognitive technologies without IT infrastructure investments or large-scale process re-engineering.
This abstract delves into real-world applications, showcasing how businesses can leverage this symbiotic relationship to optimize various facets of their operations. From accelerating data processing and reducing errors to enhancing customer experiences through personalized interactions, the combined force of RPA and AI opens avenues for unparalleled business process optimization. Intelligent automation simplifies processes, frees up resources and improves operational efficiencies, and it has a variety of applications. An insurance provider can use intelligent automation to calculate payments, make predictions used to calculate rates, and address compliance needs. Intelligent/cognitive automation tools allow RPA tools to handle unstructured information and make decisions based on complex, unstructured input.
Variants of cognitive automation
It combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. By deploying scripts which emulate human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems. RPA automates routine and repetitive tasks, which are ordinarily carried out by skilled workers relying on basic technologies, such as screen scraping, macro scripts and workflow automation. But when complex data is involved it can be very challenging and may ask for human intervention.