Cognitive Automation vs RPA: Choosing the Right Path for Automation

It can be largely used to drive a degree of process efficiency and reduction in routine manual processing. Although it is able to drive significant value but isn’t incompatible with truly transformational change in enterprise functionality due to its inability to deal with complex decision-making tasks. The pursuit of efficiency, cost reduction, and streamlined operations is unceasing and CPA is reshaping how businesses manage intricate and repetitive tasks. CPA is not just a tool but a strategic asset that can significantly enhance business operations. It’s like having an extra pair of hands that are not only capable but also intelligent, learning from each interaction to become more efficient.

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.

Various combinations of artificial intelligence (AI) with process automation capabilities are referred to as cognitive automation to improve business outcomes. The biggest challenge is that cognitive automation requires customization and integration work specific to each enterprise. This is less of an issue when cognitive automation services are only used for straightforward tasks like using OCR and machine vision to automatically interpret an invoice’s text and structure. More sophisticated cognitive automation that automates decision processes requires more planning, customization and ongoing iteration to see the best results.

Differences Between RPA and Cognitive Automation

RPA tools without cognitive capabilities are relatively dumb and simple; should be used for simple, repetitive business processes. 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. Intelligent virtual assistants and chatbots provide personalized and responsive support for a more streamlined customer journey.

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. Unlike other types of AI, such as machine learning, or deep learning, cognitive automation solutions imitate the way humans think. 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. Bots can automate routine tasks and eliminate inefficiency, but what about higher-order work requiring judgment and perception?

Logistics operations (Postnord & Digitate)

In the BFSI industries, Cognitive process automation tools play a pivotal role in fraud detection and risk management. By analyzing vast amounts of transactional data, AI-powered assistants can identify patterns, anomalies, and suspicious activities. This enables businesses to detect and prevent fraud in real-time, safeguarding their customers’ interests and minimizing financial losses. Key distinctions between robotic process automation (RPA) vs. cognitive automation include how they complement human workers, the types of data they work with, the timeline for projects and how they are programmed. Through cognitive automation, enterprise-wide decision-making processes are digitized, augmented, and automated.

Cognitive Process Automation (CPA) is an advanced technological paradigm that leverages artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to automate complex cognitive tasks traditionally performed by humans. It combines elements of AI and automation to emulate human thought processes in decision-making and problem-solving. With language detection, the extraction of unstructured data, and sentiment analysis, UiPath Robots extend the scope of automation to knowledge-based processes that otherwise couldn’t be covered. They not only handle the automation of unstructured content (think irregular paper invoices) but can interpret content and apply rules ( unhappy social media posts). Language detection is a prerequisite for precision in OCR image analysis, and sentiment analysis helps the Robots understand the meaning and emotion of text language and use it as the basis for complex decision making.

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. The same is true with Robotic Process Automation (also referred to as RPA). The phrase conjures up images of shiny metal robots carrying out complex tasks. Especially if you’re not intimately familiar with the tech industry and its automated contributors, Robotic Process Automation probably sounds impressive.

Managing all the warehouses a business operates in its many geographic locations is difficult. Some of the duties involved in managing the warehouses include maintaining a record of all the merchandise available, ensuring all machinery is maintained at all times, resolving issues as they arise, etc. All of these create chaos through inventory mismatches, ongoing product research and development, market entry, changing customer buying patterns, and more. This occurs in hyper-competitive industry sectors that are being constantly upset by startups and entrepreneurs who are more adaptable (or simply lucky) in how they meet ongoing consumer demand.

Developers are incorporating cognitive technologies, including machine learning and speech recognition, into robotic process automation—and giving bots new power. „The ability to handle unstructured data makes intelligent automation a great tool to handle some of the most mission-critical business functions more efficiently and without human error,“ said Prince Kohli, CTO of Automation Anywhere. He sees cognitive automation improving other areas like healthcare, where providers must handle millions of forms of all shapes and sizes. Employee time would be better spent caring for people rather than tending to processes and paperwork. E42, an AI and NLP-powered Cognitive Process Automation platform empowers enterprises with AI co-workers built to automate processes across functions.

However, it is likely to take longer to implement these solutions as your company would need to find a capable cognitive solution provider on top of the RPA provider. You can foun additiona information about ai customer service and artificial intelligence and NLP. Only the simplest tools, initially built in 2000s before the explosion of interest in RPA are in this bucket. A cognitive automation solution is a positive development in the world of automation. A cognitive automation solution for the retail industry can guarantee that all physical and online shop systems operate properly. As a result, the buyer has no trouble browsing and buying the item they want. ServiceNow’s onboarding procedure starts before the new employee’s first work day.

In CX, cognitive automation is enabling the development of conversation-driven experiences. He expects cognitive automation to be a requirement for virtual assistants to be proactive and effective in interactions where conversation and content intersect. „Ultimately, cognitive automation will morph into more automated decisioning as the technology is proven and tested,“ Knisley said.

LATEST ARTICLES

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. Where little data is available in digital form, or where processes are dominated by special cases and exceptions, the effort could be greater. Some RPA efforts quickly lead to the realization that automating existing processes is undesirable and that designing better processes is warranted before automating those processes. RPA tools interact with existing legacy systems at the presentation layer, with each bot assigned a login ID and password enabling it to work alongside human operations employees.

Once a cognitive automation platform understands how to operate the enterprise’s processes autonomously, it can also offer real-time insights and recommendations on actions to take to improve performance and outcomes. If your organization wants a lasting, adaptable cognitive automation solution, then you need a robust and intelligent digital workforce. That means your digital workforce needs to collaborate with your people, comply with industry standards and governance, and improve workflow efficiency. Training AI under specific parameters allows cognitive automation to reduce the potential for human errors and biases.

Deliveries that are delayed are the worst thing that can happen to a logistics operations unit. The parcel sorting system and automated warehouses present the most serious difficulty. They make it possible to carry out a significant amount of shipping daily.

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. It is worth noting that RPA’s ability to wring substantial process improvements from legacy systems, often at relatively low cost, can undermine the business case for large-scale replacement of systems or enterprise application integration initiatives. 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.

They are looking at cognitive automation to help address the brain drain that they are experiencing. „The shift from basic RPA to cognitive automation unlocks significant value for any organization and has notable implications across a number of areas for the CIO,“ said James Matcher, partner in the technology consulting practice at EY. „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.

What Are the Benefits of Cognitive Automation?

RPA started roughly 20 years ago as a rudimentary screen-scraping tool, technology that is used to eliminate repetitive data entry or form-filling that human operators used to do the bulk of. For example, the software could copy data from one source to another on a computer screen. Imagine a finance clerk handling invoice processes by filling in specific fields on the screen. Early RPA was able to take this function off the clerk’s plate by automating that invoice processing. 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.

These six use cases show how the technology is making its mark in the enterprise. In the realm of HR processes such as candidate screening, resume parsing, and employee onboarding, CPA tools can automate various tasks. With the implementation of AI-powered assistants, companies can analyze job applications, match candidates with suitable roles, and automate repetitive administrative tasks. This frees up HR professionals to focus on strategic initiatives like talent development and employee engagement. Once the system has made a decision, it automates tasks such as report generation, data entry, and even physical processes in industrial settings, reducing the need for manual intervention.

Another important use case is attended automation bots that have the intelligence to guide agents in real time. RPA is taught to perform a specific task following rudimentary rules that are blindly executed for as long as the surrounding system remains unchanged. An example would be robotizing the daily task of a purchasing agent who obtains pricing information from a supplier’s website.

The growing RPA market is likely to increase the pace at which cognitive automation takes hold, as enterprises expand their robotics activity from RPA to complementary cognitive technologies. In today’s world, data is at the core of any business, data that comes in various forms. An organization that’s not employing ways to harness it is sure to lag in the cut-throat competition. It can be organized in a predefined format, say a database or spreadsheet with rows and columns – known as structured data. This kind of data can be easily handled and hence, automated using RPA – for the obvious reason that it doesn’t require intelligence to be processed.

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. 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. Therefore, businesses that have deployed RPA may be more likely to find valuable applications for cognitive technologies than those that have not. CIOs are now relying on cognitive automation and RPA to improve business processes more than ever before.

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.

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. It uses AI algorithms to make intelligent decisions based on the processed data, enabling it to categorize information, make predictions, and take actions as needed. Consider you’re a customer looking for assistance with a product issue on a company’s website. Instead of waiting for a human agent, you’re greeted by a friendly virtual assistant. They’re phrased informally or with specific industry jargon, making you feel understood and supported.

These systems have natural language understanding, meaning they can answer queries, offer recommendations and assist with tasks, enhancing customer service via faster, more accurate response times. By automating cognitive tasks, organizations can reduce labor costs and optimize resource allocation. Automated systems can handle tasks more efficiently, requiring fewer human resources and cognitive process automation allowing employees to focus on higher-value activities. Another benefit of cognitive automation lies in handling unstructured data more efficiently compared to traditional RPA, which works best with structured data sources. In this domain, cognitive automation is benefiting from improvements in AI for ITSM and in using natural language processing to automate trouble ticket resolution.

• Chart was able to save an annual amount of $240,000 from late payments alone.
• Cognitive automation can use AI to reduce the cases where automation gets stuck while encountering different types of data or different processes.
• In contrast, cognitive automation excels at automating more complex and less rules-based tasks.
• While chatbots are gaining popularity, their impact is limited by how deeply integrated they are into your company’s systems.

Cognitive automation can uncover patterns, trends and insights from large datasets that may not be readily apparent to humans. With these, it discovers new opportunities and identifies market trends. 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. One organization he has been working with predicted nearly 35% of its workforce will retire in the next five years.

An example of cognitive automation is in the field of customer support, where a company uses AI-powered chatbots to provide assistance to customers. Comparing RPA vs. cognitive automation is „like comparing a machine to a human in the way they learn a task then execute upon it,“ said Tony Winter, chief technology officer at QAD, an ERP provider. After implementing CRPA into their system, the company built conversational and process paths into their claims systems that automated connecting with claimants using two-way text messages. In the end, the company reduced the claims processing time from three weeks to one hour, saving the company roughly $11.5 million.

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. ‍You might’ve heard of a Digital Workforce before, but it tends to be an abstract, scary idea. A Digital Workforce is the concept of self-learning, human-like bots with names and personalities that can be deployed and onboarded like people across an organization with little to no disruption. From web applications to mobile platforms and voice interfaces, we provide versatile deployment options via a single omnichannel interface to meet your specific requirements. This is where Cognitive Process Automation (CPA) strides in as a game-changer.

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. 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.