What is Cognitive Automation? Combination of AI & RPA

A company’s cognitive automation strategy will not be built in a vacuum. While technologies have shown strong gains in terms of productivity and efficiency, “CIO was to look way beyond this,” said Tom Taulli author of The Robotic Process Automation Handbook. Cognitive automation will enable them to get more time savings and cost efficiencies from automation. “Ultimately, cognitive automation will morph into more automated decisioning as the technology is proven and tested,” Knisley said.

In this article, we explore RPA tools in terms of cognitive abilities, what makes them cognitively capable, and which RPA vendors provide such tools. From your business workflows to your IT operations, we’ve got you covered with AI-powered automation. These systems require proper setup of the right data sets, training and consistent monitoring of the performance over time to adjust as needed. 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.

What are examples of cognitive automation?

It can mimic and learn from humans’ experience through machine learning, natural-language processing (English, Chinese, Vietnamese, Indonesian), image-recognition, and predictive analysis. Seetharamiah added that the real choice is between deterministic and cognitive. “Go for cognitive automation, if a given task needs to make decisions that require learning and data analytics, for example, the next best action in the case of the customer service agent,” he told Spiceworks. Cognitive automation has a place in most technologies built in the cloud, said John Samuel, executive vice president at CGS, an applications, enterprise learning and business process outsourcing company. His company has been working with enterprises to evaluate how they can use cognitive automation to improve the customer journey in areas like security, analytics, self-service troubleshooting and shopping assistance.

One of their biggest challenges is ensuring the batch procedures are processed on time. Organizations can monitor these batch operations with the use of cognitive automation solutions. This form of automation uses rule-based software to perform business process activities at a high-volume, freeing up human resources to prioritize more complex tasks.

Cognitive automation examples & use cases

RPA is a simple technology that completes repetitive actions from structured digital data inputs. Cognitive automation is the structuring of unstructured data, such as reading an email, an invoice or some other unstructured data source, which then enables RPA to complete the transactional aspect of these processes. The goal of cognitive systems is to assist humans without their help.

• A cognitive automated system can immediately access the customer’s queries and offer a resolution based on the customer’s inputs.
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• Put differently, AI is intended to simulate human intelligence, while RPA is solely for replicating human-directed tasks.
• Cognitive automation does move the problem to the front of the human queue in the event of singular exceptions.
• 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.

However, this rigidity leads RPAs to fail to retrieve meaning and process forward unstructured data. In addition, businesses can use cognitive automation to automate the data collection process. This means that businesses can collect data from a variety of sources, including social media, sensors, and website click-streams. For example, businesses can use chatbots to answer customer questions 24/seven. 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.

Cognitive RPA solutions by RPA companies

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 best results. Cognitive automation typically refers to capabilities offered as part of a commercial software package or service customized for a particular use case.

A cognitive automated system can immediately access the customer’s queries and offer a resolution based on the customer’s inputs. A new connection, a connection renewal, a change of plans, technical difficulties, etc., are all examples of queries. 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. It handles all the labor-intensive processes involved in settling the employee in.

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As a result CIOs are seeking AI-related technologies to invest in their organizations. 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. RPA performs tasks with more precision and accuracy by using software robots. But when complex data is involved it can be very challenging and may ask for human intervention. Cognitive computing systems are typically used to accomplish tasks that require parsing large amounts of data. For example, in computer science, cognitive computing aids in big data analytics, identifying trends and patterns, understanding human language and interacting with customers.

Cognitive automation is most valuable when applied in a complex IT environment with non-standardized and unstructured data. Cognitive automation expands the number of tasks that RPA can accomplish, which is good. However, it also increases the complexity of the technology used to perform those tasks, which is bad, argued Chris Nicholson, CEO of Pathmind, a company applying AI to industrial operations.

Where to use cognitive automation?

In order for RPA tools in the marketplace to remain competitive, they will need to move beyond task automation and expand their offerings to include intelligent automation (IA). This type of automation expands on RPA functionality by incorporating sub-disciplines of artificial intelligence, like machine learning, natural language processing, and computer vision. “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.

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