RPA and the First Steps in Enabling Cognitive Automation

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. Training AI under specific parameters allows cognitive automation to reduce the potential for human errors and biases. This leads to more reliable and consistent results in areas such as data analysis, language processing and complex decision-making. Thus, cognitive automation represents a leap forward in the evolutionary chain of automating processes – reason enough to dive a bit deeper into cognitive automation and how it differs from traditional process automation solutions. Given its potential, companies are starting to embrace this new technology in their processes. According to a 2019 global business survey by Statista, around 39 percent of respondents confirmed that they have already integrated cognitive automation at a functional level in their businesses.

It now has a new set of capabilities above RPA, thanks to the addition of AI and ML. Some of the capabilities of cognitive automation include self-healing and rapid triaging. One of the most important parts of a business what is cognitive automation is the customer experience. The cognitive solution can tackle it independently if it’s a software problem. If not, it alerts a human to address the mechanical problem as soon as possible to minimize downtime.

On-boarding and off-boarding employees (Asurion & ServiceNow)

Companies looking for automation functionality will likely consider both Robotic Process Automation (RPA) and cognitive automation systems. While both traditional RPA and cognitive automation provide smart and efficient process automation tools, there are many differences in scope, methodology, processing capabilities, and overall benefits for the business. Cognitive automation creates new efficiencies and improves the quality of business at the same time.

Make automated decisions about claims based on policy and claim data and notify payment systems. While these are efforts by major RPA vendors to augment their bots, RPA companies can not build custom AI solutions for each process. Therefore, companies rely on AI focused companies like IBM and niche tech consultancy firms to build more sophisticated automation services.

Human intervention in the development of AI 🤖🤝

Cognitive automation may also play a role in automatically inventorying complex business processes. Processors must retype the text or use standalone optical character recognition tools to copy and paste information from a PDF file into the system for further processing. Cognitive automation uses technologies like OCR to enable automation so the processor can supervise and take decisions based on extracted and persisted information. “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.

• RPA bots can also work around the clock, nonstop, much faster, and with 100% accuracy and precision.
• Digitate‘s ignio, a cognitive automation technology, helps with the little hiccups to keep the system functioning.
• Cognitive automation performs advanced, complex tasks with its ability to read and understand unstructured data.
• It is rule-based and does not require much coding using an if-then approach to processing.

The goal of cognitive systems is to assist humans without their help. For instance, at a call center, customer service agents receive support from cognitive systems to help them engage with customers, answer inquiries, and provide better customer experiences. For instance, Religare, a well-known health insurance provider, automated its customer service using a chatbot powered by NLP and saved over 80% of its FTEs. The organization can use chatbots to carry out procedures like policy renewal, customer query ticket administration, resolving general customer inquiries at scale, etc.