Cognitive automation is adept in managing unstructured data

Cognitive automation is adept in managing unstructured data. Source: Shutterstock

Cognitive automation – the next frontier of enterprise RPA?

  • Cognitive automation focuses on completing tasks that require judgment and critical thinking
  • These tools are suited to sift through unstructured data and derive valuable information 
  • We explored three sectors which could leverage cognitive automation’s potential

Cognitive automation is being heralded as the next frontier of robotic process automation (RPA). But unlike RPA, which adheres to a predetermined set of rules and is usually implemented to simplify and automate repetitive tasks, cognitive automation focuses on knowledge-based tasks, where decisions have to be made.

Cognitive functions refers to the higher brain functions found in humans and other mammals, where reasoning is carried out to make judgments, based on the available data. Cognitive automation, on the other hand, utilizes artificial intelligence (AI) driven technologies including machine learning (ML) and natural language processing (NLP) to sift through available data, and make “intelligent” decisions that can then be fully automated.

Powered by AI technology, cognitive automation possesses the capacity to handle complex, unstructured, and data-laden tasks. Cognitive automation capabilities have already been adopted by various organizations and across value chains, helping businesses break existing trade-offs between efficiency, expenditure, and speed. This extension of automation brings forward new opportunities and room for innovation, expanding digital transformation reach.


Take the retail sector as a starting point to discuss the benefits of cognitive automation: One of the challenges faced in retail is harmonizing data between different stores. Data silos are easily created when disparate sources of data are gathered, stored, and managed differently according to the specific store’s management or operational procedures. Though a uniform plan to manage data may be in place, it may be more challenging than envisioned.

Cognitive automation, emerging from the foundations of RPA, is suitable in this sense to not only streamline data collection processes but also exercise uniformity and consistency in business operations.

Incoming data across the supply chain, from product providers, partners, retailers, and consumers, comprises various formats like receipts, emails, images, and digital documents. AI techniques applied to automation can extract the values and insights from these elements of unstructured data and churn them into new datasets crucial for business decision-making.   

Businesses with a holistic view of their data can translate the knowledge into action plans like enhancing inventory forecasts and supply chain management, automating customer-facing services, and improving marketing campaigns.


The healthcare industry deals with streams of unstructured data on a daily basis. Similar to how cognitive automation can boost efficiency in orchestrating a vast amount of data from disparate locations in retail, it can collect and analyze medical data from multiple sources in healthcare as well.

Medical data that includes patient records, business reports, diagnostic tools, and others bear a wealth of knowledge but is also challenging to decipher and requires medical professions to invest valuable time and resources to sift through the data. Cognitive automation baked with AI capabilities like NLP (natural language processing), text sentiments, and corpus analysis can derive meaningful findings and conclusions in this aspect.

There is also a sense of readiness and confidence towards emerging technologies in the healthcare industry, as covered in TechHQ.

The American Medical Association (AMA) has been pushing digital initiatives to ensure its members are able to access the needed support to embrace emerging technologies. 

AMA Board Chair Jesse Ehrenfeld said, “the rise of the digital-native physician will have a profound impact on healthcare and patient outcomes, and will place digital health technologies under pressure to perform according to higher expectations.”


Since employee onboarding is an essential and repeated office process across all industries, with predictable roles and procedures, it is a perfect testing ground for the benefits cognitive automation can provide.

Cognitive automation can help automate the onboarding process by providing the necessary tools, access, and information employees need from day one. For example, cognitive automation can automatically create computer credentials such as Slack logins, business email accounts, and enroll new hires into departmental training and orientation. This new-age technology can take a step further by setting up meetings for new hires and managers, completing manual HR workload without room for human error or complexity.

This could be a crucial advancement in HR processes as the ongoing pandemic has disrupted the routine procedure of onboarding employees. Cognitive automation tools can simplify the onboarding process for new hires that may start their first days outside of the office and provide the support needed for new employees joining the organization.