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Reimagining Conventional RPA: An introduction to Cognitive Automation

Across all industries, businesses are riding the digital transformation wave. Global companies depend on technology to add value-creating differentiators to their products and find newer ways to enhance their customer experience. The digital-first economy opened more unique opportunities for most businesses. On the contrary, it has also intensified competition to acquire new customers and grow market share. Investments in technology solutions and services have emerged as the new priorities across all boardrooms to remain competitive in the long term.

What is cognitive automation?

The amalgamation of Artificial Intelligence (AI) and Cognitive Computing is acting as catalysts for organizations seeking to achieve operational excellence through automation. Cognitive automation brings intelligence to enhance the performance of unstructured and semi-structured data-intensive business processes. AI improves the scope of actions that a typical process automation workflow does. It simplifies the real-time processing of such data for better decision-making. It enhances organizational operational efficiency and saves costs.

According to a McKinsey study, businesses that adopted cognitive automation tools were able to:

  • Automate approximately 50–70 percent of tasks.
  • Cut down data processing time by 50 to 60 percent
  • Decrease annual labor expenditure by 20–30%
  • Achieve triple-digit ROI

Cognitive Automation Pillars

The technologies that power automation and cognitive decision-making across the business process include data mining, text analysis, natural language processing, machine learning model, AI, and more.

  • Optical Character Recognition - It uses a combination of machine learning models and fuzzy logic to match patterns across scanned documents to extract relevant pieces of information for further processing.
  • Machine Learning: It improves a system's performance and accuracy through continuous learning based on real-time data; it eliminates the need to explicitly hard code instructions.
  • Data Mining: Data is mined from documents and simultaneously checked for meaningful patterns, trends, or correlations based on existing warehouses/repositories, often using advanced statistical and mathematical modules.
  • Natural Language Processing: NLP is the system's ability to understand and process native human languages and perform necessary actions.
  • Cognitive Reasoning: It is when a system successfully develops real-time decision-making capability often exhibited by a human operator.

What does it mean for enterprises?

Fusing different AI features with automation helps organizations to achieve automation excellence. It is an ideal state when automation can be seamlessly scaled across multiple business processes and seamlessly handle the increasing volumes of semi-structured and unstructured information.

Cognitive automation builds efficiencies to every business process core by improving the quality of operations and does it at scale. Digital transformation officers are keen on keeping cognitive automation at the center of their digital transformation plans for global business processes.

Cognitive Automation benefits!

Enterprises often face an increasing number of challenges: to enhance operational efficiency, enhancing real-time decision-making capabilities, building competitive advantage, retaining customers, enhancing customer experience, compliance are just some of the impediments. Cognitive automation has proven its effectiveness in addressing most of the challenges by intelligently optimizing day-to-day activities across business processes for users and operators.

The following factors make cognitive automation the preferred choice of technology solution to digitize operations across business process :

  • Cost reduction: Cognitive automation can help companies save up to 70% of their additional resource allocation cost.
  • Increased Operational Efficiency: Automating mundane and repetitive tasks helps staff members to focus on business priorities. It uplifts staff morale and productivity, which contributes to increased operational efficiency.
  • Reduce error rates: Cognitive automation can seamlessly process semi structured and unstructured data, which otherwise, when processed by a human operator, is time-consuming and may lead to unwanted errors.
  • Real-time decision-making: Cognitive intelligence systems are built to perform decision-making activities usually performed by human operators. It minimizes the need for supervision, increasing overall productivity and efficiency.

About the author

Aritro Chatterjee, Product Management, Kanverse.ai

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