Artificial Intelligence (AI) vs. Robotics Process Automation (RPA)

With buzzwords such as Artificial Intelligence (AI), and Robotics Process Automation (RPA) floating around, it’s often difficult to grasp their actual meaning and how they are different from one another. In this post, we definitions aim to clear the air around these technologies and their capabilities.

According to Marvin Minsky, “Artificial Intelligence is the science of making machines do things that would require intelligence if done by men.”

AI is the computer systems’ ability to learn, reason, think, and perform tasks requiring complex decision-making. It involves the ability of computer systems to perform tasks that typically require human intervention and intelligence. AI enables the systems to perform complex tasks that require human judgment to analyze, evolve over time, and look for better ways to execute based on experience.

Most AI technologies work towards extracting meaning from images, text, or speech, detecting patterns and anomalies, and making recommendations, predictions, or decisions. In general, they have two functions:

  • Capturing information through vision recognition (e.g., recognizing a face or photo), sound recognition (e.g., transcribing spoken words), search (e.g., extracting data from unstructured documents), and data analysis (e.g., identifying clusters of behaviors in customer data).
  • Turning gathered information into useful insights through natural language processing (e.g., extracting meaningful data from an email), reasoning (e.g., should I act based on the information given), or prediction (e.g., predicting buying behavior based on past purchases).

AI can train itself or be trained to automate more complex and subjective tasks through pattern recognition. It can process natural language and unstructured data, respond to a change in the environment, adapt, and learn the new way.

AI is used as a parent term when it comes to RPA. When people first hear about “Robotic Process Automation,” they tend to imagine physical robots wandering around offices performing human tasks. But in reality, it is merely a software package created to fulfill the kinds of administrative tasks that otherwise need stop-gap human handling.

In other words, Robotic Processing Automation is the use of software ‘robots’ (aka bots) mimicking human actions to perform a well-defined business process, previously performed by people, such as transferring data from multiple sources like email and spreadsheets to systems of record like Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems.

Because RPA can sit on top of an IT infrastructure, a company can implement the technology without altering existing infrastructure and systems. RPA can bring instant value to the core business processes, including employee payroll, employee status changes, new hire recruitment and onboarding, accounts receivable and payable, invoice processing, inventory management, report creation, software installations, data migration, and vendor onboarding, etc. to name a few applications.

Robotic Process Automation has abundant applications in financial services, healthcare and pharmaceuticals, outsourcing, retail, telecom, energy and utilities, real estate, and many more sectors. Combined with Artificial Intelligence (AI), it can help handle unstructured data in support of fraud / Anti Money Laundering (AML).

Best solutions by RPA

RPA is best suited for performing repetitive tasks in nature and executed by following a fixed set of rules. Some of the best solutions addressed by RPA are as follows:

  • Rules-based processing with structured digital inputs such as credit card activation or fraud checking
  • Repetitious transactional processing such as SIM swaps or invoice processing
  • Complex/mission-critical processing – pension redemptions and financial reconciliation
  • High transaction volumes such as billing or new handset order processing
  • Process adherence/quality issues such as policy renewals or policy migrations
  • Fluctuation in demand or backlogs such as with new product launches
  • “Swivel Chair” processes such as Human Resource onboarding or launching a new online product where there is no integration
  • Customer service: RPA can offer better customer service by automating contact center tasks, including uploading scanned documents, verifying e-signatures, and verifying information for automatic approvals or rejections.
  • Supply chain management: RPA can be used for procurement, automating order processing and payments, monitoring inventory levels, and tracking shipments.

Benefits of RPA

  • RPA eliminates human error, improves compliance, audibility, and visibility, reinforces an audit trail, and offers better control over end-to-end processes.
  • Robots can quickly and easily be scaled up and down to handle demand fluctuations and seasonal variations.
  • RPA increases productivity significantly with the potential to operate 24×7, requiring fewer FTEs to complete repetitive tasks.
  • RPA yields around a 40 percent reduction in operational costs.
  • The average cost of implementing and running a robot is much less than the equivalent FTE costs and decreases with large-scale deployments.
  • Eradicating monotonous tasks boosts satisfaction among the staff as well as the customers. This can free up time and effort invested in data administration and enable them to focus on high-value work.

When business and technology leaders look for RPA technologies, they should consider several things, including:

  • Scalability: Companies should look for RPA platforms that can be centrally managed and scale massively. They shouldn’t select RPA software that requires them to deploy software robots to desktops or virtualized environments.
  • Speed: Companies should design and test new robotic processes in a few hours or less and optimize the bots to work quickly.
  • Reliability: Companies should look for tools with built-in monitoring and analytics that enable them to monitor their systems’ health and thousands of automated tasks.
  • Standardized/structured data: RPA tools should provide standardized, structured digitized data.
  • Simplicity: Organizations should look for simple products that any employee in the business can build and use to handle various tasks, including collecting data and turning content into insights that enable leaders to make better decisions.
  • Intelligence: The best RPA tools support simple, task-based activities, read and write to any data source by taking advantage of advanced learning to further improve automation.
  • Enterprise-class: Companies should look for tools built from the ground up for enterprise-grade scalability, reliability, and manageability.

LEAVE A REPLY

Please enter your comment!
Please enter your name here