What is RPA? Everything You Need to Know About It

Robotic Process Automation (RPA) is an important element of the ‘Future of Work’ toolkit. According to research, about 70% to 80% of rules-based business processes can be automated. Large organizations have realized the benefits of automation and are trying to utilize this quick and effective tool. In this blog, [...] The post What is RPA? Everything You Need to Know About It appeared first on AutomationEdge.

What is RPA? Everything You Need to Know About It

Robotic Process Automation (RPA) is an important element of the ‘Future of Work’ toolkit. According to research, about 70% to 80% of rules-based business processes can be automated. Large organizations have realized the benefits of automation and are trying to utilize this quick and effective tool. In this blog, we will give you a rundown of everything you need to know about RPA, from its benefits to use cases, and more. 

At first glance, RPA may sound like a theoretical machine in the lines of self-aware artificial intelligence, but it’s not as much a new set of technology as it is the application of technology in day-to-day business processes.

What is RPA?

Robotic Process Automation (RPA) is a technology that uses software robots—or “bots”—to automate repetitive, rules-based business tasks such as data entry, invoice processing, and report generation. Unlike AI, which learns and adapts, RPA follows predefined workflows to increase efficiency, cut costs, and reduce human error.

In simple terms: RPA is like a digital workforce that performs routine tasks faster, more accurately, and at scale. RPA is not self-aware AI—its software bots automating rule based tasks—but increasingly integrated with AI/ML for cognitive automation.

RPA as AI Chatbot and Its Influence on the Customer Care Industry

Chatbots have existed for years and are now going mainstream by providing support to apps, social networking sites, Microsoft, etc.

Reports published by Pew Research in 2015, suggest that mobile messengers are used by 36% of smartphone owners. And this number will grow to 49% in the age group of 18-29 years.

A survey by a market research firm One Reach, researched on US consumer behavior towards texting in customer service applications and found out that 64% of consumers would prefer texting over voice as customer service support, and 77% of consumers have a positive approach towards companies that offer text capability.

Mobile messengers such as WhatsApp, WeChat, and Facebook Messenger have become a popular means of communication on mobile phones. WhatsApp has a billion monthly active users, whereas Facebook Messenger and WeChat has about 900 million and 700 million users respectively. In terms of popularity, they have surpassed social networks proving the importance of Artificial Intelligence in the customer care system of organizations.

[Also Read:  How AI Chatbot Is Transforming Customer Care industry ]

RPA for the Modern Enterprise

The key to effective RPA implementation is to understand its benefits and challenges. While manual processes are inefficient and capable of errors, RPA enables the modern enterprise in the following ways:

  • It increases process speed along with a reduction in errors
  • Since IT departments spend 30% of their time on low-level tasks, automation allows them to focus on higher skilled work, improving business and employee satisfaction
  • 50% of companies spend $5 to $25 on a manually-processed invoice. RPA increases the quality of data by reducing manual data edits and reducing compliance risks

Traditional vs Cognitive vs Agentic RPA

Feature / Criteria Traditional RPA Cognitive RPA Agentic RPA
Definition Automates repetitive, rule-based tasks Combines RPA with AI to handle semi-structured data Uses autonomous agents that plan, act, and learn
Core Technology Rule engines, scripting AI/ML, NLP, OCR LLMs, multi-agent systems, reinforcement learning
Human-like Decision-Making No Limited (pattern recognition) Yes (autonomously adjusts to goals & context)
Data Handling Structured data only Structured + semi-structured Unstructured, multi-modal, and dynamic data sources
Learning Ability None (static scripts) Learns from data over time Continuously learns and adapts autonomously
Interaction Style Mimics UI clicks and keystrokes Interprets data, reads documents Understands goals, context, and user intent
Scalability Limited by ruleset complexity Moderate with training data Highly scalable through self-organization
Ideal Use Cases Invoice entry, data scraping, form filling Claims processing, email classification Intelligent assistants, end-to-end process automation
Deployment Speed Fast (script-based setup) Moderate (requires training models) Slower initially but self-improving over time
Maintenance Effort High – changes break scripts Moderate – models retrainable Low – learns and self-corrects in real time
User Autonomy Low Moderate High (acts as a co-pilot or digital worker)
Example Tools / Platforms UiPath, Automation Anywhere (classic bots) AutomationEdge with IDP, IBM RPA + Watson Microsoft Copilot, UiPath Autopilot, Open Agents
Future Outlook Stable but limited scalability Growing adoption in digital operations Emerging frontier in AI-driven enterprise automation

Future Trends: A Shift in How Organizations Are Doing Business

RPA is currently one of the most popular AI application, as 98% of IT business leaders consider automation to be essential in driving profits. Listed here are some of the trends related to automation, which will help in finding out where exactly it’s headed in the future:

  • RPA can play an important role in the analysis of Big Data and the Internet of Things by streamlining data management. The software can analyze available data along with the time taken to process it, and the number of automation activities left in the end
  • These tools will enable industries to utilize a flexible and scalable workforce, resulting in a reversal of outsourcing jobs
  • When integrated with other technologies, the benefits of RPA transcend and yields even better and more efficient outcomes
  • RPA software works on customer experience enhancement by mimicking human activities and has proven to be a good alternative to humans, while creating a loyal relationship with customers

Why RPA Matters in 2025

According to Gartner, more than 90% of organizations worldwide will adopt some form of RPA by 2025 as part of their digital transformation strategy. Businesses across banking, healthcare, HR, and IT are using RPA to improve accuracy, speed, and compliance while freeing employees to focus on innovation. The global RPA market is projected at ~$6–23 billion in 2025, growing rapidly as enterprises shift to cloud and AI powered automation.

Top RPA Trends in 2025

Automation is evolving from simple task bots to intelligent ecosystems. Here are the key RPA trends shaping industries:

  • AI + RPA (Intelligent Automation): Combining AI, ML, and NLP with RPA for smarter decision-making.
  • Hyperautomation: Integrating RPA with process mining, workflow automation, and analytics for end-to-end automation.
  • Cloud RPA: Growing adoption of SaaS-based RPA tools for remote scalability.
  • Industry-Specific Solutions: Healthcare EVV bots, BFSI fraud detection, HR onboarding automation.
  • Citizen Development: Low-code RPA tools enabling business users (not just IT) to create bots.

Key Benefits of RPA

RPA is no longer just about cost savings—it’s about enabling agility and growth.

  • Faster Processes: Reduces execution time by up to 70%.
  • Lower Costs: Saves 30–50% in operational expenses.
  • Error-Free Workflows: Eliminates human errors in repetitive tasks.
  • Better Compliance: Creates audit trails for every automated process.
  • Scalability: Bots can be scaled instantly during peak workloads.
  • Employee Productivity: Frees teams to focus on strategic, value-driven work.

Top 10 common Use Cases in Every Industry

RPA has transformed numerous business processes. Researchers at Hadoop estimate that companies will potentially save between $5 trillion to $7 trillion with RPA, by 2025. They also predict that the software will give an output of 140 million FTEs, by performing day-to-day business tasks. Following are some examples/use cases that exist in various industries:

  • Software installations
  • Data migration and entry
  • Procure-to-pay
  • Quote-to-cash
  • Periodic report preparation and dissemination
  • Customer onboarding
  • Creating and delivering invoices
  • Customer Service
  • Updating CRM
  • Generating mass emails

RPA Use Cases by Industry:

Industry Function / Process Automated Key Benefits
Banking & Finance Invoice Processing, KYC Verification, Report Generation Faster processing time
Reduced manual errors
Improved compliance
Healthcare Patient Data Entry, Billing, Claims Processing Enhanced accuracy
Faster reimbursements
Better patient experience
Insurance Claims Intake, Underwriting, Policy Administration Lower processing costs
Fraud detection
Improved customer trust
Retail & eCommerce Order Processing, Inventory Updates, Customer Onboarding Real-time updates
Reduced stockouts
Enhanced customer satisfaction
Telecom Customer Service, CRM Updates, Billing Disputes 24/7 support automation
Error-free CRM
Reduced churn
Manufacturing Supply Chain Management, Quote-to-Cash, Report Generation Streamlined operations
Faster quote cycles
Reduced delays
HR & Payroll Employee Onboarding, Timesheet Processing, Payroll Management Time-saving
Reduced HR workload
Accurate payroll
IT Services Ticket Management, Data Backup, System Monitoring Quick response time
Reduced downtime
Increased productivity

Things to Consider While Selecting the Right RPA Tool

Among the three types of RPA tools – RPA bots, Self-learning solutions, and Cognitive/intelligent automation – the third tool cognitive/intelligent automation solutions are the most in demand. There have also been cases where RPA sellers have recommended programmable bots, rather than the cognitive automation solutions.

While choosing the RPA tool, the things to remember are that the tool should be easily integrated with the existing systems, it should be scalable with the growth of the company, and should be able to gather and analyze operational data and offer a detailed report about the process.

[ Also Read:  Selecting The Right RPA Tool, Doing It Right The First Time ]

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Things to Remember While Implementing RPA

There are few points you will have to keep in mind before RPA implementation:

  1. Identify the process that needs to be automated first – The pilot project for automation needs to be identified first before RPA is implemented on all processes. Once you are sure of the benefits, you can choose other processes. In a similar way, a process can be automated entirely or partly. Either way, understand the process first and the effect of automation on it, before selecting it as the pilot project.
  2. Human supervision is needed in automation – Ensure that the team has RPA certified professionals or at least are trained about RPA, the changes in the process after implementation, and the measures needed to be taken after deployment.
  3. Allocating budget – Automation is a costly investment, so you need to make sure that enough budget is allocated for implementing the process. You have to keep in mind that few processes show immediate result while others take time to provide a good ROI.
  4. Selecting the right vendor – Once the objective for automation is defined, stakeholders are convinced, and the process has been identified, you need to select the right software and vendor. The vendor should be technologically ahead, should provide training to use the software, and should provide customer support during initial use of the software

[ Also Read:  10 tips for successful Robotic Process Automation ]

Creating RPA Business Case for Your Management

Organizations are constantly looking for ways to improve their business processes, and RPA provides the opportunity to transform these processes at a low cost. Knowing that without a clear plan a small RPA pilot is likely to fail, you need to build an RPA business case that will deliver long-term results. You can either start small or first create a comprehensive automation strategy to seek the funding you require.

The approach to building a business case that delivers long-term results in RPA requires a clear plan, and following is a list of business case considerations related to RPA implementation:

  • Clear on the goals and outcomes – You should be clear about the outcomes that you are expecting with the change
  • Doing it right the first time – Complete a thorough review before starting the process
  • The environment of the organization – Understand whether your business is inclined towards automation
  • Delivering results long-term – See whether you will be able to create value by making a change on major initiatives

You will primarily need to do a comprehensive scan of your business processes, to understand what processes will be more conducive to automation. Once they are analyzed, you can choose the processes that will be targeted for automation.

Once the bots are operational, you can conduct a process evaluation to understand the capabilities of the bots. Choose a process for a proof of concept and once the bot is operational you can create a video of it performing the process. This is to highlight and have a clear understanding of the different steps taken by the bot, for justification and moving forward with the broader use of RPA.

Now that the original proof of concept is completed, start to proceed on the other processes with the additional bots. Your next steps in automation should include the following:

  • Review the target areas and output
  • Plan on your business priority and execution
  • Create an RPA roadmap for your business
  • Make a project team and engage an automation partner
  • Start off with a detailed design phase

These steps are required to be well-defined while creating a business case. Once the case is completed and approved, the requirements for the procurement of RPA vendor should be finalized. While there are different approaches your company can take for developing a business case, the most important one is to create a strategy and secure the required funding.

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Conclusion:

RPA implementation in organizations enables effective redeployment of employees to much more value-added roles. This, in turn, increases employee satisfaction, ROI, and customer satisfaction.

RPA can boost development across industries, and although the technology is in its infancy, experts believe that it will be worth $3.1 billion by 2019 and $4.9 billion by 2020. RPA systems are being welcomed by organizations eager to increase productivity, cut costs, and gain a competitive edge.

RPA is not just a cost-cutting tool—it’s a growth accelerator. From banking to healthcare to HR, automation empowers organizations to boost efficiency, compliance, and customer experience. As RPA integrates with AI and cloud solutions, it’s becoming the foundation of hyperautomation in the workplace.

The RPA market is projected to reach $25 billion by 2030, proving its long-term relevance. Businesses that adopt RPA today will be better positioned for agility, innovation, and competitive advantage in the years ahead.

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Frequently Asked Questions

RPA is software that automates repetitive, rules-based tasks like data entry and reporting—saving time and reducing errors.
No. RPA follows predefined rules, while AI learns, adapts, and makes predictions. Together, they form Intelligent Automation.
Popular RPA platforms include AutomationEdge, UiPath, Automation Anywhere, and Blue Prism.
Yes. With AI integration and hyperautomation, RPA is more relevant than ever for efficiency, compliance, and scalability.
Banking, healthcare, HR, IT support, retail, and manufacturing are the top industries adopting RPA.
RPA works by mimicking human actions such as clicking, typing, copying, and pasting within software applications. Bots follow predefined rules to complete tasks quickly and accurately.
Yes. Many RPA platforms offer low-code or no-code interfaces, allowing business users to design bots without deep programming knowledge.
RPA is evolving into hyperautomation with AI integration. By 2030, most enterprises will combine RPA with AI for end-to-end automation across industries.

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