Top 10 RPA use cases by industry & real-life examples

RPA bots help streamline many financial and accounting tasks, never getting tired and operating 24/7. What is more, they can perform high-volume standardized operations, like data entry and processing, faster and more accurately than humans with a close-to-zero error rate. 

When enhanced with AI capabilities, RPA bots can identify, extract, and interpret financial data from scanned documents, images, and other unstructured data. According to McKinsey, approximately 60% of the financial services companies participating in the survey have already implemented AI-enabled RPA solutions in their operations.

Insurance companies can be overwhelmed by a massive volume of time-consuming and repetitive paperwork, traditionally handled manually. Implementing the RPA technology, companies can delegate many of these tasks to software bots, enabling employees to concentrate on more complex tasks, such as data analysis or customer experience management. According to Accenture, the automation of mundane tasks can lower the cost of underwriting and claims processing in the insurance sector by 30-40%.

AI-enabled RPA bots can scan disparate data sources to gather heterogeneous information for claim processing. Moreover, an intelligent automation solution can detect inconsistencies between the submitted claims and supporting documents that can indicate fraudulent activities.

For medical professionals, clinical documentation management, including data entry, takes up to 16.5 hours per week on average. Considering employee shortage in the healthcare sector, automating such repetitive tasks will help medical professionals handle more patients and improve overall job satisfaction. For example, if the patient switches healthcare providers, a medical receptionist can start an RPA bot to process their previous health records (provided as PDF files or paper documents) and enter key information into the EHR system. RPA bots can also help handle administrative tasks like matching patient appointment requests with the physicians’ schedules or updating patient information in the healthcare CRM.

Pharmacy chains can also apply RPA to optimize routine tasks, like accurately monitoring medication inventory, updating inventory levels, and alerting the staff about low stocks.

80% of retailers expect intelligent automation, including AI-enabled RPA solutions, to become mainstream, according to UiPath. The source also claims that 60% of critical consumer and retail activities are automatable. 

Enhanced with ML models, RPA bots help monitor store inventory. They can enter data about new incoming shipments from invoices to the inventory management system, send notifications to procurement managers about low stock, and predict the potential SKU demand using ML algorithms and historical sales data. 

AI-powered RPA software also helps monitor promotion efficiency by collecting sales data over time, classifying it, comparing it against historical data and set KPIs, and generating promotion performance reports.

Being a part of the retail software ecosystem, RPA bots can contribute to business growth and customer satisfaction.

According to a UiPath survey, 60% of telco companies consider automation a critical driver for digital transformation for the next five years. Implementing RPA technology can reduce the time of human intervention by 40% by 2027. No wonder 87% of telecom and tech leaders defined automation as their top business priority. 

Human resources teams perform numerous time-consuming tasks that can be automated, such as talent search, new employee onboarding, training planning, payroll processing, and exit management. 

According to the Hackett Group, 75% of companies have already implemented RPA solutions for their HR services in 2024. Meanwhile, the Kofax study suggests that 78% of companies plan to automate their employee onboarding process with intelligent RPA solutions.

While physical robots are transforming the plant floor, RPA takes care of other workflows and processes in the manufacturing sector. 

In manufacturing, business software enhanced with ML models help employees predict demand and plan raw materials procurement. RPA bots with integrated ML algorithms can analyze historical data and make accurate demand forecasts. Based on the ML-generated insights, RPA bots can scan inventory to check if there are enough finished products or raw materials for their production. In case of inventory shortfall, the bot can notify the procurement manager or create a new purchase order.

According to the Global Lighthouse Network, automation in manufacturing, including RPA, AI, and IoT technologies, can result in 30%-90% faster time to market, up to 200% higher factory output, and 10%-40% lower operating costs.

The automotive RPA market is projected to experience a 32.6% growth from 2024 to 2030. Enhanced with AI, process automation solutions can handle tedious tasks such as order and invoice processing, manual vehicle or customer data entry and verification, report generation (e.g., on vehicle financing eligibility checks), and others. 

RPA helps automotive companies ensure operational cost-efficiency, reduce delivery delays, and create cohesive and error-free documentation, enabling employees to focus on high-quality customer services.

Robotic process automation in real estate aims to free up employees from numerous time-consuming and repetitive tasks. ML-enhanced RPA bots can process a plethora of real estate data from disparate sources, like property listings, sales records, tenant records, or rental price trend reports. Then, bots can extract and classify relevant property data and enter it into standardized forms to create digital records and comprehensive property reports.

As a part of customer support, AI-enhanced RPA chatbots integrated into property portals can process tenant requests in spoken language, analyze the context and emotions of user communication, provide accurate answers, help schedule property tours, and notify employees if their involvement is required.