Robotic Process Automation (RPA)

What is RPA?

Robotic Process Automation (RPA) uses software “robots” to perform basic, repetitive tasks across multiple applications the way a human would. Typical tasks include reading forms, sending confirmation messages, checking for completeness, filing documents, and updating spreadsheets. RPA is designed to reduce manual effort, speed processing, and minimize human error for routine office work.

How RPA works

• A software robot is configured to follow a defined workflow and can launch or operate other software.
• It mimics user interactions (clicking, copying, pasting, data entry) to move data between systems without changing underlying applications.
• RPA does not inherently learn or discover efficiencies; it executes the steps it has been programmed to perform. When combined with AI/ML, it can handle more complex or unstructured data.

Benefits

• Increases efficiency and throughput by automating repetitive tasks.
• Reduces errors associated with manual data entry and routine processing.
• Lowers labor costs and frees employees to focus on higher-value work.
• Often easier and cheaper to implement than full enterprise resource management (ERM) or AI platforms, especially when integrating with legacy systems.
• Can provide rapid ROI for back-office and data-heavy processes.

Common applications

RPA is widely used wherever structured data and repeatable processes exist, including:
– Financial services: compliance checks, KYC updates, credit checks, back-office processing.
– Customer service and CRM: ticket routing, account updates.
– Accounting: reconciliation, invoice processing.
– Healthcare: claims processing, record updates.
– Human resources: onboarding, payroll administration.
– Supply chain: order processing, inventory updates.

Challenges and risks

• Not suited to tasks that require judgment, creativity, or handling highly unstructured information unless augmented with AI.
• Customization and deployment can be costly and time-consuming.
• Poorly governed RPA can create serious problems: for example, automated document signing without oversight led to wrongful foreclosures in the mortgage industry. Lack of control and auditability can produce legal and compliance failures.
• Maintenance burden increases if underlying applications or workflows change frequently.

Implementation considerations

• RPA projects require careful process mapping, governance, and testing to avoid operational and compliance risks.
• Many organizations favor RPA when they need a noninvasive solution that works with legacy systems.
• Development is often tailored to the organization’s processes and may require coding or specialized RPA configuration; this can lengthen development time relative to turnkey solutions.

Types of RPA

• Traditional RPA: hard-coded rules that automate predictable, structured tasks—still the most common approach.
• Intelligent RPA (RPA + AI/ML): combines RPA with machine learning, natural language processing, or image recognition to handle unstructured data and more complex decision-making.

Career outlook

Automation can reduce headcount for repetitive roles, but demand remains strong for professionals who design, build, and manage RPA solutions—roles such as developers, business analysts, product managers, and RPA architects.

Market note

Industry research projects significant growth in the RPA market, reflecting broad interest across sectors that handle high volumes of routine data and filing work.

Key takeaways

• RPA automates repetitive, rules-based office tasks by mimicking human interactions with software.
• It delivers efficiency gains and cost savings, particularly where legacy systems are involved.
• Success requires proper governance, ongoing maintenance, and, when needed, integration with AI for complex or unstructured tasks.
• While RPA can pose risks if unchecked, it offers substantial value when implemented thoughtfully.