What is robotic process automation (RPA)?

Robotic process automation (RPA) is a technology that empowers businesses to automate repetitive tasks typically handled by people. These are often tasks that follow a set of defined rules and can include things like data entry, processing transactions, and managing emails. RPA employs software robots, or bots, to replicate human interaction with digital systems and applications. These bots can be configured to perform a wide range of tasks, and they can help give employees time back to focus on more strategic work.

Examples of robotic process automation

RPA has several practical applications in today's business world. Here are a few examples of how RPA may be being used by businesses today:

Invoice processing: An RPA bot can be configured to monitor a specific email inbox for new invoices. When an invoice arrives, the bot opens the attached PDF, uses optical character recognition (OCR) to extract key data like the invoice number, vendor name, amount due, and purchase order number. It then logs into the company's accounting software (like SAP or NetSuite), enters the data into the correct fields, and flags any exceptions for human review.
Customer onboarding: New customer onboarding processes, like information gathering and account creation, can be automated with RPA.
Order fulfillment: The digital aspects of customer order fulfillment can be automated with RPA, including order entry, updating inventory systems, and initiating shipping processes. RPA software bots handle these digital tasks, and can integrate with physical warehouse automation systems to complete any non-digital tasks.

How does robotic process automation work?

Understanding how RPA functions is key to leveraging its potential. It works by using software robots to mimic human actions when interacting with digital systems based on a set of pre-defined instructions and triggers. These robots are designed with specific instructions, which they can execute autonomously. For example, a bot could be configured to log into an application when a specific event occurs, extract data from a structured spreadsheet, and then copy and paste that data into another application.

The automation process typically follows the following steps:

Employee identifies a task suitable for automation
Create a bot using RPA software by recording the steps a person would take to complete the task
Test the created bot to ensure it’s running correctly
Deploy the bot into the organization

While standard RPA usually operates on predefined rules, it can be extended with technologies like machine learning and artificial intelligence (AI) to boost its ability to automate more complex tasks. This combination, often called intelligent process automation (IPA), can enable some software solutions to learn from past interactions to improve accuracy and efficiency over time.

What are the 3 types of robotic processing automation?

When implementing RPA, there are three main types of automation to choose from:

Feature	Attended automation	Unattended automation	Hybrid automation
Trigger	Initiated by a human employee on demand.	Runs automatically based on a schedule or system trigger.	Can be triggered by either a human or a system.
Interaction	Works alongside a person as a "digital assistant" to keep a human-in-the-loop.	Works independently in the background; no human intervention needed.	Switches between independent and attended tasks as needed.
Best for	Customer service, help desks, tasks requiring human oversight.	High-volume, back-office processes like batch data processing, report generation.	End-to-end processes that require both automated steps and human judgment.
Example	A call center agent clicks a button to have a bot retrieve a customer's full history from three different systems.	A bot runs every night at 2 AM to process all of the previous day's online orders and generate a sales report.	A bot processes a loan application, but flags it for a loan officer to make the final approval decision.

Feature

Attended automation

Unattended automation

Hybrid automation

Trigger

Initiated by a human employee on demand.

Runs automatically based on a schedule or system trigger.

Can be triggered by either a human or a system.

Interaction

Works alongside a person as a "digital assistant" to keep a human-in-the-loop.

Works independently in the background; no human intervention needed.

Switches between independent and attended tasks as needed.

Best for

Customer service, help desks, tasks requiring human oversight.

High-volume, back-office processes like batch data processing, report generation.

End-to-end processes that require both automated steps and human judgment.

Example

A call center agent clicks a button to have a bot retrieve a customer's full history from three different systems.

A bot runs every night at 2 AM to process all of the previous day's online orders and generate a sales report.

A bot processes a loan application, but flags it for a loan officer to make the final approval decision.

What is the difference between RPA and artificial intelligence?

While the two terms are sometimes confused, RPA and AI are distinct concepts. Although RPA can leverage AI technologies, the core focus of each differs significantly.

Robotic process automation primarily focuses on automating rule-based tasks and processes that use structured data, whereas AI is centered on enabling systems to learn and make decisions without human intervention, including processing unstructured data like text and images.

RPA proves most effective for automating tasks that are repetitive and predictable, while AI is often better suited for tasks that are complex and require a certain level of understanding and decision-making. For instance, RPA could be used to automate the process of creating invoices, while AI could be used to develop a chatbot that can interact with customers and answer their questions.

RPA bots versus AI agents

While it’s helpful to know the general differences between RPA and AI, it can also be useful to consider the distinction between an RPA bot and an "AI agent." An AI agent can be thought of as a more advanced entity that not only processes information but also is aware of its environment, makes autonomous decisions, and learns from its interactions to achieve specific goals.

Here’s a breakdown of their differing characteristics:

Characteristic	RPA bots	AI agents
Nature of operation	Programmed to execute predefined steps; follows explicit instructions; requires reprogramming for changes.	Simulate human cognitive functions; analyze data, identify patterns, and make autonomous decisions; adapt based on new information.
Intelligence and learning	Lack inherent intelligence; operate based on given rules; do not evolve independently.	Often incorporate ML and other AI techniques; learn from data; improve performance over time; adapt to changing circumstances.
Decision-making	Based on deterministic, predefined rules (if X, then do Y).	Can make more complex, probabilistic decisions in ambiguous situations by inferring, predicting, and evaluating options.
Data handling	Primarily work with structured data (spreadsheets, databases).	Can process structured and unstructured data (text, emails, images, voice) using NLP and computer vision.
Analogy	A digital assistant following a checklist or script; the "arms and legs" for executing tasks.	A "digital brain" or cognitive partner that can understand context, make judgments, and learn.

Characteristic

RPA bots

AI agents

Nature of operation

Programmed to execute predefined steps; follows explicit instructions; requires reprogramming for changes.

Simulate human cognitive functions; analyze data, identify patterns, and make autonomous decisions; adapt based on new information.

Intelligence and learning

Lack inherent intelligence; operate based on given rules; do not evolve independently.

Often incorporate ML and other AI techniques; learn from data; improve performance over time; adapt to changing circumstances.

Decision-making

Based on deterministic, predefined rules (if X, then do Y).

Can make more complex, probabilistic decisions in ambiguous situations by inferring, predicting, and evaluating options.

Data handling

Primarily work with structured data (spreadsheets, databases).

Can process structured and unstructured data (text, emails, images, voice) using NLP and computer vision.

Analogy

A digital assistant following a checklist or script; the "arms and legs" for executing tasks.

A "digital brain" or cognitive partner that can understand context, make judgments, and learn.

Essentially, RPA bots can be useful for automating well-defined, repetitive processes, while AI agents may be better suited for the automation of more complex, dynamic, and judgment-based tasks. The trend is towards combining these capabilities in "Intelligent Automation," where RPA handles the execution and AI provides the cognitive power.

Benefits of using robotic process automation

Businesses that adopt RPA solutions may experience a wide range of benefits. Some of the most notable potential advantages include:

Increased efficiency

By automating repetitive tasks, RPA may significantly improve operational efficiency. This can free up employees to focus on more strategic and complex tasks that require thoughtful human input.

Improved accuracy

Bots are typically less prone to errors than humans, so they can help improve the accuracy of data entry and other tasks.

Enhanced compliance

RPA can help businesses improve compliance by automating tasks related to regulatory requirements. For example, a bot could be used to ensure that all invoices are properly processed on time and that all required information is included.

Scalability

Businesses can leverage RPA to scale their operations more easily. Bots can be easily replicated and deployed across different systems, making it easier to expand operations without increasing employee headcount.

Better employee satisfaction

RPA can help foster a more positive work environment. By freeing up workers to focus on more challenging and rewarding tasks, it can help reduce employee boredom and frustration, improve morale, and help employees do more of the work they want to do.

Faster ROI

RPA frequently delivers a rapid return on investment (ROI). Many RPA projects can be implemented relatively quickly and can start generating benefits within a short period. Automating the more tedious tasks currently performed by human workers could also lead to significant cost savings over time.

What are the challenges of robotic processing automation?

Despite the many benefits of RPA, businesses should be aware of potential challenges associated with its implementation. These can include:

Integration with existing systems: Integrating RPA with existing systems may sometimes be difficult, especially if the systems are not designed to work with automation
Security concerns: Having strong security measures set up is critical, as RPA systems may be vulnerable to security threats
Maintenance and updates: RPA systems require ongoing maintenance and updates, which can be time-consuming and complex
Change management: Implementing RPA can require significant changes to business processes, which can be challenging to manage

How does Google Cloud support robotic process automation?

While Google Cloud provides powerful building blocks for creating modern, intelligent automation solutions that go beyond traditional RPA, it does not offer a standalone, low-code RPA tool. Instead, it allows you to build more powerful and scalable automations by combining serverless execution with world-class AI.

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