What is robotic process automation (RPA)? What does artificial intelligence (AI) have to do with it? If you're interested in joining the world of robotics, understanding these technologies can help get you started.
At Universal Technical Institute (UTI), we offer Robotics & Automation programs that dive into the fundamentals of robotics!1 With courses like Industrial Networking and Computer Aided Design, students can grow their robotics and automation skills!
In this blog, we'll break down what RPA and AI are, their differences and why they are an important part of robotics automation!
What is RPA?
RPA, or Robotic Process Automation, is a form of software technology that uses bots or "digital workers" to automate repetitive, rule-based tasks traditionally performed by humans. These tasks can include things like data entry, invoice processing and system updates. RPA tools interact with digital systems the same way a human would by clicking, typing and navigating through software, without changing the underlying systems.
RPA helps businesses increase efficiency, reduce human error and free up employees to focus on more strategic or creative work. It's commonly used in industries like finance, healthcare, manufacturing and logistics to streamline operations and improve productivity.
What is AI?
AI, or Artificial Intelligence, is the field of computer science focused on creating systems that can perform tasks that typically require human intelligence. This includes capabilities like learning from data, recognizing patterns, understanding language, making decisions and solving problems.
AI comes in many forms, from simple chatbots and recommendation engines to advanced systems like machine learning algorithms and neural networks. It's used across industries to enhance automation, improve customer experience, drive innovation and enable smarter decision-making. Unlike RPA, which follows predefined rules, AI can analyze data, adapt over time and make informed predictions or decisions.
Key Differences Between RPA vs. AI
Task type
RPA is designed for structured, rule-based tasks that follow a clear sequence, like copying data between systems or processing transactions. It excels at repetitive, high-volume workflows.
AI, on the other hand, handles more complex tasks that require interpretation, analysis or problem-solving, like understanding natural language or recognizing images.
Data type
RPA works best with structured data, organized information such as spreadsheets, databases and digital forms.
AI can handle both structured and unstructured data, including text, audio, images and video, making it suitable for tasks that require data analysis and interpretation.
Decision-making ability
RPA follows predefined rules and cannot make decisions beyond its programming. It does what it's told without deviation.
AI can make data-driven decisions. It can analyze patterns, learn from past behavior and even adjust its responses based on new information.
Learning capability
RPA does not learn or improve over time. It performs tasks the same way unless manually updated.
AI systems can learn and evolve using techniques like machine learning. As they process more data, they become more accurate and efficient at performing tasks.
Use cases
Common RPA use cases include invoice processing, data entry, payroll management and report generation tasks that are repetitive and rule based.
AI is used for fraud detection, customer service chatbots, predictive maintenance, image recognition and language translation tasks that benefit from reasoning and analysis.
Is RPA a Form of AI?
A common question is whether RPA is a form of AI. The short answer is no, RPA is not a form of AI, but they can complement each other.
RPA is rule-based and doesn't involve learning or adaptation. It follows pre-defined instructions and doesn't change its behavior unless programmed to do so. AI, however, involves learning and adapting, making it more flexible and capable of handling complex tasks.
While RPA and AI are different, combining them can create powerful automation solutions.
How RPA and AI Work Together
When RPA and AI work together, they create automation solutions that can change the way business processes function. This combination pulls in the strengths of both technologies. It makes automation more efficient and capable.
For example, AI can handle unstructured data and make decisions, while RPA can execute a solution based on those decisions.
In a financial services company, AI can analyze customer data to detect fraudulent transactions. Once identified, RPA can automatically flag these transactions for review or even reverse them, depending on the set rules. This reduces the risk of fraud and improves operational efficiency.
How To Combine RPA and AI
Combining RPA and AI requires a strategic approach. First, identify the processes that can benefit from automation. Look for tasks that are repetitive, rule-based and involve structured data for RPA. Tasks that need decision-making, analysis of unstructured data or prediction capabilities are ideal for AI.
Next, integrate RPA and AI solutions to create a seamless workflow. For instance, use AI to analyze customer feedback and generate insights. Then, use RPA to automate the implementation of these insights. This could look like updating customer profiles or sending personalized offers.
The key is to make sure that the technologies complement each other.
Common Applications of RPA and AI
RPA and AI have uses across various industries. Some of them include:
Customer Service: In customer service, RPA can handle routine queries, while AI analyzes customer sentiment and provides personalized responses. This improves customer satisfaction and reduces response times.
Human Resources: RPA can automate HR tasks like payroll processing and employee onboarding. AI can analyze employee performance data to identify areas they can improve and recommend training programs.
Data Analysis: AI excels at analyzing large datasets to uncover patterns and trends. Combining this with RPA allows businesses to automate data collection and reporting. This can provide real-time insights for important decisions.
Supply Chain Management: RPA can automate inventory management, order processing and shipping. AI will predict demand and optimize supply chain operations to help reduce costs and improve efficiency.
Marketing: AI can analyze customer behavior to create targeted marketing campaigns. RPA automates the execution of these campaigns. That can include sending emails or updating customer databases.
Learn How To Use RPA and AI in UTI’s Robotics & Automation Program
RPA and AI are transforming industries and creating exciting opportunities for those interested in robotics and automation. Learn more about UTI’s Robotics & Automation Technician program options that can help you gain the skills and knowledge to pursue an entry-level position in robotics!1
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