Discover three market trends in automation that are revolutionizing the industry. Dive into the future of automation in this insightful blog post.
Intelligent Automation vs. RPA: Unpacking the Differences
Intelligent Automation vs. RPA: Learn the key differences between these two automation technologies and how they can benefit your business.
Intelligent Automation vs. RPA: Definition, Differences and Uses
What is Intelligent Automation and How Does It Work?
The Components and Technologies of Intelligent Automation
- Artificial Intelligence:
This is the broadest tool we will describe, as AI has many meanings and applications. We will focus on how AI applies machine learning and complex algorithms to analyze structured data through predictive AI and unstructured data through generative AI.
Predictive AI analyzes historical data to make predictions about future trends and activities. Generative AI identifies patterns in a dataset and then makes new versions of the data that should be indistinguishable from the real inputs. Common examples of this are AI images and AI voices. Generative AI allows businesses to automate content production for marketing content efficiently.
- Optical Character Recognition: Optical character recognition (OCR) identifies words and characters in images and converts them to text. This is useful for businesses that need to reorganize data. You may have information in a PDF or screenshot format that you want to be able to manipulate. OCR will pull the text into a document or spreadsheet, allowing you to edit and analyze the information.
- Computer Vision: This allows the automation of picking out objects in images or videos. This allows machines to interpret and understand the world around them. The information can be saved and analyzed later or used in real time in situations that require a quick response.
Natural Language Processing: Natural language processing (NLP) allows machines to understand human speech or text and respond in a human-like manner. NLP can be applied to chatbots or voice assistants to improve the customer experience. These features are always available, and you never have to wait for human workers to become available.
Real-World Use Cases and Benefits of Intelligent Automation
What is Robotic Process Automation and How Does it Work?
The Core Principles and Components of RPA
- Recorder: The recorder captures the steps performed by a human so that they can be replicated by the bot later. When recording the steps, follow the ‘Don’t Repeat Yourself (DRY) Principle.’ The DRY principle is part of software development to ensure that each piece of logic has an unambiguous representation within the system. Ensuring tasks are not repeated in a process helps avoid errors and bugs.
- Development Studio: The development studio is a core feature of RPA for designing and developing your intelligent workflow automation. It is recommended to take a modular approach when designing your workflow automation. This makes finding errors easy because you can quickly test each step one by one to locate any problems.
Bot Runner: The bot runner instructs the bot to start performing the task. When you activate the bot, check closely that it is performing the task thoroughly and correctly using actual data. There may be edge cases that pop up on which you have not trained the bot yet. You may need to update or retrain the bot if there are any issues at this stage.
Control Center: The control center is used to monitor and manage RPA workflows. You can set up a specific time or schedule from the control center for the bot to execute the task. This is also where you can scale up the activities of the bot if your requirements or requests change.