AI or RPA. How do AI and RPA work together?

RPA (Robotic Process Automation) and AI (Artificial Intelligence) are two distinct but overlapping areas of technology. We’ve often found that the clear demarcation between the two isn’t commonly understood, leading to the question, “Is RPA AI?” To be clear, RPA is not AI, but it can be used to help AI perform simple tasks. With RPA solutions continuously becoming more featurized, it can begin to look similar to technologies such as AI. And so it’s worth pausing to understand them individually, what each of these technologies can help a business accomplish and how they can work together to maximize performance.

RPA vs. AI – Where is the distinction?

Both artificial intelligence (AI) and robotic process automation (RPA) are technologies that can perform tasks. The distinction becomes clear when we think of one as the body and the other as the brain.

Robotic process automation (RPA) can be understood as a body that is efficient at executing functions. RPA, or robotic process automation, is software that performs rule-based tasks by mimicking human action. You can streamline and accelerate business processes by automating structured tasks. Designed for repetitive, continuous, and well-defined processes, RPA requires structured data that is well defined and must be trained to execute a procedure. By itself, RPA is ‘built to execute’ and can handle time-consuming tasks like logging into applications, moving files, copying data, connecting to APIs, and opening email and attachments.

Artificial intelligence (AI) can be understood as the human brain that can think and perform actions through cognition. AI automation can receive both structured and unstructured data, process it, and carry out tasks that are not exclusively rule-based. Through techniques like Natural Language Processing (NLP) and Machine Learning algorithms, the AI can train itself to recognize incoming data and respond immediately based on what needs to be done. As a result, AI can complete tasks such as understanding documents, visualizing screens, understanding conversations, processing language, and even discovering processes to automate. Furthermore, with the ability to take in large unstructured data sets and predict several outcomes, AI can easily handle complex processes that humans previously did alone.

Choosing your automation tech – RPA or AI?

When our clients are trying to determine whether RPA or AI should handle an operation, this is what we suggest – Start by automating with RPA, quickly and mentally mapping out the process, and when RPA alone is found to be insufficient for a given workflow, introduce AI. This provides a twin with an advantage:

  • first, you get quick wins for your automation initiatives

  • and second, RPA lays the foundation on which a robust AI implementation can occur

With the first layer of simple processes automated, it is then time to look for workflows that are ‘too complex’ for RPA alone:

  • processes where outcomes can’t be predicted with 100% accuracy, such as loan defaults, inventory forecasts, tax deduction calculations

  • processes where outcomes can’t be predicted with 100% accuracy, such as loan defaults, inventory forecasts, tax deduction calculations

  • processes that rely on unstructured data from documents, articles, images, videos, and emails, such as invoice extraction, email routing, and speech-to-text

Intelligent Automation – RPA and AI working together

There’s a ceiling on how efficient you can be when limiting yourself to only flowchart-friendly processes. That is why AI is the perfect companion to RPA. AI is the process of simulating human intelligence in machines, while RPA automates processes that use structured data and logic. Together, AI + RPA provides more accurate and efficient automation powered by an informed knowledge base. And this is what the industry knows as intelligent automation (IA).

Intelligent automation is an end-to-end automation solution that combines AI and automation technologies like RPA. It adds capabilities to process automation only possible through bots that can learn and adapt to data in real-time. In addition, it simplifies processes, helping users to be the outcome or goal-oriented rather than process-oriented.

Industries and businesses are continuously finding uses for intelligent automation (IA) tech that are unique. Some of the more common ones are:

  • Intelligent document processing (IDP): Business data can appear in an unstructured format across images, emails, and files. Intelligent automation (IA) tools like RPA, machine learning, and natural language processing (NLP) extract, validate and process that data.

  • Process discovery: Intelligent automation (IA) can help create a complete guide for automating a process using RPA.

  • Streamlining workflows: Intelligent automation (IA) can use data to automate workflows for faster, more efficient processes.

  • Managing production and supply-chain: Intelligent automation (IA) can be used to predict and adjust production to respond to changes in supply and demand.

Process automation creates tremendous value through faster, more accurate solutions and contributes to productivity. And clearly, understanding the capabilities of RPA, AI, and IA is significant to planning your automation journey. Whether you want to automate operations that span your entire organization or are looking to automate repetitive tasks, get in touch with us. Our experts can help you build the complete blueprint for your automation roll-out.

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