RPA and AI: The Ultimate Combo

AI is a hot topic these days and seems to be taking the world by storm. The question it raises is: what if computers could take over as humans and not just work as well as us, but even better? What if computers could make decisions for us, solve problems, converse intelligently, draft online, generate images, and more?

And then there’s the question: how can we use AI to make our daily tasks less tedious and more successful at work?

We tend to think of Robotic Process Automation (RPA) and Artificial Intelligence (AI) as separate entities, but in the ever-evolving world of automation technology, that’s no longer the case. AI is now changing RPA for the better.

While RPA is growing beyond market expectations, AI continues to create even more value: Forrester predicts that by 2023 , 10% of Fortune 500 companies will use AI tools to generate content.

AI is a cognitive technology that perceives and learns, with limitless possibilities ranging from cognitive algorithms to AI-powered industry innovations, while Intelligent Automation (IA) is the integration of AI, Machine Learning (ML), Robotic Process Automation and other technologies to scale automation end-to-end with a digital workforce.

While RPA and AI each have their own benefits, they need to be combined to best optimize business processes. The result of this combination is intelligent automation. RPA focuses on rule-based automation of repetitive and other tasks. AI, on the other hand, uses computer systems to simulate human intelligence, so when the two work together, the possibilities are enormous.

What distinguishes robotic process automation (RPA) from artificial intelligence (AI)?

Robotic Process Automation (RPA) uses software robots that mimic human actions to automate repetitive business processes, improving engagement and morale by freeing employees from mundane, routine tasks and allowing them to focus on more meaningful cognitive work. RPA robots follow the instructions programmed into them to perform the automated tasks efficiently and without error.

Artificial Intelligence (AI) is capable of cognitive learning and reasoning, and can also identify errors and correct them efficiently. AI technologies include a wide range of applications such as Machine Learning (ML), Intelligent Document Processing (IDP) , Optical Character Recognition (OCR), Natural Speech, Speech Recognition, and Natural Language Processing (NLP).

When you deploy AI-powered RPA robots, you get intelligent digital workers that follow contextual rules to execute tasks and learn as they go. Digital workers can execute tasks with different levels of automation: they can operate independently as “unattended” automation , or they can work in collaboration with humans as “attended” automation.

Digital Workers perform tasks around the clock to improve employee workflows, reduce errors, increase productivity, and deliver faster service for satisfied customers.

There are four main areas where artificial intelligence and robotic process automation are rapidly evolving: chatbots, unstructured content, IoT sensors, and analytics . When it comes to making robots more intelligent, the ability to extract better insights from unstructured data is gaining traction.

Combining RPA and AI creates the ultimate team called the Digital Workforce.

Why Unstructured Data is So Important for Intelligent Process Automation

Unstructured data creates a unique opportunity for automation. Many companies have tens or even hundreds of terabytes of unstructured data in their data sets. So it’s no surprise that organizations are looking for proven solutions that can help them better leverage unstructured data to unlock the full potential of intelligent robotic process automation.

Analytics will continue to be a focus for closing process gaps, with nearly half of organizations looking to use AI and automation software to create a new digital workforce.

Using Unstructured Data in RPA Processes

For example, the availability of unstructured data while building an RPA process is important in the following scenarios:

When you need to categorize documents according to a particular customer’s taxonomy and then act on each category accordingly
To understand whether the content of a document is relevant
When inferences need to be applied to information before it can be extracted
You need to also discover relationships attached to the data you are extracting and apply those relationships in your process.

In the above scenario, expanding the scope of AI and RPA integration to facilitate the use of unstructured data will broaden the scope of intelligent automation.

AI rapidly transforms all relevant data into useful and actionable data for RPA. AI analyzes, classifies, extracts and organizes relevant information contained in unstructured data (e.g. text fields in various business rules, documents, purchase orders, invoices, emails, survey reports, forms etc.) into clean files that can be used by Robotic Process Automation.

How AI and RPA work together

RPA and AI working together delivers intelligent process automation, or Intelligent Automation (IA), which not only combines the two but also machine learning and other AI-based automation to optimize workflows, streamline processes, and enable an all-around digital transformation in your organization.

Intelligent automation software transforms RPA robots into a digital workforce powered by cognitive automation to handle more complex tasks.

RPA and Machine Learning

AI-powered RPA robots will be able to take on current capabilities and make decisions, and with the introduction of machine learning (ML), the bots will be able to solve problems and make suggestions for improvement.

Machine learning is a branch of AI that uses data and algorithms to mimic human learning and gets better as it learns. Machine learning models allow these AI-powered software robots to make predictions and forecast outcomes.

AI and RPA working together

AI is the perfect partner for RPA to analyze, classify and extract unstructured data, and the combination of RPA and AI can improve outcomes for even the most complex and mission-critical intelligent RPA workflows.

At the same time, RPA is an ideal complementary technology, enabling effective automation with cognitive capabilities at scale.

This means that by automating processes end-to-end using an all-in-one platform, organizations can derive the automation benefits from both technologies and easily leverage the value of their intelligence capabilities.

Integrating Expert AI’s artificial intelligence capabilities into SS&C Blue Prism’s Robotic Process Automation platform improves worker efficiency and productivity while providing greater accuracy when using unstructured data, automating tasks once handled exclusively by humans and expanding business automation into new strategic areas.

RPA and AI Use Cases

There are countless examples of how AI is enhancing the capabilities of RPA bots, but here we will focus on just a few:

Email Management: Robots scan email streams for urgency, issues, and purpose, and extract key information to improve response times and keep topics organized.

Invoice processing: Using AI-powered robots in payment processing systems can drastically reduce invoice processing times and dramatically improve accuracy.
Financial Transactions: PRA can work with AI to ensure security and accuracy in financial transactions by collecting data on each user from various sources and scanning for anomalous activity that may be fraudulent. Machine learning predictive analytics can be used to spot risk in future transactions based on previous experience.
Communication Experience: Using bots to scan employee and customer experiences helps identify areas for improvement and issues so they can be fixed quickly, while also ensuring nothing falls through the cracks – a win-win for both employees and customers.

What are the benefits of RPA and AI?

Now that we’ve covered what RPA and AI are and how they can effectively work together, there’s one more topic left to cover in this blog post: benefits. Digital Workers have the potential to transform your automation efforts from “good enough” to “excellent.”

There are countless benefits to be gained by linking RPA and AI, but here we will briefly explain the four main benefits.

Increased employee satisfaction : Employees are freed from mundane tasks and can focus on projects that add greater value.
Efficiency : Streamlined processes reduce time to results.
Accuracy : Automating processes reduces human error, leading to greater efficiency.
Consistency and Compliance : With fewer errors and rules-based operations, your Digital Workers leave clear audit trails to ensure compliance requirements are always met.