How RPA and AI Work Together in Intelligent Automation

RPA uses software robots to automate processes, mimicking human actions to offload dull, manual processes from human employees. It’s business rule-based execution that uses structured data to enact user interface (UI) automation. For example, RPA automates time-consuming data entry and data transfer tasks. That in turn boosts employee engagement and morale, allowing them to focus on more interesting, strategic work. RPA runs automated tasks efficiently and without error, acting under the instructions for which they’re programmed. It’s predictable and repeatable.

AI is capable of cognitive learning, reasoning and identifying patterns and errors for correction and can interact with unstructured data. There’s an expanse of applications within AI technologies including gen AI, machine learning (ML), intelligent document processing (IDP), optical character recognition (OCR), natural speech, computer vision, predictive analytics, speech recognition and natural language processing (NLP). AI, however, doesn’t execute workflows by itself.

By introducing AI-enabled RPA robots, you get intelligent digital workers following contextual rules and learning as they go to complete more complex tasks. These digital workers can perform on different levels of automation: independently as ”unattended” automation or with your people as “attended” automation. We call this AI-powered RPA “intelligent automation” because it fuses AI orchestration, decision engines, machine learning models and end-to-end business automation in one place. Think of it like this: RPA is the “doer” while AI is the “thinker”.

Digital workers perform without breaks to improve employee workflows, reduce errors, increase productivity and achieve customer satisfaction by providing quicker service. And now AI, you can think of having RPA and AI workers working together as an AI workforce.

In the four primary areas where artificial intelligence and robotic process automation are quickly progressing – RPA chatbots, unstructured content, IoT sensors and analytics – the ability to capture greater insight from unstructured data is center stage in making robots more intelligent.

Together, RPA and AI are the ultimate team-up to bring you a future-ready intelligent automation AI workplace.

Combining traditional RPA with AI unlocks greater business benefits and can lead to greater success. Often, we think of robotic process automation (RPA) and artificial intelligence (AI) as separate entities. But with the ever-evolving world of automation and AI technology, that’s no longer the case. You need both.

AI is changing RPA for the better, putting more intelligence in processes across businesses with help from AI agents.

When talking about AI and RPA, most benefits cite how RPA is improved. But it’s not all about how RPA is better with AI; it goes both ways. RPA improves AI, too, in ways you might not realize. Here’s how:

• Helps AI with data: RPA digital workers can gather, clean and label data to help AI make decisions in the right context.
• Connecting systems: RPA helps bridge the gap between systems, where newer AI tools might lack the ability to.
• Provide some explainability: You might have heard “AI is a black box”, RPA helps provide some accountability by ensuring steps are followed systematically.
• Opportunity for human-in-the-loop: RPA robots can be a kind of safety net when AI makes decisions. For example, if gen AI creates text for an important record, an RPA bot can redirect it for a human to review.
• Monitors performance: RPA can track AI system performance, watching for errors and flagging issues that need review.

Organizations are using AI and RPA together to enable end-to-end intelligent automation. Let’s look at what SS&C Blue Prism customers are doing today with the combination.

As one of the largest financial institutions in Denmark, Danica Pension is determined to provide outstanding customer service. They wanted to give their customers swift responses to their inquiries.

Danica Pension brought in a team of 129 digital workers to assist their employees in completing back-office and frontline work. Alongside that, they infused their digital workers with AI to improve their anti-money laundering (AML) and due diligence efforts, ensuring their customers’ transactions are always secure.

Sandie Lindblad, first vice president of operational excellence at Danica Pension says, “The next step with AI and intelligent automation is to make our digital customer engagement more personal than we’ve been able to make it before.”The Spanish retail bank ABANCA delivers personalized service to millions of customers, and they’ve invested significantly in digital banking services for their customers. Now, they’re taking their digital transformation efforts further with SS&C Blue Prism IA, generative AI and NLP. They’ve increased their customer response times by 60% and have automated more than a thousand tasks, improving operational efficiency and employee productivity. Digital workers have delivered 1.2 million hours back to the business so far.

The future of AI in business continues growing as tools like generative AI are absorbed into more processes. And with AI developments like agentic AI and autonomous agents evolving, organizations need to start their AI journeys on the right foot with human-in-the-loop systems and guardrails.

The best way to get the most out of your AI and RPA solutions is to use a unified enterprise solution, where you can orchestrate your people with your digital workers, system