Many organizations still rely heavily on robotic process automation (RPA) to handle routine tasks. But as workflows grow more complex, there’s a push to move beyond traditional RPA into more advanced, intelligent automation. SS&C Blue Prism is guiding its customers through this transition, helping them adopt what’s called agentic AI at a pace they’re comfortable with. This shift is big but necessary, as modern business processes often involve unstructured data and real-time decision making that traditional RPA can’t handle easily.

The Limitations of Traditional RPA

According to Steven Colquitt, VP of Software Engineering at SS&C Blue Prism, traditional RPA was built to automate predictable, rule-based tasks. However, today’s workflows are far more complex. They involve unstructured data from many sources, resembling real-world interactions that don’t follow a fixed pattern. Inputs can change, outcomes can vary, and decisions often depend on context in the moment. These factors make it clear that RPA alone isn’t enough anymore.

As tasks become more nuanced, organizations need automation that can understand and adapt to this complexity. That’s where AI, especially large language models (LLMs), comes into play. But integrating AI into automation isn’t just about replacing rules with smarter algorithms; it’s about enabling machines to reason and make decisions based on context.

The Journey Toward Agentic Automation

Brian Halpin, Managing Director of Automation at SS&C Blue Prism, describes this evolution as a journey. Instead of giving AI explicit step-by-step instructions, companies are starting to specify the outcomes they want—like reviewing a loan or onboarding a customer—and letting the AI figure out how to achieve them. It’s a shift from prescriptive automation to outcome-driven AI agents.

Halpin notes that this approach isn’t fully ready for widespread adoption yet. Concerns around trust, regulations, auditability, stability, and security still need to be addressed. Large language models can hallucinate or produce inconsistent responses, especially if the underlying models change. Companies must proceed carefully, understanding that true agentic workflows driven by non-deterministic AI are still a work in progress.

He emphasizes that this is a continual journey. New models and technologies are constantly emerging, which means organizations will keep evolving their automation strategies over time. The goal is to gradually build more autonomous, intelligent systems that can handle complex tasks with minimal human intervention.

Connecting AI and Automation in Practice

Many of SS&C Blue Prism’s customers already have extensive automation setups, from centers of excellence to digital workers in daily operations. Their challenge now is to upgrade those systems with AI capabilities. Halpin observes that often AI is treated as a separate unit within a company, making integration difficult. Automation teams may not even be allowed to use AI tools directly, which slows progress.

The key is to find ways to blend AI into existing automation workflows. This means enabling process teams to leverage AI’s power without disrupting their current operations. By doing so, organizations can unlock additional efficiencies—sometimes 20% or more—by automating more complex, end-to-end processes. SS&C Blue Prism is developing new technology to help organizations embed AI agents directly into their workflows, making automation smarter and more adaptable.

Overall, the move from traditional RPA to agentic automation is a gradual but essential evolution. It involves learning, experimentation, and careful management of risks. But it promises a future where automation is more intelligent, flexible, and capable of handling the unpredictable nature of real-world business processes.

Inspired by

• https://www.artificialintelligence-news.com/news/ssc-blue-prism-on-the-journey-from-rpa-to-agentic-automation/

Sources

• blueprism.com
• intelligentautomation-conference.com