From RPA to Agentic AI: How SS&C Blue Prism Is Guiding Enterprises Through the Next Automation Frontier

The robotic process automation (RPA) landscape is undergoing a seismic shift as organizations grapple with the limitations of traditional rule-based systems in handling today’s complex, unstructured workflows. For companies still anchored in the structured world of RPA, the emergence of agentic AI represents both an exciting opportunity and a potential source of anxiety. SS&C Blue Prism is positioning itself as the trusted guide for this transformative journey, helping enterprises navigate the transition from deterministic automation to intelligent, adaptive systems that can reason and make decisions in real-time.

The Complexity Problem: Why Traditional RPA Is Reaching Its Limits

Steven Colquitt, Vice President of Software Engineering at SS&C Blue Prism, articulates the fundamental challenge facing modern enterprises: “Modern workflows have reached a level of complexity that traditional RPA was simply not designed to handle.” The crux of the issue lies in the nature of contemporary business processes, which increasingly involve unstructured data flowing from multiple sources and mimicking non-deterministic real-world interactions.

Inputs can vary dramatically, outcomes shift based on context, and decisions must be made in real-time with incomplete information. This represents a quantum leap from the predictable, structured environments where RPA excels. Where traditional automation follows predefined rules and linear workflows, today’s business challenges demand systems that can adapt, reason, and learn from experience.

The Evolution from Data Points to Answers

Brian Halpin, Managing Director of Automation at SS&C Blue Prism, provides a concrete example that illustrates this evolution. Consider the task of analyzing a credit agreement—a process that might require extracting 30 or 40 distinct pieces of information. But Halpin deliberately uses the term “answers” rather than “data points,” emphasizing the sophisticated reasoning that large language models (LLMs) bring to bear on such tasks.

This distinction is crucial. Traditional RPA might extract specific fields from a structured document, but agentic AI can understand context, interpret ambiguous information, and provide nuanced responses that reflect genuine comprehension rather than simple pattern matching. The system isn’t just retrieving data; it’s reasoning about what the data means and what actions should be taken as a result.

The Journey Metaphor: From Instructions to Outcomes

The transition to agentic automation represents a fundamental shift in how we think about automation itself. Halpin explains: “We’re now saying we’re giving an AI agent the outcome that we want, but we’re not giving it the instructions on how to complete.” This marks a departure from the traditional automation paradigm where every step is explicitly defined.

Instead of saying, “Follow step one, two, three, four, five,” organizations are beginning to say, “I want this loan reviewed” or “I want this customer onboarded.” The AI agent is entrusted with determining the optimal path to achieve the desired outcome, drawing on its training, reasoning capabilities, and access to relevant information sources.

However, Halpin acknowledges that the industry isn’t quite ready for fully autonomous agentic workflows. “Is it ready for that? No. Why? Because there’s trust, there’s regulations, there’s auditability, stability, security.” These concerns are well-founded—LLMs are known to hallucinate, drift over time, and produce different responses when underlying models change. The path forward requires careful navigation of these challenges while building the necessary trust and governance frameworks.

The Reality of Enterprise Adoption

Despite the transformative potential of agentic AI, Halpin emphasizes that this represents a journey rather than an overnight revolution. “There’s an awful lot of learning to happen before I think companies go fully autonomous and real agentic workflows driven from that sort of non-deterministic perspective.”

This measured approach reflects the reality of enterprise technology adoption, where concerns about reliability, compliance, and risk management often temper enthusiasm for cutting-edge capabilities. Organizations must balance the desire for innovation with the need for stability and predictability in their operations.

Bridging Organizational Silos

One of the most interesting observations from Halpin’s discussions with customers is the prevalence of organizational silos between AI and automation teams. “In a lot of cases, AI has been established as a separate unit in a company. You go over to the process automation team, and they’re maybe not even allowed to use the AI.”

This separation represents a significant missed opportunity. By bringing these capabilities together, organizations can achieve the next 20-30% of automation in terms of end-to-end process coverage. The integration of AI reasoning with process automation creates synergies that neither technology can achieve independently.

SS&C Blue Prism’s Internal Journey as Proof of Concept

SS&C Blue Prism isn’t just selling a vision—they’re living it. As part of SS&C Technologies, one of the world’s largest users of RPA, the company has deployed over 3,500 digital workers across its operations, generating hundreds of millions in run-rate benefits. More importantly, they’ve already implemented approximately 35 AI agents in production, working alongside these digital workers to handle complex tasks.

This internal deployment serves as both a proof of concept and a learning laboratory. By experiencing the challenges and opportunities of agentic automation firsthand, SS&C Blue Prism is better positioned to guide its customers through similar transformations. The company’s journey provides valuable insights into what works, what doesn’t, and how to overcome common obstacles.

The Technology Roadmap: New Capabilities on the Horizon

SS&C Blue Prism is preparing to launch new technology that will help organizations build and embed AI agents within their existing workflows while providing orchestration capabilities. This technology aims to make the transition to agentic automation more accessible by providing the tools and frameworks necessary to integrate AI reasoning into established processes.

The upcoming launch, previewed at TechEx Global as part of the Intelligent Automation conference, represents a significant milestone in making agentic automation practical for mainstream enterprise adoption. By providing the scaffolding that organizations need to experiment with and deploy AI agents safely, SS&C Blue Prism is lowering the barriers to entry for this transformative technology.

The Broader Context: AI as the Next Industrial Revolution

The transition from RPA to agentic AI represents more than just an incremental improvement in automation technology—it signals the beginning of what many consider the next industrial revolution. Just as the first industrial revolution moved manufacturing from hand production to machines, and the digital revolution brought computation to every aspect of business, the agentic AI revolution promises to transform how work gets done by introducing intelligent, adaptive systems that can handle complexity and ambiguity.

Organizations that successfully navigate this transition will gain significant competitive advantages through increased efficiency, improved accuracy, and the ability to handle increasingly complex processes. Those that lag behind risk being left behind as their competitors leverage these new capabilities to operate more effectively and respond more quickly to market changes.

Looking Forward: The Continuous Evolution of Automation

Halpin’s observation that “there will be something else, right? There will be another model” captures an essential truth about technological progress. The journey from RPA to agentic AI is not an endpoint but a waypoint in the ongoing evolution of automation technology. Each advancement builds upon previous capabilities while opening new possibilities for the future.

This continuous evolution requires organizations to maintain flexibility and adaptability in their technology strategies. The ability to evolve and incorporate new capabilities as they emerge will be a crucial competitive advantage in the coming years. Companies that can successfully navigate these transitions while maintaining operational stability will be best positioned to thrive in an increasingly automated and intelligent business environment.

The transformation from rule-based RPA to agentic AI represents one of the most significant shifts in enterprise technology in recent years. With companies like SS&C Blue Prism providing guidance and tools for this journey, organizations have the support they need to make this transition successfully. The future of automation is intelligent, adaptive, and increasingly autonomous—and that future is arriving faster than many anticipated.

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