Is This the End of RPA as We Know It?
The automation landscape is shifting rapidly. Automation leaders are now faced with a dilemma – Should they continue investing in RPA, building on existing infrastructure and expertise? Or should they shift focus to emerging trends like agentic AI and autonomous systems, potentially preparing for a more revolutionary change?
We have analysed data from recent conferences, customer discussions, and insights from Intelligent Automation experts, two distinct trends are emerging:
- Agentic AI and autonomous systems: These advanced technologies aim to automate processes without relying on traditional RPA. With the promise of self-governing systems capable of complex decision-making, agentic AI could redefine how we think about automation.
- RPA vendors doubling down: On the other hand, established RPA providers are refining their offerings, integrating AI, and enhancing capabilities to maintain their relevance in an increasingly competitive market.
What Does This Mean for the Future of Automation?
The battle between these two paths raises critical questions for automation leaders. If agentic AI takes the lead, RPA as we know it might fade, replaced by more autonomous systems. Alternatively, if RPA evolves and adapts, it could experience exponential growth, cementing its role in enterprise automation for years to come.
Regardless of which path dominates, one thing is clear: the tools and technologies we rely on today will look very different in the near future. This evolution presents both opportunities and challenges for organizations that have invested heavily in RPA.
What Do Industry Experts Think?
The automation community is buzzing with discussions about the future of RPA and agentic AI. Here’s a summary of insights shared by thought leaders in the field:
- Agentic AI as a complement, not a replacement
Many experts agree that agentic AI will not completely replace RPA but will coexist as a tool to address different challenges. For example, Agnius B. from Definra highlights that agentic systems are better suited for dynamic, unpredictable processes, while RPA remains indispensable for repetitive, structured tasks. Marcin D. from Dovista echoes this sentiment, comparing the relationship between RPA and agentic AI to email and phone calls—technologies that coexist and complement each other. - The synergy between RPA and Agentic AI
Experts like Leon P. from Futurise and Daman T. predict a hybrid model where RPA serves as the foundation for stable processes, while agentic AI tackles unstructured and dynamic tasks. Daman also emphasizes the importance of strategic investments in both technologies to future-proof organizations. - Short-term vs. Long-term outlook
While Christian W. from Württembergische and others believe RPA will remain relevant in the next few years, many, like Rajesh N. from Automatorr, foresee agentic AI dominating in the long term. Simon McDermott from Pointee suggests that agentic AI will take a significant share of the market within 36 months, especially in innovative organizations. - Challenges for agentic AI adoption
Richard D. from Tquila Automation and Tetiana Y. from Unzer (ex-Celonis) highlight the current limitations of agentic AI, such as the lack of auditability and the need for robust architectures to manage multi-modal interactions. These hurdles might slow its adoption, making RPA a more practical choice in certain scenarios for now. - Industry applications and evolution
Several voices, including Doug Shanon and Thomas R. from BluePrism, highlight the transformative potential of autonomous systems. However, they stress that RPA still plays a vital role in organizations with legacy systems or high-cost modernization barriers.
Key takeaways: A hybrid future?
The consensus is that the future of automation lies in synergy. As agentic AI continues to evolve, it might likely work alongside RPA to address a broader range of use cases. For automation leaders, this means preparing for a future where these technologies not only coexist but also complement each other to drive innovation and efficiency.
What do you think? Is the industry headed for a hybrid model, or will one technology eventually outshine the other?
