Sanjoy Sarkar – SVP, Senior Director – Application Development & Support, First Citizens Bank.
For years, Robotic Process Automation (RPA) has been one of the most transformative technologies in enterprise automation, helping organizations eliminate repetitive work, improve operational efficiency and reduce manual errors. Yet with the rapid rise of Generative AI and autonomous agents, a common narrative has emerged: RPA is dead.
I don’t believe that’s true.
In my experience leading enterprise workflow and automation initiatives, the conversation shouldn’t be about whether AI will replace RPA. Instead, it should focus on how AI is fundamentally changing the role of enterprise automation platforms. What we’re witnessing isn’t the end of RPA—it’s the beginning of its next evolution.
The Misconception About RPA
The excitement surrounding AI is understandable. Large language models can summarize documents, answer complex questions, generate software code, analyze large volumes of information and interact with users using natural language. These capabilities are redefining how organizations think about productivity.
Because of this, many assume that AI can now perform everything automation platforms were built to do. That assumption overlooks one important reality.
Generating an answer is very different from executing a business process.
While AI excels at understanding context and making recommendations, enterprises still need technologies that reliably execute transactions, interact with multiple business systems, enforce business rules, maintain audit trails and operate within strict governance and compliance requirements.
That responsibility hasn’t disappeared.
Intelligence Doesn’t Equal Execution
One of the biggest lessons I’ve learned throughout enterprise automation programs is that automation success has rarely been about automating individual tasks. The real challenge has always been orchestrating complete business processes.
Consider a simple business scenario.
AI can review an invoice, extract relevant information, identify potential discrepancies and even recommend the next course of action. But completing the process requires significantly more.
The information must be validated against business rules. The transaction may require approvals based on financial thresholds. Multiple enterprise systems need to be updated. Audit logs must be maintained. Exceptions need to be routed to the correct teams. Service-level agreements must continue to be monitored.
These are execution problems—not intelligence problems.
This is precisely where enterprise workflow and automation platforms continue to deliver value.
How Enterprise Automation Is Evolving
Rather than replacing automation platforms, AI is becoming an integral capability within them.
Across the enterprise technology landscape, nearly every major workflow and automation platform has introduced AI-powered capabilities. AI-assisted development, intelligent document processing, conversational interfaces, process recommendations, predictive insights and autonomous agents are becoming standard features. This is not a sign that automation is disappearing.
It is evidence that automation platforms are becoming significantly more intelligent.
The organizations achieving the greatest success are not replacing their workflow platforms or automation investments. They are enhancing them by embedding AI where it creates measurable value while continuing to rely on workflow orchestration and governed execution to deliver business outcomes.
The New Role of RPA
Perhaps the biggest shift is how we define the role of RPA itself.
Historically, RPA was often viewed as software that mimicked human interactions with applications—opening screens, copying information, clicking buttons and moving data between systems. That definition is becoming outdated.
Today, I see RPA evolving into the enterprise execution layer for intelligent business operations. If AI determines what should happen next, RPA performs how that work gets done. If workflow determines when an action should occur, RPA carries out that action consistently across enterprise applications.
In many ways, AI is becoming the brain, workflow provides the orchestration and RPA becomes the hands that execute work reliably and repeatedly. That evolution is far more significant than simply automating clicks on a screen.
Workflow Remains The Foundation
One lesson continues to stand out across every enterprise transformation initiative I’ve participated in: successful automation is built on governance. As organizations adopt increasingly intelligent systems, governance becomes even more important—not less.
Enterprise leaders still need visibility into how decisions are made. They need approval mechanisms for high-risk activities, complete auditability for regulatory compliance and exception handling when business conditions change.
These aren’t limitations of AI. They are requirements of enterprise operations. Workflow platforms remain the foundation that coordinates people, AI capabilities, enterprise systems and automation technologies into a single governed business process.
Without that orchestration layer, organizations risk creating isolated pockets of intelligence rather than scalable enterprise automation.
Success Should Be Measured Differently
Several years ago, automation success was commonly measured by the number of bots deployed or the number of hours saved. Those metrics are becoming less meaningful. Organizations are increasingly evaluating automation based on broader business outcomes.
Can work move faster without sacrificing quality?
Can customer experiences improve while maintaining compliance?
Can employees focus on higher-value activities instead of repetitive administrative work?
Can AI recommendations be executed consistently under enterprise governance?
These are the metrics that matter because they reflect business transformation rather than technology adoption.
Looking Ahead
The future of enterprise automation will be defined by AI, workflow platforms and automation technologies working together as complementary capabilities. AI will continue making enterprise systems smarter by interpreting information, generating insights and assisting decision-making.
Workflow platforms will continue orchestrating end-to-end business processes while enforcing governance, compliance and accountability. Automation technologies—including RPA—will continue serving as the trusted execution layer that connects intelligent decisions to real business outcomes.
Organizations that understand this evolution will build automation ecosystems that are not only more intelligent, but also more resilient, scalable and trusted. The conversation should no longer be whether RPA will survive the age of AI. The better question is how organizations can combine intelligence, workflow and automation to unlock the next generation of enterprise transformation.
In my view, that’s where the real future of automation begins.
The views and opinions expressed in this article are solely my own and are based on my personal professional experience and observations in the enterprise automation industry. They do not represent the views, strategies or positions of my current employer, any former employer or any organization with which I have been associated.
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