The chief of UiPath, the New York-listed automation and AI software company best known for its robotic process automation platform, has said the rise of agentic AI is fundamentally reshaping enterprise software development, testing and governance across banking and financial services.
The company, which has expanded aggressively beyond traditional robotic process automation into AI-driven orchestration, testing and autonomous workflows, has launched UiPath for Coding Agents, a platform-wide integration designed to connect coding agents directly into enterprise development pipelines, governance frameworks and testing environments.
UiPath founder and chief executive Daniel Dines said the emergence of coding agents represents “a fundamental shift” in the “definition of a builder” on the company’s platform.
“With the new added bonus of agentic software application development builders now in the mix, the current state of programming is undergoing a fundamental shift,” Dines said.
The launch comes as banks and financial institutions struggle to manage surging volumes of AI-generated code while maintaining resilience, regulatory compliance and software quality.
Testing as the critical bottleneck
UiPath has increasingly positioned testing and quality assurance at the centre of enterprise AI adoption, warning that software delivery is accelerating faster than traditional QA processes can handle.
“Most reports suggest that between 70% and 80% of developers are using AI tools to help them code. But the picture is quite different when it comes to quality assurance with adoption of AI sitting well under 50%,” said Gerd Weishaar, general manager and senior vice president of testing products at UiPath.
“I’m a little bit surprised that quality assurance is not picking up much faster because how would you make sure that this code is safe, that it’s working in an enterprise context.”
Weishaar previously warned that “traditional testing is recognised by CIOs and CTOs as the biggest bottleneck to delivering new innovations,” particularly in regulated sectors such as banking where legacy QA processes remain heavily manual and resource intensive.
“I’m a little bit surprised that quality assurance is not picking up much faster.”
– Gerd Weishaar
For financial institutions increasingly embedding AI-generated code into payments, lending, onboarding and digital banking platforms, UiPath argues that testing can no longer operate as a downstream validation function.
Instead, the company is pushing agentic testing, autonomous orchestration and AI-driven governance as the next stage of enterprise software delivery.
According to UiPath, most coding agents currently operate in isolation from enterprise-grade governance, CI/CD pipelines and operational controls.
“Despite the popularity of coding agents, they still exist largely in isolation, disconnected from enterprise development workflows, security policies, code review processes and deployment pipelines,” the company said.
Connecting coding agents
Dines warned that without orchestration capable of connecting coding agents into existing CI/CD infrastructure, testing frameworks and governance controls, “any coding agent outputs require manual handoffs and human intervention at almost every step.”
The company said this prevents AI-driven productivity gains from scaling beyond development sandboxes.
“We are first to market with a platform that treats AI-generated automations as first-class citizens, with the same governance, reliability, and scale that enterprises demand,” Dines claimed.
“Now, anyone can describe what they want, direct a coding agent to produce it, and carry through every stage to production. It lowers the barrier to who can build, crossing the line from idea to execution.”
UiPath said its orchestration layer provides the underlying governance, observability and execution controls regardless of which coding agent or AI model enterprises choose to use.
“The orchestration layer is the constant, connecting into agents with observability, execution and governance as the underpinning element, regardless of the coding agent being used,” the company said.
UiPath for Coding Agents currently supports Anthropic’s Claude Code and OpenAI Codex, with further integrations planned.
Governance and auditability
With financial institutions facing growing pressure from regulations such as DORA and the EU AI Act, UiPath is heavily emphasising governance and compliance capabilities across its AI automation platform.
The company said the platform includes “policy enforcement, audit trails, credential vaults, role-based access control, and runtime controls” for automations created either by human developers or AI agents.
UiPath has also embedded “extended agent guardrails for controlled agency and sensitive data use protection” alongside audit capabilities designed to “streamline compliance, accelerate investigations, and enforce accountability.”
Its wider Test Cloud platform now includes “self-healing test automation, autonomous testing, and chatting with UiPath’s AI-driven Autopilot in Test Manager, delivering a true end-to-end solution for agentic testing.”
Weishaar said testing teams are increasingly working alongside AI agents throughout the software lifecycle.
“Testing teams engage interactively with AI agents that act like partners in collaborating, supporting, and working in tandem with testing professionals around the clock across the entire testing lifecycle,” he explained.
Human oversight
Despite the growing autonomy of AI-driven development and testing, UiPath executives stressed that human oversight remains critical.
“We often say that in AI we need a human in the loop,” Weishaar said. “In this instance, it will be human on the loop with full autonomous agents doing the work.”
“And the human will, at the end say, that is right, this works and will give the release stamp at the end.”
UiPath argues that QA teams inside banks are increasingly shifting toward governance, validation and release approval roles as AI agents take over more testing and automation work.
“Seeing huge or large amounts of code being generated in front of you and being responsible that this code does exactly what it’s supposed to do is a big burden,” Weishaar said.
“I don’t think it’s easily doable, to be honest.”
The company believes AI-driven QA and orchestration are becoming essential to managing that complexity.
“What AI does, I think, is a significant change here. It lowers the cost of creation, and it lowers the amount of maintenance because we have true self-healing now. You can build automation and easily maintain it.”
Banks including Bank Dhofar, Bank of East Asia, First Abu Dhabi Bank and Sweden’s Ikano Bank are already using UiPath-led automation programmes to strengthen QA processes, operational resilience and software delivery consistency across digital banking platforms.
For financial services firms facing increasing software complexity and mounting regulatory scrutiny, UiPath’s message is that testing, governance and orchestration are becoming the foundation for scaling AI safely inside the enterprise.
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