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UiPath is making waves in 2025 with a leap into “agentic automation” — a combination of AI, robotic process automation (RPA) and orchestration aimed at helping enterprise processes become more autonomous. The launches of Autopilot, Agent Builder, Agentic Orchestration and Agentic Testing mark more than incremental updates. They signal a new model: software agents that can adapt, learn and make decisions in complex business environments.
UiPath’s Unified Platform and Strategic Edge
Unlike traditional automation, which relies on rigid, rules-based scripts, agentic systems purport to provide intelligent, context-aware agents. These AI-driven tools collaborate across workflows, integrate with third-party frameworks and self-heal when application conditions change. Bots are no longer task followers; they’re proactive digital colleagues that plan, act and optimize in real time.
What sets UiPath apart is its unified platform that brings together AI agents, robots and humans in dynamic business environments. The company focuses on open integration with partners such as Google Cloud, LangChain, and Anthropic), enterprise-grade governance and scalability.
As enterprises pursue autonomous systems, a central question emerges: Is agentic automation truly transformative, or just smarter automation?
UiPath is betting on the former, asserting that intelligent agents can do more than automate — they can help organizations work better.
Agentic AI Amplifies Technical Debt
UiPath’s shift is a pivotal moment in enterprise automation, according to Richard Skellett, chairman of Bloor Research. Tools such as Autopilot and Agent Builder represent a more adaptive orchestration model, where AI systems move beyond static workflows into contextual decision-making. These agents help non-technical users coordinate tasks across departments such as finance, human resources and compliance, speeding deployment and increasing the return on investment.
However, Skellett cautioned against layering these capabilities onto outdated structures. “Layering intelligent agents onto outdated frameworks only accelerates dysfunction,” he warned. Without rethinking the operating model, agentic systems may amplify inefficiencies rather than solve them.
“Agentic tools don’t solve the root causes of dysfunction — they accelerate symptoms,” Skellett added “The success of UiPath’s roadmap depends not only on tool sophistication but also on how well companies adapt structurally, through cultural change, workforce strategy and governance.”
While UiPath provides auditing and governance features to help mitigate compliance risks, broader challenges such as labor liability, skill gaps and disengagement remain. Bloor Research advocates for FusionWork, a framework designed to align digital and human workers through shared purpose and accountability.
UiPath may be setting the technical standard, but transformation requires confronting legacy systems and labor debt. “The agentic age has begun, but without a reset, we may just automate our way deeper into dysfunction,” Skellett said. The risk isn’t just inefficiency, but also costly misalignment. SAP’s $2.2 billion restructuring tied to AI role reductions shows the stakes.
UiPath's Agentic Automation: The Next Step Up from RPA
UiPath’s agentic automation is part of a larger trend in AI: reducing human intervention while making orchestration more efficient, said Matthew Peters, CTO at CAI. By helping AI agents coordinate across siloed systems, UiPath shifts automation from static task execution to dynamic, outcome-driven workflows. This means they can work faster and help employees be more productive.
“This technology supercharges productivity and achieves what a person cannot in the same amount of time,” Peters said. Agentic systems outperform traditional RPA by coordinating across complex environments while still requiring developer oversight to avoid unintended outcomes.
Agent Builder and Autopilot offer low-cost entry points for enterprises to experiment and update workflows. Paired with digital twin concepts, they support simulation and optimization before deployment. Although adoption is slowed by legacy systems and policies, these tools give companies the opportunity to rethink — not just patch — how work is delivered.
How UiPath Manages Agentic AI’s Risks and Cultural Change
Many organizations already have the IT foundations needed for agentic automation. The challenge lies in cultural readiness, Peters said. Educating staff, promoting flexibility and encouraging openness to autonomous systems are important. Training and transparent communication also help this cultural shift happen faster.
Industries such as finance, healthcare and manufacturing stand to benefit most. In finance, agentic automation streamline tasks such as transaction reconciliation and audits. Healthcare automates patient data management and scheduling, freeing staff for direct care. Manufacturing improves supply chains and predictive maintenance, reducing downtime and increasing output.
Still, increased autonomy introduces risk. AI agents may misinterpret context and gain access to sensitive data, raising security and compliance concerns. UiPath addresses this through Explainable AI (XAI) and trace logs that support full auditability.
“It’s important to have a ‘glass box’ approach to automation,” Peters emphasized. “Organizations must be able to demonstrate how ‘input A’ led to ‘output B’.” Transparent automation builds trust and helps comply with regulations.
Governance, monitoring and audit trails are essential to managing AI risk. Without these safeguards, autonomous decision-making can backfire. Robust oversight isn’t optional; it’s required to use agentic AI safely.
The future lies not in automating faster but in redesigning work itself. UiPath helps enterprises take part in that change, but the responsibility for transformation rests with the organizations themselves.
Trusting Agentic AI with Human oversight
UiPath’s strategy is part of a broader move toward domain-specific automation supported by human oversight, said Sertac Karaman, director of the Laboratory for Information and Decision Systems at MIT. While AI agents can now gather data, summarize it, propose actions and ask for human approval, he expects this dynamic will evolve.
“As humans use these tools, they will get more confident in suggesting actions,” Karaman said . “Eventually, the rate at which humans choose to accept the proposed actions would increase dramatically, while the time for review reduces.” In time, agents will be trusted with increasingly autonomous decisions.
Compared with traditional RPA, which relies on manually coded rules and extensive expert setup, agentic systems are more flexible. They run with minimal instructions and use existing formats such as PDFs and Word documents to interpret context and execute tasks.
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“Agentic systems promise to work without explicitly setting up detailed rules,” Karaman said. “The setup time can be far smaller. The updates are also much quicker.”
Agentic AI’s Adoption Challenge
Products like Agent Builder and Autopilot are an evolution in how enterprises build and deploy workflows. They support agent-human collaboration, and as human supervisors continue using them, the tools improve through interactive learning.
However, adoption presents a challenge, especially culturally. Technically, many organizations are ready, with cloud-based tools already in place. UiPath’s offerings can be deployed as integrated cloud services, making the technical transition manageable.
Still, replacing trusted rule-based systems with AI-driven agents won’t happen overnight. Agentic tools should “enhance existing rule-based systems” rather than replace them initially, Karaman said, to reduce resistance and disruption.
Sectors with fewer compliance constraints, such as retail or customer service, are likely to adopt agentic automation first. Even in highly regulated industries such as finance and healthcare, there are practical applications, such as automating consumer-facing processes or simplifying tasks for human supervisors.
But with more autonomy comes higher risk. “Even small rates of mistakes can lead to important errors,” Karaman warned, especially when billions of decisions are being made.
Agentic AI will need a hybrid approach, blending AI with human oversight, Karaman said. Sensitive or high-stakes tasks will still require review, and rule-based guardrails can help contain risk during early deployment phases.
UiPath appears ahead of its competitors in bringing these capabilities to market. Yet, Karaman expects others like Microsoft Power Automate and Automation Anywhere to catch up quickly. “This is a technology that's on everyone's radar,” he said.