As enterprises seek smarter, more autonomous automation solutions, UiPath has unveiled a powerful suite of agentic AI tools designed to go beyond traditional RPA. AI agents don’t just follow instructions - they plan, decide, and act across complex workflows. In this article, we explore what agentic AI really means in practice, how UiPath’s platform enables it, and what it offers to businesses, partners, and developers ready to embrace the next generation of automation.
What Is Agentic AI?
Agentic AI refers to Artificial Intelligence systems that act with autonomy, initiative, and adaptability to pursue goals, rather than just following preset rules or reactive instructions. In essence, an Agentic AI can independently make decisions and take actions in dynamic environments to achieve objectives. Such AI agents combine multiple AI techniques (like Machine Learning, Natural Language Understanding, and Planning) so they can plan, act, learn, and improve continually. Key capabilities of agentic AI include:
- making context-aware decisions,
- breaking down goals into subtasks,
- using tools or other systems to accomplish tasks,
- adapting their behavior over time to get better results.
These capabilities unlock a new class of complex, end-to-end applications for AI across the enterprise that surpass the capabilities of traditional rule-based bots or static algorithms.
In practical terms, agentic AI enables the creation of AI agents - software programs that behave like autonomous coworkers. They can interpret goals, navigate unstructured scenarios, and collaborate with both software and humans. This represents a step change from earlier generations of automation or “intelligent” bots. Instead of being limited to predefined steps, an agentic AI can dynamically figure out how to fulfill a task. For example, an Agentic AI might be tasked with optimizing a supply chain: it could analyze real-time logistics data, predict bottlenecks, adjust delivery routes on the fly, and even trigger reordering of inventory - all without needing a human to micromanage each step. The ultimate promise is that AI agents become trusted digital colleagues that can tackle decision-intensive work and continuously learn, while humans provide high-level guidance and oversight.
From RPA to Agentic Automation: UiPath’s Vision
UiPath – known for its leading Robotic Process Automation (RPA) platform – is now fully embracing Agentic AI as the next evolution of enterprise automation. In late 2024, UiPath’s CEO Daniel Dines described this shift as “the natural evolution of Robotic Process Automation”, moving from purely rules-based bots to more flexible, AI-driven agents that collaborate with people. Traditional RPA excels at structured, repetitive tasks (think data entry or form processing). Agentic automation, by contrast, combines AI agents, RPA robots, and people in a symbiotic loop to tackle complex workflows that require dynamic decision-making. In this model, AI agents provide the “brainpower” - they autonomously plan and coordinate tasks based on high-level goals.
Crucially, agentic automation isn’t about replacing humans – it’s about extending automation to new frontiers. UiPath emphasizes that agentic AI enables enterprises to automate “the myriad of workflows that require a more dynamic, context-aware approach,” far beyond the scope of what RPA alone can do. For business leaders, this means that tasks involving complex decision criteria, unstructured data, or changing conditions (e.g., approving insurance claims, optimizing a factory floor, or personalizing customer service in real-time) can now be partially or fully automated. Early benefits reported include major efficiency gains, improved customer experiences through 24/7 intelligent service, and human augmentation – freeing employees from grunt work so they can focus on strategic and creative initiatives.
[VIDEO]
https://www.youtube.com/watch?v=Fw36aCWxVgU&t=1s&ab_channel=UiPath
To make this vision a reality, UiPath has rolled out the first enterprise-grade platform for agentic automation. Announced at the UiPath FORWARD conference and the Agentic AI Summit in 2024-2025, the reimagined UiPath Platform is built to orchestrate AI agents, software robots, and people across end-to-end business processes. This platform includes new tools and capabilities (described below) that allow organizations to “agentify” their processes - in other words, infuse AI decision-making and autonomy into workflows while maintaining the governance, security, and reliability that enterprises require. An essential part of UiPath’s strategy is the recognition that orchestration and oversight are vital: when you have fleets of AI agents and bots working together, you need robust controls (guardrails, auditing, human-in-the-loop checkpoints) to manage this intricate ecosystem safely at scale. UiPath’s Agentic AI suite is engineered to provide that control, ensuring businesses can confidently deploy autonomous AI solutions without “letting the robots run wild.”
Inside UiPath’s Agentic AI Product Suite
UiPath’s agentic AI strategy comes to life through a suite of integrated tools and platform features. These include UiPath Maestro, Agent Builder, Autopilot, and Healing Agent. Together, they empower companies to develop, deploy, and govern AI-powered agents alongside traditional automations. Below, we explore each key component and how it contributes to agentic automation:
UiPath Maestro – Agentic Orchestration for the Enterprise
Think of UiPath Maestro as the command center for orchestrating AI agents, RPA robots, and people across complex processes. It’s essentially an evolved orchestration and BPM (Business Process Management) platform designed for the agentic era. With Maestro, organizations can visually model end-to-end processes in BPMN 2.0, incorporating tasks performed by AI agents, robots, and humans into a unified workflow. Process designers use familiar BPMN constructs (events, gateways, etc.) - or can even leverage Autopilot’s AI assistance to generate process models – to map out how work should flow between agents and traditional steps. Maestro then handles the coordination, integrating with all parts of the tech stack to connect UiPath AI agents, third-party AI services, software bots, and human user interfaces into a seamless sequence. Business rules and decisions can be defined using DMN (Decision Model & Notation) and plugged into processes, adding logical guardrails for the AI’s behavior.
Once processes are deployed, Maestro provides enterprise-grade execution management. This includes real-time monitoring of process instances, exception handling tools (e.g., automatically routing issues to a human or retrying steps), and controls to pause, resume, or alter processes on the fly. Importantly, Maestro also brings analytics and optimization into the loop: it can pinpoint bottlenecks or inefficiencies in workflows and surface performance metrics so teams can continually improve their operations. In short, Maestro ensures that “agents think, robots do, people lead” in harmony. As one early user described it, “UiPath Maestro is the orchestration layer that connects everything – robots, AI agents, and systems inside and outside UiPath – ensuring seamless coordination across complex automated processes.”. By extracting high-level business rules from hard-coded scripts and managing them centrally, Maestro helps create more resilient, end-to-end automations that can adapt to changing conditions. It’s the backbone that lets companies operate a multi-agent workforce at scale.
UiPath Agent Builder – Creating Custom AI Agents with Ease
If Maestro is the orchestra conductor, the Agent Builder is the factory where new AI agents are crafted. UiPath Agent Builder™ is a development tool (integrated into the UiPath Studio family) that enables developers - and even non-developers - to build, test, and launch AI agents in a low-code environment. Rather than coding an agent’s logic entirely from scratch, Agent Builder provides a guided framework. Users can start with prebuilt agent templates from the UiPath Agent Catalog, which cover common use cases and industry scenarios (for example, an agent template for IT service desk triage or for invoice analysis). These templates come with ready-made logic that can be easily customized via a no-code/low-code interface in Studio Web. For those with unique needs, you can also create a new AI agent from a blank slate – the environment is designed to be “easy to use, low-code, fully integrated” into UiPath Studio.
Under the hood, an AI agent built in this way can incorporate various AI skills: it might use an NLP model to understand a text instruction, a machine learning model to make a prediction, and RPA activities to take action in enterprise apps. Agent Builder enables you to combine and customize AI components and classical automation steps as building blocks for the agent’s behavior. Critically, it also provides tools to test and refine the agent before it is produced. Users can run the agent in realistic workflows, debug its decisions, and even get an “Agent Score” - a metric that evaluates the agent’s performance against expected outcomes. This scoring, along with an Agent Optimizer, helps ensure your AI agents are enterprise-grade (accurate, reliable, not hallucinating or going off-script) before they’re deployed widely.
When it comes to deployment, Agent Builder offers flexibility: a finished agent can be packaged as an activity that is invoked within existing RPA workflows (allowing you to integrate intelligence into legacy automations), or it can be published as an agentic task orchestrated by UiPath Maestro within a broader process. In both cases, the agent runs within the UiPath platform’s governance envelope. This focus on enabling “citizen developers” and professional developers alike to create custom AI agents is a huge part of UiPath’s strategy. “Providing customers the ability to build their own specialized agents in a simple, low-code IDE or from a pre-built template makes it easy to automate new use cases, avoid costs, and stay ahead of competitors,” notes UiPath’s Chief Product Officer. Large enterprises and partners (like consulting firms) are already exploring this - Deloitte, for example, participated in previews of Agent Builder and identified diverse use cases across both internal systems and SaaS apps, positioning UiPath as “the orchestration engine of the agentic age.” With Agent Builder, organizations can encapsulate proprietary know-how into AI agents and continuously expand their automation portfolio as new opportunities emerge.
UiPath Autopilot – Generative AI Assistant for Automation
Generative AI also plays a starring role in UiPath’s agentic AI suite, primarily through UiPath Autopilot™. Autopilot is described as “a new set of AI-powered experiences across the UiPath Platform that make every user, from interns to CEOs, more productive.”. In practice, Autopilot is like having a smart copilot (no pun intended) for automation work. It utilizes powerful Generative AI models (LLMs) under the hood to enable users to create and interact with automations through natural language. For example, with Autopilot, you can simply describe a workflow you want automated (in plain English) and get a “text to workflow” generation – the platform will build a suggested automation sequence for you. This lowers the barrier to using the UiPath platform, enabling business analysts or less-technical staff to automate processes without writing code. Autopilot can also generate complex expressions or code snippets from natural language (“text to expression”), assist in creating UI apps, and more. It’s akin to having a ChatGPT-like assistant trained for UiPath development.
One notable Autopilot experience is in UiPath Studio and Assistant: users can have a conversational interface to build or run automations. In fact, UiPath made Autopilot available for free to encourage broad usage – “an AI tool that allows employees to automate workflows through a conversational interface (i.e., ChatGPT-like)” on both Windows and Mac. This means a user could type, “Gather all invoices from emails and enter them into our accounting system,” and Autopilot would assemble an automation or an AI agent to do just that, pulling together the necessary activities and logic. It effectively bridges the gap between intent and execution, fast-tracking automation development. Another facet of Autopilot is its assistance to everyday users through UiPath Apps and Assistant. For example, it can integrate with a CRM system via Automation Co-Pilot (in-app assistant), enabling a salesperson to trigger an AI agent by asking, “Summarize the last quarter’s pipeline and draft a follow-up email.” (Notably, Automation Anywhere has a similarly named Automation Co-Pilot feature – more on competitors later - underscoring that conversational AI control is a hot trend in automation.)
It’s important to note that Autopilot is tightly integrated with UiPath’s governance features. All those AI-generated workflows still run with the same security, permissions, and auditing as any UiPath automation. Autopilot helps users specify the desired outcome to the AI agent, and the agent determines the necessary steps. It’s a clear example of agentic AI and generative AI working hand in hand: generative AI creates and suggests, while agentic AI plans and acts to carry it out.
UiPath Healing Agent – Self-Healing Automation with AI
One of the unsung heroes of the agentic toolkit is the UiPath Healing Agent, which addresses a very practical pain point: broken automations. In traditional RPA, if a target application’s UI changes or an unexpected pop-up appears, automations tend to fail - requiring developers to manually update selectors or add new error handling. The Healing Agent brings an AI-driven “self-healing” capability to these situations. It performs just-in-time analysis whenever a UI automation encounters an issue, and intelligently determines a recovery strategy. For instance, if a button that a robot clicks suddenly moves on the screen due to a UI redesign, the Healing Agent can analyze the DOM and suggest a new selector or locate the element’s new position. It may also insert a smart delay if a page is loading slowly, or automatically close an interfering overlay window. Essentially, it’s like an on-call mechanic that fixes your automation in real-time to keep it running.
The Healing Agent provides two main benefits:
- It can surface recommendations when an automation fails, presenting the developer (or operations team) with suggested fixes, such as updated selectors or code snippets, to handle the detected issue. This guidance speeds up maintenance dramatically.
- It can self-heal on the fly by applying certain fixes automatically when safe to do so. UiPath had already introduced a robust fallback mechanism with its Unified Target technology (a way for bots to try alternate methods if a UI element is not found).
The Healing Agent augments this with AI-driven strategies, enabling certain processes to recover without human intervention. For example, if a web app loads a bit slower today, the agent could dynamically wait longer or refresh the page, rather than failing. If a random modal appears, it could detect and close it before the bot continues. These capabilities are crucial in unattended scenarios (background automations on servers) where maximum uptime is desired, as well as in attended use (automation assisting a human), where unpredictable user actions or environmental hiccups can occur.
By reducing downtime and manual fix efforts, Healing Agent increases the resilience and scalability of agentic automation. In a world where AI agents and robots collaborate on long-running processes, having them automatically adapt to minor changes means fewer breakdowns and happier operations teams. It’s worth noting this is a differentiator for UiPath – not all competitors have an equivalently advanced self-healing mechanism. The Healing Agent showcases how embedded AI can continuously watch over and optimize the “health” of automations, which is a huge value-add when enterprises run thousands of bots.
Building and Customizing AI Agents: The Open Ecosystem
A key question for enterprises is whether they must rely solely on UiPath’s out-of-the-box AI agents or can build their own and integrate other AI technologies. UiPath’s answer is an emphatic yes to openness and extensibility. The Agentic AI platform is designed as an open ecosystem, meaning it can incorporate third-party AI models, custom-built agents, and external tools into your automations. For example, UiPath has partnered closely with Microsoft and OpenAI – you can plug in the Azure OpenAI service or OpenAI APIs and use models like GPT-4 within UiPath’s Autopilot or your own agents, all governed by the AI Trust Layer. In fact, UiPath recently announced a bi-directional integration with Microsoft Copilot Studio: developers can orchestrate Microsoft’s Copilot agents alongside UiPath agents using Maestro, and even embed UiPath automations inside Microsoft’s AI workflows. This is a significant development – it means that if you’ve built some AI capabilities within the Microsoft ecosystem, UiPath can integrate them into a larger, more comprehensive process with full coordination. The integration enables cross-platform AI collaboration, orchestrating, for example, a seamless flow where a Microsoft 365 Copilot handles Outlook emails and a UiPath agent handles SAP transactions.
Beyond Microsoft, UiPath supports various AI frameworks. They’ve introduced the ability to run LangChain or LangChain-like agents (notably mentioned as “LangGraph”) natively on UiPath. This empowers more advanced AI developers to use Python and open-source AI libraries to create agents, then deploy them into UiPath’s environment without changing a single line of code. The benefit here is that the governance, security, and monitoring of UiPath (via the Trust Layer, etc.) will also apply to those custom agents, providing the best of both worlds: open innovation and enterprise control. Partners and internal teams can thus bring specialized AI research or domain-specific models into the fold. For instance, a partner might use a custom computer vision model for an agent that inspects product quality on an assembly line. They can integrate that model through UiPath’s AI Center or as a skill in Agent Builder, then orchestrate it with other tasks in Maestro.
UiPath’s Integration Service and connector ecosystem allow linking into virtually any system or AI service. They offer pre-built connectors to popular AI services (such as Google, Amazon, and IBM), as well as a Connector Builder for custom solutions. The platform’s model-agnostic approach means you can swap out AI models as needed – for example, using a more accurate model for NLP as it becomes available – without redesigning your processes. This flexibility is crucial in the fast-moving AI landscape. It also underscores a philosophical difference: while some competitors might push you into their closed AI stack, UiPath is signaling that interoperability is a priority. As they put it, many providers are building “walled gardens,” but UiPath aims to let customers “focus on business outcomes without getting bogged down by technology limitations,” whether the tech is from UiPath or someone else.
For CTOs and tech-savvy executives, this means investing in UiPath’s agentic AI platform doesn’t cut you off from other AI advances – you can incorporate the latest and greatest, including internal AI innovations your data science team develops. And your internal developers (with Python skills, for example) can contribute directly by building agents outside UiPath and then importing them in. This open yet governed model is likely to appeal to enterprises that want to avoid vendor lock-in and maintain an agile AI strategy.
Agentic AI in the Automation Landscape: UiPath vs Competitors
With every tech revolution comes a competitive race. UiPath may be a front-runner in agentic automation, but other major players are also vying to define this space:
Microsoft (Copilot + Power Automate)
Microsoft has infused generative AI (Copilot) across its product suite – from Office apps to GitHub and the Power Platform. In the context of automation, Power Automate (Microsoft’s RPA tool) now features Power Automate Copilot, which allows users to build workflows by describing what they need in natural language, much like UiPath Autopilot. Microsoft’s strength is the deep integration of Copilot AI into everyday productivity tools (Teams, Outlook, Dynamics, etc.), essentially turning them into agentic assistants for end users. For example, a Microsoft 365 Copilot can summarize your emails and take actions such as scheduling meetings or drafting responses. However, Microsoft’s approach has historically been somewhat siloed – Copilot in one app helps with tasks within that app. They are rapidly evolving this, and with Copilot Studio, Microsoft introduced a way to create custom AI agents (called “plugins” or “skills” for Copilot) that can perform multi-step tasks across the Microsoft ecosystem.
When Microsoft announced a partnership with UiPath, it enabled Copilot Studio agents to integrate with UiPath and leverage UiPath’s orchestration strengths. This suggests that rather than directly competing in complex, cross-system processes, Microsoft is leveraging UiPath to extend Copilot’s reach beyond the Microsoft cloud. That said, for organizations heavily in the Microsoft stack and with simpler automation needs, Power Automate plus Copilot might appear as a one-stop solution. Microsoft’s brand and existing footprint are strong, but in agentic AI, they are still primarily focused on generative AI content creation and user assistance. UiPath provides more end-to-end process orchestration across diverse systems (including non-Microsoft systems), which can be a deciding factor for enterprises with heterogeneous environments.
Automation Anywhere
Automation Anywhere, another RPA leader, has explicitly jumped into the agentic automation fray. They even refer to their platform as an “Agentic Process Automation System” in their marketing materials. AA’s flagship in this domain is Automation Co-Pilot, an AI-powered assistant embedded in applications to connect people with automation and AI. Automation Co-Pilot is “powered by generative AI”, allowing natural language commands and multi-step automations similar to UiPath’s Autopilot. A user in a CRM or an ERP can invoke Co-Pilot in plain language to fetch data or execute a process without leaving their screen. AA has showcased use cases, such as an insurance claims process where Co-Pilot orchestrates multiple bots and AI to handle a claim end-to-end with minimal human intervention. They emphasize being the “Leader in Agentic Process Automation” (a bold claim, evidenced by their website footer) and have introduced governance features (guardrails for AI usage, etc.) to compete with UiPath’s trust layer.
In comparison, AA’s approach is quite similar conceptually – combining generative AI for ease of use with RPA and AI to enable autonomous workflows. However, Automation Anywhere’s platform has historically been less unified than UiPath’s and may require more stitching together of components. AA’s Document Automation (IDP) is praised as best-in-class by some users, and they tout a strong ROI for their automation solutions. Yet, UiPath has an edge in breadth: a larger activities library, a built-in process mining tool, a dedicated test suite, and now the full agentic suite (Maestro, etc.), which AA is still catching up to. For many enterprises, the scalability and security demonstrated by UiPath in large deployments give it a competitive edge. Still, AA’s focus on “quick-thinking automation” and its own use of the term agentic indicate that they are a close competitor in vision. The choice may come down to existing ecosystem investments and specific feature preferences (e.g., AA’s cloud-native architecture vs UiPath’s hybrid options).
SS&C Blue Prism
Blue Prism, now part of SS&C, was a pioneer in RPA for enterprises. They, too, are reshaping their narrative around agentic AI, often using the term “Digital Workers” for their bots evolving with AI capabilities. Blue Prism explicitly differentiates Generative AI vs Agentic AI, mirroring UiPath’s messaging that generative AI creates content while agentic AI takes action towards a goal. The company speaks of an “Agentic Enterprise” and positions their solution as “governed, enterprise-level intelligent automation that combines AI with agentic orchestration, process mining, and other tech”. In practice, Blue Prism is integrating with partners for AI (they have connections with AWS, Google, and others for AI services) and emphasizing strong governance (they have an AI Ethics and Governance framework, akin to UiPath’s Trust Layer focus). They have published guides on “Path to Agentic AI”, indicating thought leadership, and cite stats like 29% of business leaders are starting to leverage agentic AI - showing market interest.
However, in terms of ready product offerings, Blue Prism’s capabilities are perceived as a bit behind the curve. They were late to adopt cloud and lagged on built-in AI features (relying more on third-party AI via API). Now, under SS&C, they have resources to invest; however, enterprises evaluating agentic AI today will find UiPath’s tools more mature and immediately usable. Blue Prism may appeal to companies already using RPA who want to gradually extend it with AI, especially in highly regulated industries where SS&C has domain expertise. They have case studies of deploying thousands of “agents” (which might refer to their bots) in operations. But as of 2025, UiPath and AA appear to have more concrete agentic AI toolsets. Blue Prism’s strategy leans on its process orchestration strengths and promises of an “autonomous digital workforce”. The competitor landscape could shift as Blue Prism rolls out its next-gen platform (they mention a “Next Generation” cloud-native platform). For now, UiPath holds a lead in delivering a unified, agent-based automation platform that has already proven itself in the field.
In summary, Microsoft, Automation Anywhere, and Blue Prism all recognize the importance of agentic AI and are integrating AI agents into their automation visions. Microsoft leverages its massive user base and AI research might, AA focuses on an AI-assisted RPA experience with Co-Pilot, and Blue Prism doubles down on orchestrating AI with governance. Yet, UiPath’s positioning is relatively unique: it combines the best of RPA (robotic precision) with the best of AI (autonomy and learning) on a single platform, and it has made notable moves (like the Microsoft partnership and open LangChain integration) to avoid isolation. For enterprise buyers, this means UiPath can fit into a heterogeneous environment and even enhance other investments (like using UiPath to orchestrate Power Automate or other agents). The competitor offerings are compelling in their own right, but UiPath’s agentic AI suite currently stands out for its completeness and emphasis on end-to-end automation rather than just task or assistant-level AI.
Conclusion: Takeaways for Enterprise Leaders
UiPath’s Agentic AI platform represents the next evolution of enterprise automation - where autonomous AI agents collaborate with robots and people to drive complex processes, boost productivity, and unlock new business value. From tools like Maestro and Agent Builder to governance through the AI Trust Layer, UiPath provides a robust and scalable environment for building, deploying, and managing intelligent automation across the organization.
Want to explore the UiPath Agentic offer further? Get in touch with us.
We’re a certified UiPath partner with deep expertise in automation strategy, AI agent deployment, and end-to-end process transformation. Whether you’re just starting with automation or ready to scale agentic AI across departments, we can help you design and implement the right solution for your business. Let’s build the future of intelligent workflows together.
