UiPath’s FUSION 2025 event marked a pivot for the company to agentic automation. Formerly known as Forward, the event has been rebranded FUSION to underscore UiPath’s vision for integration — the fusion of agents, robots, and humans, all orchestrated in a single unified platform. In effect, the previously launched Maestro steps up as the master orchestrator, handling not just classical RPA, but also AI agents and human interaction as part of agentic automation.

How UiPath is addressing the agentic AI challenge

UiPath acknowledges that building agentic systems is inherently difficult. It requires domain knowledge, systems integration, automation engineering, and governance from day one. To address this, the company is investing in a library of prebuilt agentic solutions aimed at accelerating time-to-value and reducing complexity for customers.

These prebuilt solutions are not automation templates or components to automate a task; each solution includes:

• AI agents trained on domain-specific reasoning tasks
• Robots to execute structured, repetitive workflows
• Human-in-the-loop mechanisms for oversight, approvals, and judgment
• Apps and dashboards tailored to business roles and operations
• Embedded governance for auditability and policy compliance.

Maestro plays a central role: it governs the handoffs between agents, robots, and humans; tracks progress through cases or workflows; and maintains end-to-end traceability (including the actions of AI agents) to ensure audit‑ready compliance.

As part of the announcement, UiPath launched eight prebuilt solutions:

• Consumer Loans: automates document validation and onboarding for home equity lending, reducing cycle times and manual input
• Commercial Loans: supports loan QA with robotic document reviews and agent-based exception handling
• Financial Crime Compliance: as above, orchestrates fraud detection with agents, robots, and human review
• Healthcare Claims & Denials: automates intake, denial prediction, and appeals generation, improving speed and compliance
• Order Management: aombines agents and robots to manage supply chain exceptions and fulfillment
• Inventory Management: optimizes stock handling with demand forecasting agents and robotic transactions
• Commercial Pricing: Uses AI agents to optimize pricing strategies, with human sign-off through tailored dashboards
• Merchandising & Promotions: supports campaign rollout through agent-driven planning and robotic execution.

Maestro delivering results

UiPath has indicated it aims for 95% agent accuracy as a benchmark and reports mid‑90% accuracies so far across the published solutions. The company stated that the human-in-the-loop nature of these solutions ensures that even inaccurate model choices are given to a human for review before they are acted upon and that, as models improve, so should the accuracy. We do wonder, however, about the complacency of humans reviewing data from models that is this accurate, which may make human operators less observant of errors.  

UiPath will continue to build solutions and additionally intends to support partner solutions through a marketplace. Importantly, UiPath intends to vet the agentic solutions added by partners so that there will not be too many agentic solutions covering the same problem statement.

Another message throughout FUSION was that agentic solutions built using Maestro will improve over time as the underlying agent models improve, and that organizations should be looking to implement these solutions and expand scope and improve accuracy over time; in one such example, Capgemini spoke of an internal query resolution solution, developed using Maestro, with which it targeted the top nine queries it received and automated 90% of the workflow. Following that success, the company is expanding the use across different segments, including HR and finance.

Organizations such as Allegis spoke at the event about how this shift to agentic automation hardened its previous automation efforts, which, due to their brittle nature, only delivered ~40% efficiency; this increased to 70% through the use of Maestro.

Agentic AI platform enhancements

UiPath also unveiled several platform-level enhancements to support agentic automation. One of the most interesting was ScreenPlay.

ScreenPlay is a new capability enabling users to describe UI automation needs in natural language. ScreenPlay then translates descriptions into executable UI interactions; for example, users can request a bot to extract information from a website, then the bot will use the LLM to read the website, identify where the information is, and extract it for a variable.

The users requests are transformed into actions using one of the LLMs offered through the platform such as ChatGPT, Google Gemini, and Anthropic, and UiPath intends to support organizations in a bring-your-own-model capability.

ScreenPlay aims to enable users to make more stable bots as the elements are not coded into the bot and therefore are less brittle should an application or a website change its UI. Even with additional unit costs, and being slower to identify objects than selectors, ScreenPlay could be a nice fit in processes that are brittle due to UI changes, and should result in less development and maintenance time spent by automation developers.

UiPath also launched UiPath Labs, a set of experiments and capabilities previews. The labs launched with three tools for users to begin experimenting with and providing feedback:

• Agent Sandbox: a low-code playground for building and testing agents. Consider it “Autopilot for Studio”
• Project Delegate: a personal agent that learns repetitive tasks and executes them, positioned as “Autopilot for everyone”
• Enterprise Knowledge Graph: a feature that connects and maps an enterprise's data to provide context for its AI agents. By understanding the relationships within an organization's data, the knowledge graph allows UiPath agents to provide more accurate and context-aware responses and actions. 

Similar to ScreenPlay, Agent Sandbox and Project Delegate aim to use LLMs to create automations – for automation developers automating processes and end users automating tasks, respectively.

The Enterprise Knowledge Graph is now available for preview, and the Project Delegate and Agent Sandbox will be available soon.

We hope that Project Delegate and Agent Sandbox can fulfil the earlier promises of Autopilot for Studio and Autopilot for Assistant (later renamed Autopilot for Everyone), which also aimed to support users in creating bots through natural language. These did reduce some development efforts but often left extensive last-mile work for developers, such as creating variables to be used in the task. We were told that Project Delegate and Agent Sandbox take these operations a step further, hopefully once again reducing the energy spent developing new automations.

Summary

All in all, the FUSION event highlighted that UiPath is elevating its game using GenAI: going from automation in a BPM orchestrator that combines agents, humans, and automation, and hopefully from semi-manual automation design.

This levelling up is demonstrated by the solutions and the intention to develop a solution marketplace – a levelling up from the company's marketplace of prebuilt RPA content, which covered a much smaller percentage of end-to-end processes.

Having UiPath at the center of these agentic processes as their orchestrator is a smart fit. UiPath founder Daniel Dines was clear in his keynote: many enterprise GenAI initiatives are failing because they lack integrated automation, and a tendency to deploy GenAI in narrow, standalone use cases results in low ROI. This is similar to what we see at NelsonHall, with our research showing that a proportion of GenAI projects require upfront services to ensure data readiness. Processes that have already adopted RPA automation will already have a level of readiness. Organizations and processes with some RPA deployment are more likely to have this data readiness, and platforms such as UiPath Maestro can support the case management and auditability of processes that GenAI solutions cannot do alone.