UiPath announces features to streamline automation with Autopilot and GenAI

time lapse photo of a city | automation and GenAI speed concept

Key Takeaways

UiPath has launched UiPath Autopilot, integrating GenAI and NLP to enhance the automation capabilities within its Business Automation Platform, aiming for improved user experience and better automation outcomes.

The new features of UiPath Autopilot, including text-to-workflow and text-to-code functionalities, have achieved over a 70% acceptance rate, making automation easier for less experienced developers and streamlining the development process.

UiPath has announced a collaboration with Microsoft to integrate with Microsoft 365, enabling users to automate business processes directly within Teams, and will also provide UiPath Automation Cloud on Microsoft Azure in the UK to meet local data residency demands.

UiPath, a global provider of RPA software, has announced new features, including the release of UiPath Autopilot which infuses GenAI into the UiPath Business Automation Platform to help businesses achieve better automation outcomes. 

Having specialized in robotic process automation (RPA) for decades, UiPath is now opening doors to AI to enhance user experience within its automation capabilities.

Showcased at UiPath on Tour: AI at Work summit in London, UiPath Autopilot for developers uses the power of GenAI and natural language processing (NLP) in UiPath Studio to create workflows, generate expressions and help build automations. 

So far, the solution received over 70 percent acceptance rate, making operations processes easier for less experienced developers and speeding up scaffolding for them. 

Among the features that Autopilot delivers are text-to-workflow, text-to-expressions, text-to-code and PDF form, text or image-to-UiPath apps. 

On the other hand, UiPath Autopilot for testers accelerates every aspect of software testing by leveraging GenAI to refine and improve requirements, generates step-by-step tests from those requirements and uses those tests to create coded automations. Among its specific features, it provides quality checks, test design, test automation and test insights.

Additionally, UiPath announced a plugin and integration with Copilot for Microsoft 365, now in preview. The integration will enable joint customers to automate end-to-end business processes with co-workers directly within Microsoft Teams. Customers will have access to a prebuilt automation library to run automations that complete common, repetitive tasks, along with specialized automations for function- or industry-specific tasks. Users can also discover and run automations their company has developed.

In collaboration with Microsoft, UiPath will also release the general availability of UiPath Automation Cloud on Microsoft Azure in the UK, driven by high customer demand for local data residency and a growing need for AI and automation from UiPath. 

UiPath emphasized that the expansion will enable public sector organizations, as well as customers in a wide range of industries such as financial services, healthcare and telecommunications, to better comply with regulations linked to handling sensitive customer data.

Among other announcements at UiPath On Tour London, the company released new AI enhancements for intelligent document processing (IDP) capabilities, including UiPath DocPath and CommPath, active learning and Generative validation, as well as AI-powered building blocks, GenAI activities, which is a curated collection of activities that simplify common GenAI use cases for automation developers.

The users will also be able to access Intelligent UI form-handling capabilities to accelerate development and reduce maintenance as they will deal with a form as a single entity, rather than a collection of individual fields. 

The news reflects UiPath’s commitment to the development and enhancement of its AI capabilities, as was already presented at its virtual AI Summit this spring to aid enterprises with the full potential of AI with automation – by accessing specialized AI models tailored to their challenges and use cases.