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AI-Powered Automation at UiPath’s Forward VI

Home » Digital Transformation » Intelligent Automation & RPA » AI-Powered Automation at UiPath’s Forward VI

Author

Eduardo Diquez

Managing Director of Intelligent Automation

AI-powered automation was  the central theme of UiPath’s Forward VI conference, held in Las Vegas from October 9-12. Auxis, as one of the sponsors, joined more than 3,000 automation professionals at the conference geared towards showcasing ‘AI at work.’ 

Generative AI exploded into popular imagination in recent months, thanks to the unprecedented popularity of Open AI’s ChatGPT. With a number of major technology providers jumping onto the Gen AI bandwagon, enterprise adoption of the technology seems imminent.  

Yet, excitement about the potential of the technology has been mixed with skepticism as well as the fear of being left behind or disrupted by more AI-forward competitors. Hence it was no surprise that at this year’s conference, the intense pressure to have an AI strategy in place for your organization was one of the most discussed topics among the attendees.

It is in this context that UiPath’s innovative approach to combine Generative AI with intelligent automation, and the first glimpses of what that could do, made the event a must attend for anyone considering adopting Generative AI for their business. “AI without automation is like having a brain without a body,” UiPath’s Chief Product Officer Graham Sheldon said in his keynote address. “You need to be able to take action from the decisions that AI helps you make.”  

AI-Integrated Automation: A Potential Path Breaker for RPA 

UiPath announced Autopilot, an artificial intelligence companion that blends the best of Generative AI and Specialized AI to work with a wide variety of systems and documents. This includes discovering and running existing automations from your company, stringing automations together to accomplish advanced actions, and even creating AI-powered automations by itself. 

While still in the early stages, the announcement of this capability greatly expands the scope of what can be automated. As a UiPath Gold Partner, we believe this has major implications for Robotic Process Automation and the quality of service we can deliver to our clients. Today, developers spend a lot of time fixing bot failures for reasons as simple as the addition of a new column to a spreadsheet the bot was pulling data from. With Generative AI embedded into the technology, a stuck or failed bot can potentially detect issues and take steps to “heal” itself. Bots imbued with AI self-healing capabilities would exponentially increase the value of RPA solutions, while freeing up developers to focus on more complex tasks and strategic work.

Generative AI also frees RPA from its complete reliance on well-defined rules to operate effectively, expanding its scope to include processes that do not or cannot have pre-defined rules and instead leveraging Gen AI for decision making. 

This is just the first of many use cases for AI-integrated automation for business operations. In a research report released concurrently with the event, UiPath found that 70% of respondents considered AI-driven automation adoption to be either “very important” or “critical” for the future of their industry, with 45% expecting it to catalyze a major transformation in their industry within the next few years.  

Active learning and AI-powered Intelligent Document Processing 

UiPath is also shaking up Intelligent Document Processing as we know it. Incorporating GPT-based technologies to improve classification and pre-labeling has speeded up UiPath’s model training process, allowing for faster deployment and faster time-to-value. 

Now, with active learning, training UiPath’s Intelligent Document Processing solution is “almost like a conversation between two colleagues,” as Sheldon described it. The active learning capability enables anyone, even those with no machine learning, natural language processing, or coding skills, to train Specialized AI models for data processing and actions for specific domains and document types. 

For Auxis, UiPath’s active learning capability for Intelligent Document Processing and the Gen AI-integrated Autopilot together represent a giant leap forward for democratizing automation development. We believe it could lead the way for the citizen developer model to become truly successful. While widely evangelized within large organizations, citizen developer programs have till now been hindered due to insufficient training and hands-on experience, lack of compliance with security safeguards and data governance mandates, absence of a robust QA process, etc.  

Enabling aspiring citizen developers with AI-driven solutions that can do the technical heavy lifting could be extremely valuable and accelerate citizen developer programs, delivering multiple benefits to businesses such as higher revenue, reduced expenses, and improved work quality. 

Generative AI: Opportunities and Risks 

While automation technologies have been around for the last few decades, they have still not been able to deliver fully on the anticipated benefits and outcomes for several reasons, including lack of internal skills and resources, complex legacy environments, scaling and deployment challenges.

The Secret to Scaling Your UiPath Hyperautomation Journey

UiPath successfully demonstrated at Forward VI that Generative AI, while still nascent, has the potential to significantly enhance automation technologies and dramatically improve their outcomes. This is possible because Generative AI removes several restrictions that these automated systems have had to work with till now, for example, RPA’s need for well-defined rules, requiring developers to fix broken bots, etc.

As mentioned earlier, it also democratizes these technologies, allowing non-traditional users to create and deploy automations successfully. Additionally, it can also help enhance scalability, enable advanced cognitive automation, and facilitate real-time learning and adaptation.

However, while rife with opportunity, Generative AI also needs to be examined from a risk perspective before organizations go all in. Below are some considerations to keep in mind: 

1. Data privacy and security:  

Concerns are already mounting around data privacy in Generative AI and misuse of data for training LLMs (large language models). Organizations need to set their own policies around data security, access control, and the ability to track and understand what interactions are taking place with third-party LLMs. 

2. The need for right governance:  

Generative AI introduces new complexities, requiring robust governance to mitigate potential risks effectively. This involves defining roles and responsibilities for stakeholders involved in its development and use, with the ability to check, validate, and if necessary, override AI decisions to ensure ethical and responsible practices.

3. Security Vulnerabilities:  

Implementing Generative AI introduces new security risks, as the technology may be susceptible to adversarial attacks or unauthorized access, potentially leading to data breaches or misuse of sensitive information. 

4. Skills Gap and Training Needs:  

Implementing Generative AI requires a skilled workforce capable of understanding and managing technology. A lack of expertise and training may result in suboptimal utilization and potential errors. 

Considering Generative AI? 

Any organization considering implementing Generative AI needs to keep trust, transparency, and control at the center of their strategy. As UiPath evolves to make AI-powered automation more mainstream, Auxis is leveraging our expertise as an experienced automation partner to ensure our clients get the most cutting-edge technology, skilled resources, and support for their automation journey while ensuring the security and integrity of their data.  

Written by

Eduardo Diquez
Managing Director of Intelligent Automation
Eduardo is the Consulting Director of the Intelligent Automation Practice at Auxis, including the ongoing management of its IA Center of Excellence in Costa Rica. With over 10 years of experience in process improvement and finance transformation, Eduardo has a proven track record working with C-level executives in the design and implementation of back office optimization initiatives, with a deep focus on delivering long-term, scalable Automation Programs. Eduardo has successfully delivered over 200 robots to more than 30 different organizations across multiple industries including retail, financial services, hospitality, healthcare, and manufacturing.

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