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How RPA vendors aim to remain relevant in a world of AI agents | TechCrunch

What’s the next big thing in enterprise automation? If you ask the tech giants, these are agents – powered by generic AI.

There is no universally accepted definition RepresentativeBut nowadays the term is used to describe generative AI-powered tools that can perform complex tasks through human-like interactions across software and web platforms.

For example, an agent can create an itinerary by filling in customer information on the websites of airlines and hotel chains. Or an agent can order the least expensive ride-hailing service for a location by automatically comparing prices across apps.

Sellers sense an opportunity. ChatGPT creator is OpenAI Allegedly In-depth into developing AI agent systems. And Google demonstrated several agent-like products at its annual Cloud Next conference in early April.

“Companies should start preparing for the wide-scale adoption of autonomous agents today,” analysts at Boston Consulting Group wrote in a recent article. report Citing experts, it has been estimated that autonomous agents will become mainstream in three to five years.

old school automation

So where does that leave RPA?

Robotic process automation (RPA) came into vogue a decade ago as enterprises turned to the technology to boost their digital transformation efforts while reducing costs. Like an agent, RPA drives workflow automation. But this is a much more rigid form, based on predetermined “if-then” rules for processes that can be broken down into strictly defined, discretionary steps.

“RPA can mimic human actions like clicking, typing, or copying and pasting to perform tasks faster and more accurately than humans,” Saikat Ray, VP analyst at Gartner, told TechCrunch in an interview. Is.” “However, when it comes to handling complex, creative or dynamic tasks that require natural language processing or reasoning skills, RPA bots have limitations.”

This rigidity makes RPA expensive to build – and significantly limits its applicability.

one 2022 survey RoboCorp, an RPA vendor, found that 69% of organizations that say they have adopted RPA experience a broken automation workflow at least once a week – many of which take hours to fix. Let’s go. whole business Designed to help enterprises manage their RPA installations and prevent them from breaking down.

RPA vendors are not naive. They are well aware of the challenges – and believe that generative AI can solve many of them without dismantling their platform. In the minds of RPA vendors, RPA and generative AI-powered agents can peacefully co-exist – and perhaps one day even complement each other.

Generative AI Automation

UiPath, one of the larger players in the RPA market with an estimated 10,000+ customers including Uber, Xerox and CrowdStrike, recently announced new generative AI features focused on document and message processing, as well as delivering UiPath CEO Bob Automated action has also been taken to do so. Enslin calls “one-click digital transformation.”

“These features provide customers with generative AI models that are trained for their specific tasks,” Enslin told TechCrunch. “Our generic AI powers workloads like text completion for email, classification, image detection, language translation, the ability to filter out personally identifiable information. [and] “Instantly answering any person-subject-related question based on knowledge derived from internal data.”

One of UiPath’s recent explorations in the generative AI domain is Clipboard AI, which combines UiPath’s platform with third-party models from OpenAI, Google, and others to – as Enslin says – “power automation to anyone Bring what you want to copy/paste.” Clipboard AI lets users highlight data from a form, and leverages generative AI to find the right locations for the copied data – pointing it to another form, app, spreadsheet, or database.

Image Credit: UiPath

“UiPath sees the need to bring action and AI together; That’s where the value is created,” Enslin said. “We believe the best performance will come from those that combine generative AI and human judgment – ​​what we call human-in-the-loop – in end-to-end processes.”

Automation Anywhere, UiPath’s main competitor, is also attempting to incorporate generative AI into its RPA technologies.

Last year, Automation Anywhere launched generic AI-powered tools for creating workflows from natural language, summarizing content, extracting data from documents, and — perhaps most importantly — optimizing changes in apps that typically involve RPA automation. Will cause failure.

,[Our generative AI models are] developed on top of [open] Trained with large language models and anonymized metadata from more than 150 million automation processes across thousands of enterprise applications, Peter White, SVP of enterprise AI and automation at Automation Anywhere, told TechCrunch. “We continue to build custom machine learning models for specific tasks within our platform and are now also building customized models on top of basic generative AI models using our automation datasets.”

Next Generation RPA

Ray says it’s important to be aware of the limitations of generative AI – namely biases and nightmare – Because it powers a growing number of RPA capabilities. But, risks aside, he believes generative AI is capable of adding value to RPA by changing the way these platforms work and “creating new possibilities for automation.”

“Generative AI is a powerful technology that can enhance the capabilities of RPA platforms enabling them to understand and generate natural language, automate content creation, improve decision making, and even generate code Makes,” Ray said. “By integrating generative AI models, RPA platforms can deliver greater value to their customers, increase their productivity and efficiency, and expand their use cases and applications.”

Craig LeClair, principal analyst at Forrester, believes RPA platforms are ripe for expansion Help As their use cases grow, autonomous agents and generative AI. In fact, he predicts that RPA platforms will turn into an all-around toolset for automation – toolsets that help deploy RPA in addition to related generative AI technologies.

“RPA platforms have the architecture to manage thousands of task automations and this bodes well for centralized management of AI agents,” he said. “Thousands of companies are well established with RPA platforms and would be open to using them for generic AI-infused agents. RPA has evolved in part due to its ability to easily integrate with existing work patterns through UI integration, and this will continue to be valuable for more intelligent agents going forward.

UiPath is already starting to take steps in this direction with a new capability, Context Grounding, which entered preview at the beginning of the month. As Enslin explained to me, Context Grounding is designed to improve the accuracy of generative AI models – both first and third-party – by converting business data so those models can be generated into an “optimized” format. Which is easy to index and search.

“Context grounding extracts information from company-specific datasets, such as knowledge bases or internal policies and procedures, to create more accurate and practical responses,” Enslin said.

If there’s one thing holding RPA vendors back, LeClair said, it’s the ever-present temptation to retain customers. He stressed the need for platforms to “remain agnostic” and offer tools that can be configured to work with a range of current – ​​and future – enterprise systems and workflows.

To this end, Enslin pledged that UiPath will remain “open, flexible, and responsible.”

He added, “The future of AI will require a combination of specialized AI with generic AI.” “We want customers to be able to use all types of AI with confidence.”

White was not committed to neutrality at all. But he stressed that the Automation Anywhere roadmap is being largely influenced by customer feedback.

“What we hear from every customer, across every industry, is that their ability to incorporate automation into many more use cases with generic AI has grown exponentially,” he said. “With the incorporation of generative AI into intelligent automation technologies like RPA, we see the potential for organizations to reduce operating costs and increase productivity. “Companies that fail to adopt these technologies will struggle to compete against other companies that embrace generative AI and automation.”

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