What’s the next big thing in business automation? If you ask the tech giants, they are agents, driven by generative AI.
There is no universally accepted definition of agentbut nowadays the term is used to describe generative AI-based tools that can perform complex tasks through human-like interactions on software and web platforms.
For example, an agent could create an itinerary by filling out a customer’s information on airline and hotel chain websites. An agent could also order the cheapest rideshare service to a location by automatically comparing prices between apps.
Sellers sense opportunity. ChatGPT creator OpenAI is reportedly developing AI agent systems. And Google showed off a slew of agent-like products at its annual Cloud Next conference in early April.
“Businesses should start preparing for widespread adoption of autonomous agents today,” analysts at the Boston Consulting Group recently wrote in a report, citing experts who believe autonomous agents will become more widespread. here three to five years.
Old-fashioned automation
So, what about RPA?
Robotic process automation (RPA) became trendy more than a decade ago as companies turned to the technology to bolster their digital transformation efforts while reducing costs. Like an agent, RPA drives workflow automation. But it is a much more rigid form, based on predefined “if-then” rules for processes that can be broken down into strictly defined and discretized steps.
“RPA can mimic human actions, such as clicking, tapping, or copy-pasting, to perform tasks faster and more accurately than humans,” Saikat Ray, vice president analyst at Gartner, told TechCrunch in an interview. “However, RPA bots have limitations when it comes to handling complex, creative, or dynamic tasks that require natural language processing or reasoning skills. »
This rigidity makes RPA expensive to build and significantly limits its applicability.
A 2022 survey by Robocorp, an RPA vendor, reveals that among organizations that say they have adopted RPA, 69% experience interrupted automation workflows at least once a week, many of which take hours to repair . Entire companies have been created to help businesses 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 could solve many of them without precipitating the demise of their platforms. In the minds of RPA vendors, RPA and generative AI-based agents can coexist peacefully – and perhaps one day even complement each other to complement each other.
Generative AI Automation
UiPath, one of the largest players in the RPA market with over 10,000 customers including Uber, Xerox and CrowdStrike, recently announced new generative AI capabilities focused on document and message processing, as well as taking of automated actions to deliver what Bob, CEO of UiPath, announced. Enslin calls it “one-click digital transformation.”
“These capabilities provide customers with generative AI models trained for their specific tasks,” Enslin told TechCrunch. “Our generative AI powers workloads such as text completion for emails, categorization, image detection, language translation, the ability to filter personally identifiable information (and) respond quickly to all people-related questions based on internal data insights.
One of UiPath’s most recent explorations into generative AI is Clipboard AI, which combines UiPath’s platform with third-party models from OpenAI, Google and others to, as stated Enslin, “bring the power of automation to anyone who needs to copy/paste.” Clipboard AI allows users to highlight data on a form and, leveraging generative AI to determine the right places to place the copied data, to direct it to another form, another application, a spreadsheet or a database.
Image credits: 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 – across end-to-end processes. »
Automation Anywhere, UiPath’s main rival, is also trying to integrate generative AI into its RPA technologies.
Last year, Automation Anywhere launched AI-powered generative tools to create workflows from natural language, summarize content, extract data from documents, and, perhaps most importantly, scale to changes in applications that would normally cause RPA automation to fail.
“(Our generative AI models are) built on large (open) language models and trained with anonymized metadata from over 150 million automation processes in thousands of enterprise applications,” Peter White , senior vice president 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 custom models on top of foundational generative AI models using our data sets. automating.
Next-generation RPA
Ray notes that it is important to be aware of the limitations of generative AI, namely biases and hallucinations, as it powers a growing number of RPA capabilities. But, risks aside, he believes generative AI has the potential to add value to RPA by transforming how these platforms work and “creating new possibilities for automation.”
“Generative AI is a powerful technology that can enhance the capabilities of RPA platforms by allowing them to understand and generate natural language, automate content creation, improve decision-making, and even generate code “Ray said. “By integrating generative AI models, RPA platforms can deliver more value to their customers, increase their productivity and efficiency, and expand their use cases and applications. »
Craig Le Clair, principal analyst at Forrester, believes that RPA platforms are ready to be expanded to support autonomous agents and generative AI as their use cases develop. In fact, he expects RPA platforms to evolve into comprehensive toolsets for automation – toolsets that help deploy RPA in addition to associated generative AI technologies.
“RPA platforms have the architecture to handle thousands of task automations, which bodes well for centralized management of AI agents,” he said. “Thousands of companies have well-established RPA platforms and will be willing to use them for AI-based generative agents. RPA has grown in part because of its ability to easily integrate with existing work models, through user interface integration, and this will continue to be valuable for smarter agents in the future.
UiPath is already starting to take steps in this direction with a new feature, Context Grounding, entering preview earlier this month. As Enslin explained to me, Context Grounding is designed to improve the accuracy of generative AI models – whether first-party or third-party – by converting the business data those models might rely on into an “optimized” format. easier to index and search.
“Context Grounding extracts information from company-specific data sets, such as a knowledge base or internal policies and procedures, to create more precise and insightful answers,” Enslin said.
If there’s anything holding RPA vendors back, it’s the ever-present temptation to lock in customers, Le Clair said. He highlighted the need for platforms to “remain agnostic” and offer tools that can be configured to work with a range of current – and future – business systems and workflows.
To this, Enslin promised that UiPath would remain “open, flexible and accountable.”
“The future of AI will require a combination of specialized AI and generative AI,” he continued. “We want our customers to be able to confidently use all kinds of AI. »
White didn’t exactly commit to neutrality. But he emphasized that Automation Anywhere’s roadmap is heavily influenced by customer feedback.
“What all customers, across all industries, are telling us is that their ability to integrate automation into many other use cases has increased exponentially thanks to generative AI,” he said. he declares. “Through the integration 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 with those that embrace generative AI and automation.
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