RPA hits an AI inflection point

Today: how business–process automation is changing thanks to generative AI, Adobe tries to thread the needle between AI serendipity and brand safety, and the latest funding rounds in enterprise tech.

RPA hits an AI inflection point
Photo by Scott Graham / Unsplash

Welcome to Runtime! Today: how business–process automation is changing thanks to generative AI, Adobe tries to thread the needle between AI serendipity and brand safety, and the latest funding rounds in enterprise tech.

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Automation for the people

Any modern enterprise is an extremely complex operation behind the scenes, which requires someone or something to coordinate the thousands of small tasks from payroll to invoicing that take place every hour. Over the last several years, enterprise software tools designed to automate those processes were seen as the answer to that problem — until the generative AI boom changed everything.

Robotic process automation (RPA) allows companies to configure software "robots" to automate mundane, rules-based tasks across applications and systems, and companies building RPA tools have received a lot of investment over the past several years. However, the technology is reaching an inflection point as enterprises increasingly look to get more than just productivity gains from their prior investments.

  • According to Forrester, the market for RPA software and services is expected to grow to $22 billion by 2025, but growth is slowing down as companies increasingly look to AI to solve these problems.
  • “RPA has proven to be a flexible and effective driver for both digital transformation and efficiency, making it a popular choice for enterprises seeking to enhance their operational capabilities," said Vijay Pandiarajan, vice president of Salesforce Automation in charge of the MuleSoft RPA product.
  • However, like many emerging enterprise technologies, RPA requires specialized skills to implement properly and can be very expensive at a time when IT managers are being asked to cut costs, said Amit Saxena, general manager and vice president of ServiceNow's Automation Engine.

RPA at first seemed like a godsend for companies that wanted to quickly modernize their legacy systems.

  • Applications built decades ago often come with very basic user interfaces designed by engineers for engineers, and RPA allowed those companies to extract crucial data from those systems and manipulate it with modern tools, Pandiarajan said.
  • RPA also helped companies streamline day-to-day operations, such as onboarding new employees, said Rudy Kuhn, lead evangelist at Celonis.
  • But in the process of solving some common business problems, RPA introduced some new business problems.
  • "Most RPA tools are not best-in-class when it comes to other capabilities such as rules engines, process modeling, and connectivity solutions," Pandiarajan said.

RPA vendors are experimenting with generative AI technologies, just like pretty much every enterprise software company.

  • "Generative AI is poised to amplify the accessibility and scalability of RPA, mitigating the predominant obstacles to entry, namely the need for specialized developers and the risk of bot failure," Saxena said.
  • Alex Astafyev, co-founder and chief business development officer at ElectroNeek, agreed that generative AI will make it much easier to use RPA technology inside companies that have their expensive software developers committed to other projects.
  • “In the near future, it is conceivable that you could ask a bot about the status of a customer's package in the fulfillment process, and the AI would understand the process and provide real-time updates," Pandiarajan said.

But experts warned that there are still a few pitfalls that buyers should keep in mind when considering introducing the technology.

  • Automating tasks might lead to faster business outcomes, but companies need to consider whether those business flows make sense to automate or if they even need to be there at all, Kuhn said.
  • "For example, if a bottleneck is identified with process mining, the first question should be whether the bottleneck can be eliminated. In my humble opinion, elimination is the best solution for challenges in processes," he said. 

Read the rest of the full report on Runtime here.

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Safety first

You're just going to have to trust me on this one: it's hard to generate interesting, relevant, and actionable content on a regular basis. That's one reason why marketing teams are really excited about the content-production capabilities of large-language models, until they remember the adage that it takes years to cultivate a brand and seconds to destroy it.

Adobe thinks it can blend the best of both worlds with GenStudio, a new enterprise marketing software tool that promises to help marketing teams increase the velocity of their content production staff through generative AI without going off the rails. "I think the opportunity for Adobe is: how do we bring [early experiments] more directly with the right security safeguards and with all the right compliance into the tools that these people are using?" Adobe's Amit Ahuja told Techcrunch.

The idea is that models trained on actual, certified brand assets will do a much better job producing usable content than models trained on publicly available data, and in-house customer data will make it easier to personalize that content. Those OKRs aren't going to hit themselves.

Enterprise funding

Foundry launched with $80 million in seed and Series A funding to build out a new type of AI cloud provider that will "ensure humanity maximizes the utility of the computing power we already have, and will produce," according to a blog post.

Eliyan raised $60 million in Series B funding for its chip interconnect designs, which could help improve computing performance as companies like Nvidia start to package chips together in larger bundles.

CyberSaint landed $21 million in Series A funding to expand its cybersecurity risk-assessment technology.

BlueFlag Security scored $11.5 million in seed funding as it builds out developer identity-management tools for tech organizations.

Binarly raised $10.5 million in seed funding to move beyond vulnerability research and help companies detect software supply-chain security problems.

Foundational landed $8 million in seed funding to help data teams maintain complex data pipelines.

The Runtime roundup

Zoom will attempt to play a more central role in productivity software with Zoom Workplace, a new software platform that integrates with Zoom meetings and provides summaries, calendar integrations, and a whiteboard.

The UXL Foundation, a consortium that hopes to erode the dominance of Nvidia's CUDA AI software, hopes to have a "mature" release ready by the end of this year, according to Reuters.

Redis contributors led by AWS's Madelyn Olson have started work on an open-source fork of the core project, after Redis announced it would switch the license for that project last week.

Dell laid off twice as many employees as it originally planned to do at the beginning of last year, according to recent corporate filings spotted by Bloomberg.\

Thanks for reading — see you Thursday!

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