 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. UI Pass' recent earnings, beat and raise provide some evidence that thus far anyway, GenAI has not been a negative for the company. As an early leader that is transforming beyond RPA toward end-to-end enterprise automation, UI Pass, like all automation providers, has always faced adoption headwinds beyond isolated deployments. In this sense, GenAI should bolster adoption and be a positive force. The flip side is that widely available tools like chatbots and generalized foundation models could eat away at the low end of the automation tam, highlighting the urgency for companies like UIPath to move upmarket and accelerate innovation that brings differentiation from commoditized tools and importantly creates distance from embedded AI within mainstream enterprise SaaS platforms such as Slack, GPT and Salesforce, Einstein. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we briefly review the recent earnings print from UIPath. We'll look at ETR survey data that shows Microsoft Power Automate's impact on the market and how it's forcing UIPath to target larger accounts with a more functional product set. As well, we'll look at the impact that AI is having within these larger accounts and tests UIPath management's assertions that GenAI will be a benefit for the company. First, the numbers. So this cool chart from the Motley Fool, it lays out the key metrics for UIPath's second quarter. We've pulled out some of the pluses and minuses on the upper right-hand side there. ARR of 1.3 billion beats expectations. It grew 25% year on year. Very importantly, the million dollar plus ARR accounts grew 30%. We've double starred that metric because we're going to come back and show some data that is an indicator of performance in those accounts and how important it is. Operating margin and cash flow looking good and UIPath announced a $500 million share buyback at least approved $500 million share buyback which presumably is an indication that the company sees its stock as undervalued. Although it's also a good way to prop up value. So while we see it as a positive here, only time will tell if this move will return results better than other capital allocation alternatives. On the negative side, new logos were soft and total bookings only grew in the mid-single digits. I think 5%, despite UIPath's 20% outlook for revenue growth this fiscal year. So mixed results but definitely more positives than negatives in the quarter, which is why the stock is up as of midday Friday by around 12% since its earnings release on Wednesday after the close. So we like the consistency, the cost discipline and the potentially better operating leverage that we're now seeing from UIPath. These are all the positives. Now let's take a look at some of the ETR spending data throughout last year. We saw a continued deceleration in the spending momentum around UIPath's platform as this chart shows. But relative to last October, we're seeing a rebound in UIPath's net score or again, spending momentum. That's that blue line that pops up after October. The chart shows the net score granularity for UIPath. So starting with the lime green at 9%. That represents the percentage of the 169 UIPath customers in the ETR survey this last quarter that represents new ads, new logos for the company. The forest green, which is at 38% is the percent of customers spending 6% or more on UIPath relative to last year. The gray area, which has been growing is flat spending plus or minus 5%. The pinkish is spending down by 6% or worse. That's only 3%. And the red at 4% is churn or defections. You subtract the red from the green and you get a net score of 41.4%, which is shown at that blue line. Now that brown line represents the pervasiveness of UIPath in the survey. And it's derived by dividing the UIPath N of 169 by the total survey N, which is more than 1700. And it's been declining steadily since mid-2021 when the tech market started to tighten and budgets started to shift toward things like security and other initiatives as we exited the isolation economy, refresh of the headquarters, et cetera. And I would say this was a function of both market forces and UIPath go-to-market execution, which new CEO or co-CEO Rob Enslin has been addressing with the company's so-called North Star selling framework. And based on last quarter's results, we're seeing some positive effects of Enslin's influence. And while co-founder Daniel Deniz is focusing more on product, he's also got a big emphasis on AI and we'll talk about the importance of that, which if it's not obvious, we'll show some data as to why. Now, as we said at the top, Power Automate from Microsoft has had a major impact on the market. This chart plots the leaders within the ETR dataset for the automation sector. The vertical axis is net score, remember that's spending momentum and the horizontal axis is the overall accounts which is representative of the ends. It's the penetration in the survey. You can see both the net score and the shared end counts on the table that we've inserted over to the right. Note that we've also added a dotted red line at 40%. That's an indicator of a highly elevated spending velocity. Now there's no denying that Microsoft with its end of 290 and a 64% net score has a very strong position. But it's important to point out that the ETR data measures accounts, a number of accounts, not actual spending levels and much of the Microsoft activity is small dollars that maybe adds up at scale. We've also highlighted UiPath's end here at 169. Only Automation Anywhere has more than 100 end in this last survey and you can see the position of the other players. UiPath continues to stand out but as we said, when Microsoft acquired Softomotive to create Power Automate, we said they were going to have a big presence in the market and force UiPath to go upmarket, which it has done through acquisition and organic R&D to dramatically expand its portfolio with things like process mining, task mining, communications mining and significant AI functionality, which is of course a big emphasis today. Okay, staying on this slide for a moment, take a good look at the positions. In particular, look at UiPath and Microsoft. Now, watch what happens when we tap the power of the UiPath platform and cut the data by 140 AI accounts and isolate the data to the global 2000 customers in the dataset. Look at how different this relative picture is. First, the numbers naturally get smaller because we're slicing the salami by global 2000 and by AI accounts. But UiPath's end ties that of Power Automate and its net score jumps from 41.4% overall to about 55% within the global 2000. So meaningful jump. Microsoft's net score jumps too, not as much, but so does Pegas. But look at automation anywhere. It drops quite dramatically to 19%. It was 30% on the previous chart. Blue Prism drops as well. Now, again, these are smaller ends, but we think that they're meaningful and are perhaps an indicator of which automation firms have the greatest AI affinity and potential. And the relative parity between UiPath and Microsoft in this cut is a positive data point in our view. And it also brings us back to that double star callout that we mentioned earlier, where a million dollar plus ARR accounts are critical to UiPath's future. And this data supports both the importance and performance of these accounts to UiPath, not necessarily that every global 2000 is a one-to-one map to a million dollar plus account, but it stands to reason that the larger global 2000 accounts are better candidates for that type of spending. Now, it's no secret that some folks see AI as a potential negative disruptor to firms like UiPath. In our breaking analysis last March, we said GPT models are a two-edged sword for automation platforms like UiPath, and we still feel that way. UiPath Studio was designed to simplify adoption for a wider audience, but AI has much greater potential to achieve this objective, in our opinion. UiPath announced that its Wingman project is now in private preview, which we think is a major milestone. Project Wingman brings gen AI together with computer vision to understand computer screen content, and it uses natural language processing prompts to create automation. So talk to the system and get what you want. So this could be an enormous game changer for UiPath, and it could give the company one, a leg up on the competition, and two, much broader and deeper adoption of its platform. And three, it could be an accelerant to revenue growth. Now, whether it can be a meaningful TAM expander, that remains to be seen, but it's a trend that we're following and watching closely. This is in part why company co-founder and original CEO, Daniel Dinez, spent so much time on the earnings call on this topic. And it was the number one topic of interest among the financial analysts in the Q&A segment. Here are three statements Dinez made on the call. One, to be effective, generative AI needs context, which our software robots can deliver by gathering information from across the enterprise and data documents, CRM, ERP and beyond. Two, it also needs our platform to take action and operationalize the promise of AI today, with an integrated set of capabilities that combines our specialized AI with generative AI. And three, looking ahead, we expect this next evolution of gen AI to be a tailwind to the business. What would you expect them to say? Helping customers create better, more resilient automations more quickly, and opening up novel use cases that facilitate the automation of even more processes. So I would say this as anyone who has done software development with generative AI would tell you, and by the way, we have done so here at Silicon Angle, go to thecubeai.com, thecubeai.com and sign up for our private beta. They will tell you that as powerful as gen AI is, it's not a no brainer to get consistent and accurate results and adjusting data of mixed quality and getting the system to take action, which Dinez was referring to earlier, and getting it to take the right action consistently is non-trivial. So this brings us back to our power law conversation. John Furrier, Rob Streche and I first introduced this past month in a breaking analysis, this idea of the power law as applied to gen AI. We use this example of the internet where web traffic both concentrates attention on a few big sites, but at the same time distributes attention across a very long, long, long tail. That orange line is what we said the web looks like today with a pretty hard right angle and a limited torso. We see the gen AI power laws similar but different. For our axes, we chose the size of model. It's the same one we used in the last power law. That's the vertical axis where the big internet giants like Google, Amazon and Microsoft, along with companies like OpenAI and other third parties will have these very large models. And on the horizontal axis, we show model specificity. IE use cases that are unique potentially in terms of activity or in terms of industry and industry specific models. So the basic premise that UI puts forth is shown in that insert comment box in the upper right there that generalized AI models will support the creation of automations, simplify and accelerate adoption. So those are real positives and we buy that by the way, but counterbalancing these factors are some negatives is the possibility that chatbots and consumer tools are going to eat away at the low end of the total available market. Moreover, calling your attention to that lower part of the torso, virtually every SaaS vendor is embedding AI and automations into their platforms, Salesforce, with Einstein, ServiceNow, Workday, Oracle, et cetera. Now, could be a partnering opportunity for UI path but most typically software companies, they want to own their entire stacks. So the point is that this presents a challenge for the likes of UI path because these SaaS platforms, they're going to cannibalize some portion of the automation time for specialized tasks like sales companions or writing code or summarizing documents. A lot of the things that, you know, RPA and automation technologies have done. So firms like UI path have to move fast. And we've tried to highlight some of your unique capabilities of specialized AI and automation platforms. Importantly, starting with governed use cases. UI path must show that it is best at things like document understanding, process mining, automation creation and computer vision, you know, specific to its markets but that it can apply it across many markets. It is tying wingman to computer vision for differentiation. You know, sales assistance with Jarvis, is it going to outgun Salesforce there? Industry specific automations. Another example where a lot of the SaaS players are strong, UI paths, strong industries are insurance, healthcare, financial services, manufacturing. But again, there's overlap with those SaaS platforms and that'll be critical to watch from an adoption perspective. Here's our thinking. UI path got out to an early lead, has a nice install base and now has over 10,000 customers although only about 20% of those are $100,000 plus ARR customers. Its advantage is that it, first of all, it can be more functional, a more functional automation system than these other SaaS players because it's a pure play, it's focusing its R and D on automation. And it is proving that from the standpoint of product excellence, it actually has a better product than some of these other platforms. Number two, it can be a horizontal platform and not as narrowly confined to a specific market segment like, for example, Workday and HR or Finance, for example. Well, SaaS companies have a tendency to expand through bolt-on acquisitions, just look at what Salesforce has done and it's been effective. But UI path can carve out a position as a pure play automation player to do so. It has to convince customers that end-to-end automation is a key requirement and ingredient of digital transformations and it has to prove that AI is unique. It's AI is unique in a value add as we showed on that horizontal axis of our power law. So we're looking for some upcoming catalysts there's potentially that are gonna be unveiled at UI path forward six, the week of October 9th in Las Vegas, we will be there reporting and analyzing as always, with theCUBE and we look forward to your feedback from that event, but specifically on this post. How do you see the market? Is AI a wind at UI passback or a disruptive force? Let us know what you think. Okay, we'll leave it there. Many thanks to Alex Meyerson who's on production and manages the podcast, Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and in our newsletters and Rob Hoef is our editor-in-chief over at siliconangle.com. Thank you all, all the wonderful work you do. Remember all these episodes are available as podcasts wherever you listen, all you got to do is search breaking analysis podcasts, publish each week on wikibon.com and siliconangle.com and you can email me at david.volante at siliconangle.com or DM me on x at dvolante or comment on my LinkedIn posts and please do check out etr.ai, etr.ai. You get the best survey data in the enterprise tech business and they're continuously investing and expanding their capabilities. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching and we'll see you next time on breaking analysis.