In this episode of Enterprising Insights, The Futurum Group’s Enterprise Applications Research Director Keith Kirkpatrick explores the recent developments in the enterprise application space, focusing on recent earnings announcements, and their impact on the market. He’ll also delve into the issue of enterprise application usability, and then close out the show with the “Rant or Rave” segment, where Kirkpatrick picks one item in the market, and champions or criticizes it.
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Transcript:
Keith Kirkpatrick: Hello everybody, I’m Keith Kirkpatrick, Research Director with The Futurum Group, and I’d like to welcome you to Enterprising Insights, our weekly podcast that explores the latest developments in the enterprise software market and the technologies that underpin these platforms, applications, and tools. This week I want to take a few minutes to focus in on some of the key insights that we’ve learned after looking at the quarterly earnings reports from several large enterprise software vendors, including Microsoft, SAP, OpenText, Google, and ServiceNow. Next, I’ll take a look at the topic that’s often overlooked, that’s really important to enterprises, which is the user experience, and discuss how that is being impacted by artificial intelligence. When I’m talking about user experience I’m talking about enterprise workers using enterprise applications. Then as always, I’ll close out the show with the rant or rave segment where I’ll pick one item in the market and I’ll either champion it or I’ll criticize it.
So without further delay let’s talk about earnings. As everyone’s aware, this is earning season, and several large … I’m sorry, several large enterprise SaaS companies have reported earnings recently. Overall it’s been a strong quarter really marked by three things: solid revenue growth, continued strength in cloud offerings, and, of course, the contribution of artificial intelligence, particularly generative AI to revenues. So let’s dig a little deeper here and take a look at some companies. First, we have Microsoft. They reported second-quarter earnings that really outperformed most … Outperformed their analyst forecasts across several measures. They approached an overall quarterly revenue of about 62 billion which is up about 18% year over year. This was largely due to the success of their Microsoft Cloud offering which grew about 20% to 25.9 billion during the quarter.
The success of cloud, of course, we have to look at the fast adoption of Copilot. Now, Copilot, of course, that is really one of those products that Microsoft is trying to roll out across every particular application or area within the company. But they’re really seeing a lot of success in their enterprise, their E3 and E5 enterprise offerings. The company has said that some large customers: Honda, Pfizer, they’ve all actually already rolled that Copilot to their employees and are seeing real success. I think that if we look at some of the comments that were made by CEO Satya Nadella, he said that early Copilot for Microsoft 365 users, they saw that they were 29% faster completing a series of tasks including searching, writing, and summarizing. So it’s a really good sign for the market, for Microsoft in particular. But just overall, that organizations are deploying this technology and they’re actually seeing results.
If we take a look at some other things within Microsoft, from the earnest report, that perhaps are a little bit more troubling. If we look at the sales of their Dynamics 365 ERP software, the sales were up 25%. Microsoft is warning that the bookings growth was hit a little bit by weaker demand for new business, primarily in their CRM and ERP workloads. And my sense is that demand is still being impacted by a somewhat uncertain economic environment that we’re in, as well as stiff competition for other ERP vendors that are rolling out their own AI-enabled platforms. Oracle is doing it, SAP, others, and, of course, that’s creating a lot of competition. As a result, there’s less of an impetus for enterprises to switch to another platform solely based on feature sets or functionality alone. And that is certainly true across the board with really any platform.
Now, if we move to some other companies to take a look at some highlights here. Alphabet which, of course, is the parent of Google, they also had a great year in terms of generating revenue. Of course, one of the things that popped right after they announced is that the stock took a 5% dip in after-hours trading, and that was really based on the company missing analyst forecast for advertising revenue which is still sort of the company’s core business. But if we look at some of the things that really impact the enterprise application market, Google has some good news around Duet AI, that’s their AI-based assistance technology that features sort of the table stakes functionality these days. Tech summarization, organizing data, generating content, and those sorts of things. They’re saying that Duet AI is now being rolled out and used by end customers around the world, Singapore Post, Uber, Woolworths. Again, a really great sign that organizations are seeing value from that type of technology.
Let’s move to ServiceNow. ServiceNow reported its fourth quarter results. They posted I think Q4 revenue of 2.4 billion which is good for about 24% growth year over year. And for the full year of 2023, they posted a non-gap total revenue of about 8.94 billion for a year-over-year growth rate of 23.5%. So really, really strong results. Not surprised at all about that. Bill McDermott has really done a great job of guiding that company in terms of going all-in on AI. They are seeing a lot of success with its Now Platform which is really based around incorporating AI across all different types of workflows. And I think they mentioned something really interesting on the conference call. In Q4 they had customer workflows crossing the $1 billion, that’s billion with a B, mark in three workflow-driven segments: customer, technology, and creators. That’s really, really impressive. That’s showing that the AI stuff is really helping to move the needle in terms of helping customers achieve real results in the real world using this software. A really great quarter for ServiceNow, and they clearly are on the right track.
Recently OpenText also reported Q2 fiscal year of 2024 earnings, they actually just happened on February 1st. Again, bolstered by cloud services and subscription revenue which is very, very strong over the last quarter. It’s interesting because they are also doing … Taking the approach that they want to embed AI across all of their platforms. It’s not going to be a thing where it’s … There’s an AI assistant necessarily but it’s going to be just embedded throughout the platform to really help accomplish more using generative AI. They’re also promising new features and functionality every quarter which really helps to sort of make sure that their customers are really receiving value and are able to incorporate new technology very, very quickly.
That’s going to be key in terms of success in this market because technology, particularly generative AI technology, is moving so quickly and you’re going to want to make sure that you can without a long lag time. The other thing that they mentioned that was pretty interesting is they were discussing platform Athena, which is their proprietary process platform, that’s going to be used internally to help OpenText engineers generate new software. The goal here is to use generative AI there to really speed up innovation, improve time to market, and really roll out new features and functionality much more quickly. I believe the company is saying that its first Athena-generated products are going to be in the market in cloud edition 25.2 so that’s only in about a year and a half or so.
Now I’d like to talk a little bit about SAP which had a very strong fourth quarter in 2023. Their revenue rose to about 8.47 billion euro in Q4 of 2023, up about 5% year over year. I think one of the really interesting things … What they’re doing is again, they’re making … They’re really pushing this transition from on-prem to the cloud and really diving in headfirst, all in. That is their strategy and it’s really starting to work. I think organizations are realizing, despite the pain, that this is where they need to be. Obviously, SAP has put their stake in the ground saying, “You need to be on the cloud to get the latest and greatest in terms of functionality.” I think their customers are starting to respond. As we’re seeing AI sort of take over, it’s almost a no-brainer. It doesn’t mean it’s going to be easy but I think they’re doing the right thing of saying, “Look, this is something that needs to be done.” And they’re embedding the platform with this AI technology and we’re going to see some strong results moving forward.
Of course, the other thing we have to talk about is that, as part of this, they did announce a restructuring where about 8,000 employees are going to be either re-skilled or perhaps some of them may take sort of a voluntary attrition. And the goal here is to make sure that they refocus the workforce on AI. This is the way of the world now. I think it’s a situation where in order to remain competitive you have to have that focus on AI because it has become table stakes. And really AI is not only a feature but it’s also going to be a real growth engine internally for all of these companies. As you can see, looking at the market here, obviously, there’s still other companies that are yet to announce but we’re going to be seeing that over the next several weeks. I think we’re going to see continued strength in terms of overall revenue. I think the only real question, of course, is, at what point, if we look at some of these companies, are they going to be able to manage their expenses? Because, obviously, AI, it is not cheap to either develop, if we’re talking about generative AI. Those cost can add up so it’s something that we need to keep looking at over time.
So with that, I want to move on to another topic here for the week and that is enterprise application usability. One of the things that I think is really interesting when we look at enterprise software and we talk about usability, it’s really … It’s an interesting discussion because if you compare that with say customer user experience versus enterprise user experience, there really are some key differences. I think sometimes when it’s talked about, user experience, these differences aren’t really parsed out. If you’re talking about customer UX it’s all about easy, easy, easy. That’s great because you don’t know what the skill level of that user is. You want someone who’s been able to … Who comes in and maybe has never heard of your product, never used it before, you want to be able to get them up and running automatically.
Now, the difference is, with enterprise software and user experience, yes, you don’t want to make things difficult but you may have other constraints there, and that certainly is … A limiting factor. And when I talk about constraints, it’s not even necessarily with the application itself it can be with the way that application software is procured and brought to users. So if you think about your typical organization, typically they don’t send out a survey to end users in the company and say, “Hi, what software platform would you like to use for CRM? Or what contact center software would you like? Or, what collaboration software do you want?” It’s not usually done that way. They might capture a little bit input here or there but this is … Generally speaking, these choices are made, and then it comes down to users having to deal with whatever they have. And that can create some issues. Or from the perspective of end users, they’re not going to have perhaps as much flexibility, or it won’t be quite as easy to use as a consumer-facing application. But the real impetus is all on the IT department to make sure that they select a product that you can actually … That the IT department can customize based on user feedback once you should start to use the program or use the application.
Every application vendor is going to say, “We can do everything,” of course. And maybe they can maybe they can’t, but really the key is making sure that it is flexible enough so that certain processes you can modify them in such a way that workflows can be modified and changed easily so it doesn’t take an army of developers to do that. And the reason is that ultimately, if you think about employees within an organization, you want them to use the software otherwise you’re just wasting the money. If they’re not using it they’re not going to be as productive. If it’s a system that introduces a lot of roadblocks it makes it very, very hard for them to accomplish certain tasks, you make it lower compliance. And I’ll just use a basic example of, if you have a sales department and they need to log all of their interactions, if there are workflow issues that make it difficult to pull in data from other applications, or if they have to enter the same information three different places then it’s not going to get done all the time because it’s too hard, it’s too difficult to do it. And humans being humans it’s not always going to happen.
Another issue, of course, is if there’s too much friction in the experience you won’t get as much internal cooperation or collaboration between employees in terms of sharing information if it’s too difficult to do that. If they have to flip back and forth between say four or five different applications instead of having information automatically pulled in, that’s a workflow disruption. Sometimes things will get overlooked because it is challenging to do that. Ultimately, I think we still are in this era where we need to think about making that interface easy to use within the constraints of an enterprise application, which ultimately needs to really focus on what are the sort of underlying needs of the organization to take control of a company’s data and make sure that users have access to it. Now, the sort of really interesting catalyst in the mix, of course, is generative AI. And we’re starting to see organizations incorporate generative AI to really assist with workflows. An employee would be able to say something like, “Pull all of the last month’s sales data from my ERP and display it here and create a chart for me in Excel,” or something like that. That’s an overly simple example. But the idea is that by using generative AI, you’re almost getting over some of those points of friction with application design where it would be almost too difficult to create a custom view for every single employee and to make that process seamless.
So I think we’re going to see some really interesting things occurring over the next several years as generative AI becomes embedded within these applications, and allows each individual user to really just find the information they need quickly and easily, either by typing in a prompt, or by speaking to it, or interacting with certain sets of information more frequently than others. I think that’s really going to help in terms of removing these points of friction that often occurs simply due to the fact that you cannot design an interface, no matter how composable it may be, for every single employee in every situation, it just doesn’t make sense to do that, to manually code it that way. Generative AI, however, will help you do that or will help application developers pull that information and make it easier for workers to get the information they need, from wherever it lies within the organization, more quickly and more seamlessly. One of the interesting things is, in conversations I’ve had over the year talking with some very large SaaS vendors, there’s this idea that we might get to the point where really the prompt is the user interface, at least for some basic queries.
And then yes, of course, we’re going to be still using visualization software, things like that, of course, because that’s how humans can make sense of information within context. I do really think we’re going to start seeing this very prompt-driven interface because it’s just going to make access to different pieces of information much more simple for workers which hopefully will make them more productive. And this is where we’re really starting to see ROI from generative AI as opposed to just that sort of basic low-hanging fruit of content summarization or content generation, that sort of thing. It is interesting. I think we’re, obviously, not anywhere close to that yet but I think we are on that road. And in talking with various application vendors, I do think that is … That’s the path we’re going to be on. Anytime you can make it very, very simple to get access to information, it’s just going to make people that much more productive. Really there’s so much ROI in that.
Now, I’d like to move to the rant or rave section of the podcast. This week I’m actually back to a rant. This one is actually more of a customer experience rant but you’ll see where there’s sort of an enterprise application component to it. Last week I was trying to help my mother purchase a new home. She had moved out of her previous one and needs a new home. We were getting closer to the closing and she wanted me to help her set up a wire transfer. Now, unfortunately, she does not live in the same state as I do so we had to conduct this transaction over the phone. I set up a conference call with the bank and I started an interaction asking, “I’d like to set up a wire transfer for my mother.” And then she asked, “Well, how much is it?” And I said, “Well, it’s for” … The amount was well into the many six figures because, obviously, she’s going to be purchasing the home outright. And the challenge was, of course, is that the agent on the phone … There were two issues. One, there was sort of a bit of an accent or language barrier there which made things a little bit challenging. But perhaps more challenging was she did not understand or have the information available to her to understand context. So when I used words like we need to have a closing, a real estate closing, she heard closing and heard oh, you want to close the account. No, that’s not what we want.
And then we would say something like “We need to conduct a wire.” And I said, “Well, it’s through a mobile application.” And she said, “Why don’t you use the mobile application?” And I, of course, said, “Well, I don’t believe that the amount that we need to wire we would be able to conduct that transaction through the mobile app.” She said, “Well, let’s keep trying it.” And I think there was just a disconnect there. We were able to escalate it to another … A supervisor. But, unfortunately, even there she was not able to accurately convey what we wanted to do and I had to go through it all again with that second person. Now, I think there are a couple of things here that are at play. One is, of course, training. But I think ultimately what really would help the situation … And we’ve talked to some vendors out there who do this sort of AI coaching to really help walk agents through a process in dealing with different situations. But I think that AI systems could be really useful in terms of listening to different keywords and phrases throughout an interaction, and then putting up likely scenarios or suggesting relevant scenarios to really help agents reframe their conversations, even if there is something like static on the line or there is a miscommunication due to the speaker’s accent or something like that.
Saying, “I’d like to conduct a wire transfer” and I give a figure that’s in the hundreds of thousands of dollars, we can automatically infer that we’re looking at a major purchase of something. So, as a result, the AI assistant, if they heard the word closing, clearly they would understand it was a real estate closing as opposed to trying to close the account. I think the key here is for organizations to look at how can we use technology to again, further understand not what’s being said just verbatim but also understanding context and relevant scenarios to really make sure that there is more understanding between the customer and an agent. Despite my rant, it is not fair to assume that agents who might’ve been on the job for a very short time would understand every possible scenario. But that’s where I think AI can be used to really help provide that extra little boost of context and information so they can understand quickly okay, this is something I’m not capable of handling, let me transfer you quickly to a supervisor, or to whoever it needs to be escalated to, very quickly to again, ensure that the customer is being taken care of and build confidence that the organization knows what the actual problem is.
That’s my rant for today. It’s really not a rant against any particular agent it really is, let’s figure out a way to get these folks more contextual information to help them do their job better and satisfy customers more. With that, that is all the time that I have today but I want to thank everybody as always for joining me here on Enterprising Insights. I’ll be back again next week with another episode on the happenings within the enterprise application market. Thanks again for tuning in and be sure to subscribe, rate, and review this podcast on your preferred platform. Thanks, and we’ll see you next time.
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
