Search

Enterprising Insights, Episode 30 – Predictions at the Halfway Point of 2024

Enterprising Insights, Episode 30 – Predictions at the Halfway Point of 2024

In this episode of Enterprising Insights, host Keith Kirkpatrick discusses his predictions about enterprise SaaS applications and the market that he made back in late 2023, including generative AI, personalization, tech stack consolidation, market consolidation, industry-specific software, and consumption pricing. He will also address the underlying elements driving each trend and discuss which companies in the market are being impacted.

Finally, he will close out the show with the “Rant or Rave” segment, where Kirkpatrick picks one item in the market, and he will either champion or criticize it.

You can grab the video here and subscribe to our YouTube channel if you’ve not yet done so.

Listen to the audio below:

Disclaimer: The Enterprising Insights podcast is for information and entertainment purposes only. Over the course of this podcast, we may talk about companies that are publicly traded and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors and we do not ask that you treat us as such.

Transcript:

Keith Kirkpatrick: Hello, everyone. I’m Keith Kirkpatrick, Research Director with The Futurum Group, and I’d like to welcome you to Enterprising Insights. It’s our weekly podcast that explores the latest developments in the enterprise software market and the technologies that underpin these platforms, applications, and tools. Now for this week’s episode, I actually want to take a step back here. We are now as I’m recording this, we’re in the beginning of July and I’d like to take a step back to some market predictions that I made back in December of last year, and I wanted to go back, review them and see how many of them actually came through. So we’re going to take our time this week, go through those, see where I was right, where I was wrong, and in some cases I’ll bet the jury will still be out. Then as always, I will move to the Rant or Rave segment where I pick one item in the market and I will either champion it or criticize it.

So let’s get right into it. So as I mentioned, back in late December of ’23, I made several predictions about the market and one of the ones that I made obviously was focused on generative AI and one of the things I said is that in 2024, generative AI will go, basically, we’ll see a lot of general availability of various generative AI tools and really that generative AI was going to become table stakes. So back in December I was saying that, “Well, right now we’re seeing a lot of pilot activity. Basically vendors are releasing product in beta saying, ‘Hey, try this out, see if it works for you.'” And my prediction was that by 2024, we would actually see general availability of generative AI tools. Well, as we check in here at the beginning of July, I would have to say I was pretty much spot on, to no one’s surprise. We have seen a large number of vendors actually go GA with various generative AI tools and functions. Everyone from Salesforce to Microsoft, ServiceNow, OpenText, Adobe, you name it, pretty much the vendors have released product that is actually out in the wild and is being used in a production environment. This is not a terrible surprise.

I think the interesting thing is that we are starting to see, in addition to the very, very basic use cases for generative AI that we were talking about about six to eight months ago, things like content summarization or the generation of content or even the basic generation of images from text prompts, we’re starting to see more advanced use cases for generative AI, essentially using that technology to query these large systems to make it easier to interact with them. So I think that’s been a little bit of surprise in that how quickly we moved along. But on the other hand, given the pace of innovation and just the fact that if you look at some of the large language model providers who have come out with the next couple of generations of their large language models, plus the development of small language models, which are more specific or tuned models that are really set up to handle very specific use cases or specific industries, I think that’s why we’re starting to see a great variety of use cases and dare to say it, some more advanced functionality. So yes, I certainly think that that prediction certainly has come true.

For the second half of the year, I expect more of the same in terms of rolling out these various different types of generative AI tools and enhancements to products from these major SaaS vendors. So let’s see here. Second prediction. Vendors will try to introduce usage or consumption-based pricing models. Okay, so what was I referring to here? Well, if we talk about generative AI at the very end of last year, the idea was that this was so new that really vendors were really just trying to get some product out in the market for customers to try and get familiar with it and really ascertain whether or not this actually added value to their organization. And the goal of course, was to just spur usage, not necessarily worry about developing a full business model to actually recoup cost or turn a profit from these new technologies. So where are we now in the middle of 2024? Well, we are starting to see vendors start to take a closer look at these types of pricing models. It doesn’t mean they’ve fully moved to them, but certainly we have seen a bit of a shift. I’ll give you one example.

If we look at one of the major SaaS vendors in the marketplace, Salesforce, they actually have really rebranded their generative AI product as the Einstein 1 platform, which can be leveraged across all of their major clouds, Sales Cloud, Service Cloud, Commerce Cloud, Marketing Cloud, so on and so forth. And obviously that will all link back to Data Cloud, which is sort of their CDP solution to link all of the data sources within the organization, and even some outside, together and making it so AI can act upon all of that data. The interesting thing is that they are marketing these clouds products as having a certain number of generative AI credits included, and what we’re seeing here is sort of a freemium model. Essentially, “We’re going to give you X number of credits to use generative AI, get familiar with it, and hopefully give you enough for probably 80 or 90% of the market to feel like they’re not bumping up against the limits.” Obviously you’ll have outliers that are using more and of course they are making these additional credits available for purchase.

But I think the goal was again, still at this point, to try to entice folks to use the technology, see that it has value, see that it actually fits into their workflow and not necessarily worry about tying that use to the actual cost. So at this point we’re still sort of in that early stage of vendors trying out usage or consumption-based models. Again, it’s sort of more of a tiered approach where you get a certain number of credits per tier or per product if you go over that and then you have to pay more, as opposed to a direct consumption model or a model like deposit account where you have X number of credits and you pull them out and once you hit your limit, that’s it. I think that is still coming, but I think it’s going to take time to roll that out because it is a major shift and if we look at the way the market is also changing in terms of using generative AI to replace or shift human workers into other roles, I think that’s going to have a major impact on how pricing is developed and rolled out over time.

Okay, so our next prediction or my next prediction from last year, enterprises will continue to focus on consolidation with their technology stack. So what am I talking about here? Well, if you think of large organizations that basically went out a few years ago and bought and bought and bought new applications to handle new functionality, obviously part of it was due to the pandemic. They had to stand up new resources very quickly and didn’t necessarily have time to take a long-term approach to application planning and purchasing. So what resulted of course was this model where you had a number of different applications within a particular organization, some of which may have had overlapping functionality, perhaps you’d have applications that were purchased and still had some good features but they needed something else and they went out and bought another application to fill the gap. So what we wound up with were a large number of applications in use at a particular organization, and what that resulted in was obviously security risks. You had waste. You had a situation where perhaps maybe not all of the licenses were actually being utilized, which obviously creates, it’s a cost issue, a waste issue. You also have issues with various skill sets and different people using the same functions from different applications, which is inefficient, leads to some issues in terms of workflow as well.

So my prediction was that enterprises would really start to focus on consolidating their technology stacks in 2024. Now, has that happened? Perhaps a little bit. I think what we’ve seen more is that enterprises, they are evaluating all of these applications. Some are making a move to try to consolidate. Others are saying, “Well, we may have all of these applications. What we need to do is identify which ones are we using, which ones are we not?” And that’s where platforms like WalkMe, CloudEagle, they’re starting to see more utilization from organizations that are trying to get a handle on exactly what is their technology footprint so they can actually go through and shut off the applications they’re not using, let some licenses go and so forth, and really understand what the technology utilization is within the organization. In terms of consolidation, I think that’s something that’s going to take a little more time and is very, very much organizationally dependent upon an organization’s priorities with respect to digital transformation, the management of data and what their own particular needs are.

I do think we are going to start to see that happening more as you see large SaaS application vendors do two things. One is incorporate more functionality across their platform to make some other sort of standalone point solutions redundant in some ways. So I think what we’re going to see is certain large platforms taking the approach of incorporating more functionality within their platforms so they can make certain point solution applications redundant in a sense. So for example, if you’re a platform, a commerce platform, instead of just offering a commerce functionality, like a checkout on your website functionality, you could also incorporate things like the ability to look up tax for different jurisdictions or to incorporate shipping information so that one platform can handle the functions of many minor point solutions. So that’s going to certainly happen. The other thing is this growing commitment to an open ecosystem to allow more pre-built integrations and more smooth integrations via API with other solutions in the marketplace.

So the goal here is not necessarily that you’re going to be compressing these tech stacks, but you’re going to be making sure that all of the applications can talk to each other and you’re actually receiving value from all of the applications that you’re using. Will there be consolidation as the year goes on? Undoubtedly. It is going to be up to the organization to determine at what pace they do that, which applications go, which stay, that sort of thing. Wholesale rip and replace, I don’t know that that’s going on to a large degree, just given the cost involved. If we think about something even like this migration to the cloud where organizations, where vendors in particular are saying, “Well, hey, we should move to the cloud.” Well, that’s really expensive. It can be done, but you have to have the organizational will. You have to have the business leaders who are able to actually focus in and go, “Okay, what assets still need to be on-prem? Which can actually move to the cloud? What is our security situation like?” So it is very complex.

I think it’s not something that just sort of happens overnight, but certainly I do think that to some degree we’re just seeing a little bit more focus on organizational tech stacks and what the utilization is. So I would say for this prediction, I’m perhaps half right. So next trend that I thought would happen in 2024. SaaS vendor consolidation will accelerate. Well, this was based on the idea that, again, there were a ton of vendors that popped up during the pandemic, even before then, that all really, for the most part, they had very similar levels of functionality and features. And my sense is that when you get to a certain market and you have large vendors that control a large percentage and you have a bunch of smaller ones all trying to do the same thing and competing against the same dollars, you do see consolidation. Now so far that has not come to fruition in a large way at this point as of July 2024. We’ve seen a couple of deals where it’s happening. I’ll give you a couple of examples. Avaya actually acquired Edify, which is a CCaaS, CPaaS, and UCaaS platform provider.

That was very strategic in nature to provide Avaya with some very specific capabilities. So that deal happened, I believe it was in April or May is when it was announced. And then another one comes from SAP, which paid 1.5 billion to acquire WalkMe. Again, this was also strategic in nature. SAP is doing everything they can to try to incent its customers to move to the cloud. So what does that mean? That means that you need to do all of this work of identifying which resources you have, which you’re using, which you’re not, making sure that your whole tech stack is accounted for. And WalkMe’s digital adoption platform actually provides a lot of that functionality and it’s certainly an application that adds value to SAP’s portfolio along with a couple of other acquisitions that they’ve previously made. Signavio and LeanIX, which also dealt with this whole idea of making sure that organizations had the tools and the data and the insights to actually make an informed move to the cloud.

I would say here, I kind of missed the mark a little bit on this prediction. Not sure what’s going to happen in the second half of the year. I do think there might be a bit of a stagnant period here given that we are coming up, at least in the United States, into an election year and there’s always a little instability around that, but certainly we’ll wait and see, but I think at this point I would have to say I kind of missed the mark on this one. Let’s see here. The next one. Focus on personalization continues in the B2C market and expands into the B2B market. Okay, this one’s really interesting. This kind of plays into the whole idea that as we start to see AI really kind of permeate throughout organizations, there would be this ability to actually personalize interaction not just for B2C customers, and essentially you and I going to our favorite retailer online or in the store and making sure that we’re getting served up products that meet our particular preferences and past histories and needs and all of that kind of stuff.

This prediction is really focused on this type of approach expanding to B2B companies. And I would say that we’re starting to see a little more of it on the vendor side in terms of offering those capabilities. They realize that the B2B process when it comes to purchasing is not at all like the B2C. It is much more complex. There are far greater number of influencers and other stakeholders who need to be intimately involved in that purchasing process and it is not all the same. You can’t even just say B2B versus B2C. That process is very different in, let’s say, a pharmaceutical company versus a heavy industry manufacturing company just in terms of the different procurement processes, the levels of approval needed, regulatory issues, all of that kind of stuff. Now, why I thought this would kind of expand now is that we are seeing this greater focus on really activating all the data that is available in organizations about all of these stakeholders. And now that you have generative AI, it is that much easier to try to interact with that data and really activate it and improve these processes, automatically serving up if someone is interacting with a company and they’re looking at a part, being able to automate the process of making sure that before that purchase order is sent through, making sure that all stakeholders are signing off, things like that.

Is this happening to a great degree? Probably not yet, but I do think that there are certainly steps being put in place at vendors to enable these types of interactions, this greater level of automation and the increasing use of generative AI. So I don’t think we’re there yet. I’d be interested to hear from anyone if they can provide any examples real world on this going on. I have talked to some companies and customers about it. They just said it is interesting to them, but it is a question of really revisiting not only the technology but the processes to make sure that the technology fits in to the workflows. So kind of jury’s still out on that one. Okay. And for my final prediction for 2024, I said that there would be an increase to industry or niche-based approach to SaaS sales and marketing. So what does that mean? It means that are we going to see more sort of industry-specific versions or enhancements to these large SaaS platforms? I would say absolutely this is coming true. I’ve sat on a number of different briefings where large generic platforms are now being reformulated or enhanced or recast to focus on specific industries and use cases within those industries.

Everything from tax and accounting to manufacturing to retail to service, all of the above and more. Why is this? Well, there’s a couple of reasons. Number one, customers, they’re not going to sit around and necessarily wait for a package that is sort of generic to be customized to their every whim from a third-party consultant. That approach is very costly, time-consuming. A lot of times it just doesn’t ever work as good as you could because there’s so many competing stakeholders who are competing for that consultant’s time. And it also, because it is so customized, it doesn’t always work the way it should because of the breakdown between, let’s say, me the user trying to explain exactly what I want from that application and having that consultant reconfigure the application to work exactly the way I want it because it may not be the most efficient way to do it. So what we are seeing are vendors really kind of doing that hard work before, basically in productizing based on their industry knowledge of all of the processes and workflows within a specific industry.

A great example would be if you look at the work that Epicor, which is an ERP company, does with its ERP product. They are very focused on the manufacturing vertical, but not just manufacturing. They are looking at very, very specific ones like specific well-drilling equipment, something like that. So they’re going to know all of the ins and outs of that business and are able to tailor a solution that will be able to work pretty much out of the box for that industry. Why would they do that? Well, because they realize that if you do it for one company there and you do it successfully, obviously you can do it for others in the industry with minor tweaking. That’s just a smart play. It sort of also plays into the whole idea that ultimately, just as consumers are expecting more personalization, businesses are also expecting a more personalized approach to the software that they’re buying and they’re wanting much more out-of-the-box functionality to be incorporated so they don’t have to spend a lot of time customizing that software because really there’s no time when you think of the rate of innovation, the pace of innovation today with incorporating things like generative AI. If you have to wait eight, 12, however many months to get the solution to work exactly the way you want it, well, things have already changed.

So you can look at my research notes where I’ve covered a lot of different industry vertical focused launches from all of the major software vendors that I cover, you can sort of see this trend in action. So I think I hit the nail on the head on this one. I think this will certainly continue. I think what we’ll also see is a greater number of these large SaaS companies really kind of diving in, not only on the technology side but also trying to work with other experts in the field to really kind of build up and cement their sort of domain expertise. Because that’s ultimately where the real value is is understanding what workflows are commonplace, what are the pitfalls, what are the regulatory issues that are involved so that a solution can be tailored to that specific industry. All right, so I think I did pretty well with my predictions. Like anything, sometimes you miss the mark a little bit, but I think overall, as we look forward to the end of 2024, I expect all of these to continue to some degree and I will certainly be back at the end of the year for my predictions for 2025.

So with that, I’d like to move to my Rant or Rave section and this week I have a rave. Now this is around something I normally have a pet peeve about, which is when a vendor releases a new product and they do not release any sort of pricing along with it. They usually say, “That depends,” or, “You need to call,” or whatnot. The challenge with that is for me as an analyst is trying to ascertain, well, what is the actual likelihood that a particular product is competitive in the marketplace with others in terms of pricing? Now pricing is not the be-all end-all. We have to look at value and that’s obviously a calculation that is highly dependent on the organization, the use case, the scale at which the solution is being rolled out, so on, so forth. But just getting hard numbers for pricing is certainly a welcome change from a lot of the analysis that went out. So what I’m referring to here is Microsoft Dynamics 365 Contact Center just went generally available and the release that went out and the folks from Microsoft actually put out plain and simple pricing. They said it’s available for $110 per user per month for Dynamics 365 Contact Center, which includes digital and voice channels as well as individual channel options for additional purchase. They also talked about another tier of service, the Dynamics 365 Customer Service Premium available now for $195 per user per month.

And then what’s really nice about this again is this is very helpful in terms of framing and understanding what would the potential outlay be for a particular contact center of a certain size. It’s very easy to kind of get that calculation and then assess, hey, what is the value delivered just on a straight pricing basis. And then you can do a further analysis in terms of looking at, well, what features are involved, what is the expected shift that will occur within that organization in terms of moving frontline call center employees to higher value techs? Or maybe they’ll be x more productive or what. Ultimately though, having that metric there is really great to see, particularly given that a lot of times all of this stuff is hidden behind layers and layers of different terms and conditions, which makes it very difficult to compare solutions. So kudos to Microsoft for being upfront about that pricing. Obviously the devil is in the details with everything in terms of when we really get into it, but at least there’s sort of a baseline there. So certainly a rave there to Microsoft. All right, well, with that, that’s all the time I had today. So I want to thank everyone for joining me here on Enterprising Insights. I will be back again next week with another episode focused on the happenings within the enterprise application market. So thanks again for tuning in. 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.

SHARE:

Latest Insights:

Nivas Iyer, Sr. Principal Product Manager at Dell Technologies, joins Paul Nashawaty to discuss the transition from VMs to Kubernetes and the strategies to overcome emerging data storage challenges in modern IT infrastructures.
Shimon Ben David, CTO at WEKA, joins Dave Nicholson and Alastair Cooke to share his insights on how WEKA's innovative solutions, particularly the WEKApod Data Platform Appliance, are revolutionizing storage for AI workloads, setting a new benchmark for performance and efficiency.
The Futurum Group team assesses how the global impact of the recent CrowdStrike IT outage has underscored the critical dependency of various sectors on cybersecurity services, and how this incident highlights the vulnerabilities in digital infrastructure and emphasizes the necessity for robust cybersecurity measures and resilient deployment processes to prevent widespread disruptions in the future.
On this episode of The Six Five Webcast, hosts Patrick Moorhead and Daniel Newman discuss CrowdStrike Global meltdown, Meta won't do GAI in EU or Brazil, HP Imagine AI 2024, TSMC Q2FY24 earnings, AMD Zen 5 Tech Day, Apple using YouTube to train its models, and NVIDIA announces Mistral NeMo 12B NIM.