In this episode of Enterprising Insights, The Futurum Group’s Enterprise Applications Research Director Keith Kirkpatrick will discuss the upcoming year in enterprise-focused SaaS applications, focusing on six trends that he expects will come to fruition in 2024. He will also address the underlying elements that are driving each trend, and discuss which companies in the market may be 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.
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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. 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, in our last episode, we had a rousing discussion between me and two other Futurum Group analysts, Craig Durr and Sherril Hanson, where we took a look back at the year that was 2023.
This week, I’d actually like to take a look ahead to the trends that I believe will come to bear in 2024 in the enterprise application market. Now, some of these trends started in 2023, to be fair, but I think we’re going to see a significant amount of momentum this calendar year brought on by both internal and external factors. Then, as always, I’m going to close out our show with the rant or rave segment where I pick one item in the enterprise software market and either champion it or criticize it.
So without further delay, I just want to jump right in to the topic of the week, which really revolves around six emerging trends that I believe are going to shape the enterprise software market. Now, when we’re talking about enterprise software, we’re, of course, referring to these large software as a service or SaaS platforms and applications. These are the applications that are used across enterprises to do any number of different things. We can talk about things like customer relationship management software, certainly enterprise resource planning or ERP software, contact center software. Really it kind of runs the gamut. But really what we’re starting to see here are some factors that are going to change the way that these applications are put together in terms of both pricing, the features, and even really how enterprises really consume them given that we are seeing some interesting changes happening in the market.
Why don’t I get started here by talking about my first trend that I expect really to take off in 2024? And really that is, of course, the general availability of generative AI functionality within these large SaaS platforms. Now, of course, as we all recall, if you go back about a year ago, we were just starting to hear about generative AI. Open AI made their tool available to the public. And then a couple months after that, we started to see some large vendors incorporate generative AI functionality within their tools, generally speaking, in a pilot version or a beta test version. And these things were generally restricted to very basic functionality, summarization of text or you could perhaps have some really limited other types of functions there.
But ultimately, most of these tools were deployed in a pilot basis so users could get used to them, as well as allowing the vendors to refine the functionality, make sure that they had everything they needed to ensure that the tool would be properly constrained so it wouldn’t hallucinate and provide strange answers, and would also make sure that you didn’t have any issues with respect to incorporating or inadvertently bringing in these bias or other inappropriate responses. Now, we’ve seen over 2023 some companies actually started to make these tools generally available.But I predict that in 2024, almost all of the large SaaS vendors will move ahead full steam in terms of incorporating generative AI functionality, making them generally available to their users. And we’re talking about companies like Salesforce, Automation Anywhere, Microsoft, Amazon, ServiceNow, OpenText, Adobe, you name it, Zendesk. Any vendor that is offering some sort of a SAS platform, I believe throughout 2024, they are going to be moving their generative AI tools out of pilot, out of beta and making them generally available to their customers.
And the reason for this is we’re starting to hit that inflection point where generative AI is not something that is nice to have or a shiny new feature. It really is starting to become table stakes when you have an organization or an enterprise organization that is looking to purchase new technology. It’s almost become something where if you don’t have generative AI, I don’t want to say you’re completely X out in terms of being a possible vendor, but it’s pretty close to that just because of the sheer amount of hype surrounding generative AI, as well as some of the early results that we’ve seen in terms of ROI, productivity gains, cost reductions, that sort of thing. So that’s my prediction right there around generative AI. We’re going to see that move to general availability throughout most of the vendor landscape.
Now, moving on to the second trend I expect is that we’re going to see a little bit of shift in terms of how vendors are going to try to price these tools. Initially, again, in a pilot program, some of the companies were basically saying, “Here, users can use this technology for free while it’s in beta. And then once we move to general availability, we’re going to move to a per user per month seat license based approach to pricing functionality.” So essentially if you are a user of a particular application, you can add on generative AI features and functions for a set flat price of whether it’s 20 bucks a month or 30 or 25, what have you, 50, whatever it might be. So essentially you’re getting access to that generative AI functionality for an additional cost. Now, I’ve spoken to a number of vendors who have said that in terms of trying to come up with the price for that, it has largely been almost their best guess estimate on what appropriate pricing level should be.
So they don’t necessarily know or have enough data to really ascertain whether or not the price that they’re charging on a per seat basis will actually cover the real cost of providing that service. So what I think we’re going to see here in 2024 is vendors slowly starting to push for usage based or consumption based pricing models. So what that means is you’ll have…
Instead of saying, “Okay, I’m going to have 50 users who want to use generative AI technology and they’ll pay an additional $25 per month per user to use generative AI,” they’re going to want to actually tie that activity to actual consumption-based pricing. And how do we do that? Well, my thought, and I believe this is just something that’s going to come to the market, is, of course, you’re going to move to more of a token based approach pricing approach. And what that means is you’ll have various generative AI functions, whether it’s content summarization or it’s providing a recommendation or generating an image. All of those require compute. All of that requires a call to that actual large language model. Some functions require a greater amount of compute, others require less.
By assigning a token based approach where you could say that let’s say generating an image from a text prompt is worth 10 tokens versus doing a summarization of an agent’s call with a customer is two, there you can establish relative value for that generative AI call in such a way where it’s more transparent to the end customer and also allows the vendor to more closely tie the usage with the price that is actually being charged to the end user. I expect we’re going to see that start to creep in within 2024 because the vendors are starting to get a better handle on how much their AI technology is actually being used by end customers, and it’s also a way to make sure that as functionality continues to increase, they’re able to closely tie all of that activity to pricing and make sure that the people, their end customers who need the technology, have it and they have a clear and transparent model for looking at what their costs are going to be over the next contract period.
So I think that is going to happen in 2024. It is going to be a gradual shift. It’s not going to be something where organizations flip the switch overnight, but I do think it’s coming. Because at a certain point, the per user per month model is simply not going to be sustainable either for the vendors who may wind up losing money if you have users that are just doing generative AI calls all the time just because they can do it, that becomes very expensive for the vendors. And on the end user side, it isn’t really cost-effective to just go out and buy all of these licenses for functions that maybe really don’t require generative AI or they don’t require an all you can eat type availability of that technology. So that’s another prediction for 2024.
Now, let’s look at the next one, which is something that’s been going on for a while, but I do believe that we’re really going to start to see some momentum in 2024, and that is enterprises are really going to focus on consolidating their technology stacks. If you look back to the pandemic starting in 2020 and really carrying throughout the next couple of years, you had enterprises that were going out and buying new applications. A lot of that was due to the fact that you had a massive shift in the way people were working. You had people moving to fully remote work, and then, of course, moving to hybrid working environments where they may be doing some work in the office, but also needing to be able to work outside the office as well seamlessly. So applications were going out and acquiring technology, and problem with that is you start to get a very, very bloated technology stack. You have applications that perhaps you bought five, 10 years ago which are no longer being used, but you’re still paying for the licenses, or you’re trying to incorporate new functionality that your previous application vendor wasn’t able to provide, so you went and bought another one to fill that gap. Well, now we’re in this period where organizations are starting to take a hard look at what they have.
Because number one, there is significant waste involved in that in terms of costs. If you have applications that have duplicative functionality, you’re overpaying. You also have issues with security. The larger and more bloated your tech stack is, the more potential there is for security holes to really creep up. And sometimes that is due to data being passed between applications. Sometimes it’s due to having a greater number of logins. And of course, humans being humans, sometimes they reuse passwords even though they’re not supposed to, and that can create a security issue.
So what I expect to see this year is organizations, enterprise organizations, really focusing and taking a look at the tools they have, the tools that they are going to need to acquire, and part of that is, of course, driven by the incorporation of generative AI, and really making an assessment of what functions do they need to accomplish and how can the software they have meet those needs and taking a look at the stuff they have that they don’t need anymore and really trying to streamline that. Because ultimately, this upward trajectory of just acquiring software over and over and over again endlessly, it just is not sustainable. So I expect to see organizations take a close look at that. They may be using these digital adoption platforms, which help assess what the utilization of the technology is within the organization, what it really is, what’s really being used, what really is not being used, and using that to provide a little more intelligence.
Now, the next trend that I see is, again, given the fact that we’re in a new year here, we’re starting to get to a point where we have a lot of SaaS vendors out there providing very, very similar functions. Every time I talk with a vendor, they’re always talking about, “Well, we have this feature. We do this better than another company,” of course, because they obviously want to position their product as being superior on a technology level, functional level, and ultimately being a better fit or a better choice for an organization that is looking to accomplish all of their technology goals. Now, the problem is that you have a lot of companies out there that really say, even though they may use different language, slightly different terminology, and even the feature sets may be slightly different, there is a lot of overlap in terms of functionality. And what I think that means is that we’re going to start to see a little bit more vendor consolidation coming back into the market now. Certainly large vendors are going out looking at some providers of very specific technology like generative AI or like automation technology and acquiring that because they’re realizing that in order to… There’s two things going on. One, of course, is large vendors want to make sure that they have all the capabilities that are out there under their own roofs.
And secondly, if you’re a smaller vendor and let’s say you offer the same technology as a large one, chances are you’re going to be faced with a real challenge in terms of competing in the marketplace, particularly as large enterprises start to try to consolidate their technology stack. So a lot of these smaller companies may be looking for exits, and one of the ways to do that, of course, is to be acquired. So I expect that that’s going to happen. Sometimes when this occurs, there’s the fear that with consolidation in the market in terms of number of vendors, we wind up seeing less innovation. I don’t think that’s going to be the case given that right now, if you look at where we are in terms of maturity level or maturity curve of things like generative AI, I still think there’s a lot of innovation left out on the table that even large vendors, they’re really pushing hard to make sure that they’re able to incorporate that. I don’t think consolidation will negatively impact innovation right now because there’s still so much that is in the works.
Now, another trend that we are expecting to see come to fruition in 2024 is this continued focus on personalization as it relates to applications providing the ability of organizations to more personalized interactions. And this has been going on for many years, particularly on the B2C side. If you go to any large retailer or service provider, chances are you’ve already experienced this where you’re getting personalized offers, or perhaps based on actions that you’re taking, you’re getting shown products that relate to what you’ve done in the past or your preferences from the past. We expect this to really expand this year to the B2B segment, and there’s a couple of reasons for that. One, B2B buyers in their personal lives, they’re consumers, so they’re becoming accustomed to get a very personalized approach to things. The second reason is the B2B purchasing cycle is just… It’s a great opportunity to provide that personalization. Because if you think of a company, it’s rare that one person makes a purchasing decision on their own. You have influencers.
You have people who actually do the purchasing themselves. You have approvers, and you have end users who actually are using the technology. And all of those folks generally need to have some sort of input into that purchase process. By providing more personalization, you can streamline those flows in terms of getting deals approved and also making sure that anyone who has influence or decision authority can actually get all of the information they need and only the information they need. You don’t need to have everyone within the organization to see every detail of every deal. It’s not efficient. And in some cases, it would violate company best practices or standards in terms of a particular employee at a certain level seeing let’s say all of the pricing or all of the offers that are available. So ultimately, we expect to see a greater amount of personalization into the B2B buying process.
And this is something that technologically speaking is easy to do or can be done now, and I think generative AI will help usher that in by making it easier for all of these stakeholders to query systems to get the information they need, as well as for vendors to automatically serve up the most relevant information to these buyers or influencers at the right time in the process. So we expect to see that continue in 2024. For the final trend of 2024, I think the trend that we’re going to see is this industry or niche-based approach to SaaS sales and marketing. So obviously you have large SaaS vendors that are continuing to proliferate in terms of making their platform available to a number of different types of companies in a number of different industries. But what I think is going to really happen this year is you’re going to start to see a more targeted approach to reaching out to customers within the specific industry segments and being able to actually package and market specific functions or features of a large SaaS platform to them based upon their needs.
And a lot of that is going to be based upon these vendors realizing that a large CRM platform may work for 80% of the industries out there, but it might be missing certain specific functions or features that are specific to let’s say the restaurant industry or to a travel agency or to a construction company. By making sure that a solution has those industry specific functions or features pulled out or grouped or highlighted in some way, they’re able to appeal to the buyers that go, “I know that my industry is very, very unique and I need a very specialized solution.” Now, they may be considering these specialized ERP or CRM or what have you systems out there in the market, but these large SaaS vendors are realizing that they’re leaving money on the table by not taking more of a niche approach. These companies have the budget and they have the ability to hire industry experts to help them really focus in and create these solutions that are very specific to each industry and the buyers within. And I think we’re going to see more of that happening in 2024 largely because this era of one size fits all, it’s just I think we’re past that now.
We have the technology and the data to do this more targeted marketing and sales based approach even with large platforms that technically can serve every type of industry. But ultimately, buyers are looking for something that is tailored directly to them. So we expect to see that happen in 2024. Now, will all of these trends happen at the same time in 2024? Probably not. We’re probably going to see a gradual curve toward adoption, most likely led by some of the largest vendors out there that have the budget and have the staff to actually enact some of these changes. And then we’ll see the rest of the market, that 80%, slowly follow on. Will everything happened within 2024 in that calendar year? Probably not. We’ll probably see some of these trends creep into 2025.
But we believe that right now, given the state of the economy, given the fact that enterprises are still being cautious with their approach to purchasing, they’re going to be looking for more tailored solutions and a more targeted marketing push towards them so they can make sure that what they’re buying is most relevant to them. So those are some of the trends that we expect to see in 2024. I’m sure that I will be revisiting them throughout the year and seeing which ones are coming true and which ones I’ve missed the mark on.
Now we’ve come to the rant or rave section where I either champion something from the enterprise application space or I criticize it, and today I have a rant. So I want to talk to you a little bit about a story I recently heard with respect to an employee having an issue with an enterprise application.
This employee was trying to adjust their contribution to their 401(k) plan, and they mistakenly input a per paycheck deduction of $20,000 into the field instead of 20%, which would seem to be a bit more normal. So there are really a couple issues here. One, within the application, there should have been some sort of guardrail to prevent the incorrect data from being input into that field. Usually for any type of value, there is going to be a normal accepted value, which would be anywhere from like if we’re talking 401(k), anywhere from 3% to perhaps 15% or something like that, or 20%. It should not go up to 20,000 or something like that.
Second, there needs to be some way to really make clear whatever that field is what the units are. Is it percentage? Is it dollar amount? Either which way, it needs to be made more clear. And then of course, the other thing would be is if there is something that is an amount that is put in there and it is outside… Basically there needs to be some confirmation that whatever the total amount is provided for that paycheck period or some way to really confirm that the information that the employee wanted to put in is actually going in. And in this particular case, they never got a confirmation until two days later, when, of course, as we’re all kind of used to doing, we read through things quickly and don’t necessarily confirm the information. Now, there’s a couple different issues here at play. One is, of course, the actual user interface and the user experience there with that application, it needs to be more clear. There needs to be guardrails so the wrong information or information that is outside the norms cannot be input.
Secondly, there needs to be a confirmation sent right away, not two days later. If you think about some consumer facing applications, if you go to let’s say book a haircut or something like that, you’ll usually get a confirmation right away that clearly says you’re booked for this time with this person. This did not happen. And finally, when we think about this whole plan or this whole situation, the employee actually contacted their HR department when they realized that they weren’t getting a paycheck that week because they tried to deduct $20,000 or something like that from the paycheck. It took quite a few hours to actually resolve the situation. This is a real issue because of a couple things. One is that’s lost productivity when we have both the HR people, as well as the vendor scrambling to correct the error.
Second thing, of course, is it’s a very, very poor employee experience. We’re in an era where, quite honestly, it’s easy to do usability testing with these things and easy to make sure that even people without a lot of technological savvy are able to fill out forms in such a way where there isn’t going to be a massive error. So my rant really is it’s focused in on looking at user experience design and making sure that there are proper guardrails in place. Because in the end, if you don’t have it, you’re going to have angry employees, which, of course, impacts their, I guess, feeling about the organization and perhaps could impact the way that they carry out their jobs. And then of course, secondly, it is an issue when it comes to lost productivity, dealing with errors that are really easily correctable or preventable. So that’s the rant for the week.
Generally speaking, these situations can be taken care of just by going through and having almost like a mystery shopper go through and try to put in incorrect information, and most likely you’ll be able to uncover any points of friction or points where there’s confusion pretty quickly. So that’s our rave for the week. Now, that’s all the time I have this week. I want to thank everyone for joining me here on Enterprising Insights.
I’m actually going to be headed to the National Retail Federation’s big show next week, and I will have a recap on my thoughts on enterprise application technology that I see for the retail market in the next episode. So thanks, everyone, 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.