How SaaS Can Use AI and Machine Learning

by Jonathan Tarud
Blog Post

Artificial Intelligence (AI), powered by machine learning principles has long been a driver of fiction. From The Jetsons in the 1960s to more contemporary movies such as 2013’s Her, we’ve had a natural fascination with the possibilities that AI can create.

These days, fact has caught up with many ideas from fictitious plots. We’ve got chatbots being integrated into many services and growing development of AI-related applications. In a recent letter to Amazon shareholders, CEO Jeff Bezos stated:

“Big trends are not that hard to spot … We’re in the middle of an obvious one right now: Machine Learning and Artificial Intelligence.”

Bezos mentioned AI twice in his letter, referring to Amazon’s own SaaS offering, Amazon Web Services (AWS):

“Inside AWS, we’re excited to lower the costs and barriers to Machine Learning and AI so organizations of all sizes can take advantage of these advanced techniques.”

It should be no surprise that SaaS are very much a part of this “big trend.” SaaS specialize in data, and AI, along with machine learning enable more automated means of mass data-processing.

How can SaaS use AI and machine learning moving forward?

The current state of the SaaS market

Indicators across the SaaS marketplace and research from industry analysts all point to the fact that the SaaS market is maturing and slowing in terms of growth. There is still room for continued adoption of SaaS, particularly among industries that have been slow on the uptake (healthcare and manufacturing are just two examples), but the explosive growth we have seen previously has slowed.

A report from IDC shows that the SaaS segment, which makes up 68.7 percent of overall cloud market share, was the slowest-growing segment of the cloud market with a 22.9 percent year-over-year growth rate last year.

Venture capital funding, usually an indicator of how “hot” investors view a market to be, has been found to be on the decline when it comes to SaaS startups. TechCrunch attributed this in large part to market saturation and the fact that those newbies seeking funding are often trying to compete with large, established players.

While the SaaS market is still expected to show some growth, it’s expected to be at a lower rate than we’ve seen previously. SaaS markets are maturing and it seems that those who are going to come out as winners will need to be onto the next “big thing.”

Big players incorporating AI

Besides Amazon and AWS, other big players in the market are announcing offerings that integrate AI. This is perhaps another solid indicator that AI and machine learning could be the next step in differentiating a SaaS and helping it to carve out a space in the market.

Oracle just recently announced that it is infusing its entire lineup of SaaS applications with AI and machine learning. They state that thousands of businesses across every industry are now expecting a new generation of AI-infused apps to “trigger unprecedented levels of speed in innovation, in the ability to disrupt competitors or even entire industries, and in the ability to adapt to and get in front of rapidly shifting market dynamics.”

SaaS makes up the biggest proportion of Oracle’s cloud-based services, accounting for about 74% of their cloud revenue. They are the world’s second-largest provider of SaaS apps behind Salesforce, although they are jockeying to take over the number one spot.

Their new breed of AI-infused apps are designed to create better, more personalized experiences for users as the machine learning component allows apps to learn as they are used. They believe that there is room for AI across all segments of their SaaS lineup.

If these larger companies provide a good indicator, we’re about to see more integration of AI and machine learning in the SaaS world, as other companies seek to carve out a position for themselves.


Gartner released a report last year predicting that AI will drive big changes to the pricing models of SaaS. More customers deploying their own AI means fewer employees using the software, putting the pricing model of charging per named user under pressure.

An example they give is that of an ecommerce firm cutting their staffing numbers and deploying chatbots to pick up some (not all) of their customer service duties. The prediction from Gartner is that SaaS cannot charge for chatbots the same way they would for named users. This means that SaaS would be in danger of losing most of their users and a pricing rethink would be needed. Gartner further predicts that by 2025, 40% of software that currently operates pricing on a per-user basis will transition to other models.

How SaaS use AI and machine learning

SaaS are picking up on the trend for AI and machine learning and it looks like this sector is set to grow. Here are a few things we are seeing already and can expect to see further development in:


AI can bring the option of hyper-personalization to SaaS, something which we’ve already seen in mobile apps in particular (look at Taco Bell’s “Tacobot” or Starbucks’ “My Starbucks Barista”). In SaaS, natural language processing and the ability of AI to learn from user’s previous interactions can help configure user interfaces so that they cater to the individual.

For example, if you think about any SaaS without AI capability, adding more functions or features tends to cram the user interface and add complexity for the user. AI can help not only with personalization but with easier adoption of features.


Automation is demonstrated in many different ways in SaaS with AI baked in. It can take over where previously manual functions were required, for example, in the case of chatbots that help to provide users with answers to basic questions.

One of the challenges for SaaS is always keeping an engaged customer base from a remotely operated perspective. It can be difficult staying on top of customer service requests and ensuring that every customer gets a good experience. AI can help with that by reducing that remoteness and stepping in to supplement human effort.

For example, there are already several examples of apps (Lola, Verizon, banking apps etc.) where chatbots answer questions up to a point, but refer users to human operators where necessary.

Deploying code

The consequences for a SaaS rushing through code and deploying early, only to have a crash or bug that affects all users can be very costly. Reputation and potential liability issues abound, yet being able to deploy quickly can be a distinct advantage. If you’re in a competitive market, the difference between leading or lagging can be if you are first to reach people.

AI is a game-changer for SaaS developers because it can augment their own coding abilities by providing the necessary checks that the coding is good. Deployment can be cut down from months, to a very short time when AI can verify that the SaaS is built to scale to thousands of users.

Docker is an example of this, checking and testing code for quick deployment. Look out for further developments in this area – Microsoft and the University of Cambridge are working on teaching AI to write code itself.

Predictive analytics

There are many potential ways in which AI built into SaaS can leverage predictive analytics to create a better user experience and/or help to arrest churn for SaaS. For example, machine learning can help to predict user preferences or behavior, then perhaps trigger alerts or actions when it appears the user is disengaging.

Enhanced security

Cloud security issues are always a hot topic among SaaS, and traditional security measures tend to be static, perimeter devices which require human input to update for new threats. AI gives SaaS the possibility of security services that can replicate and learn from new security threats automatically. Oracle has recently added machine learning and AI to their cloud security services, facilitating automated threat detection.

What does the future hold for SaaS with AI and machine learning? At a recent event, Oracle EVP and head of applications Steve Miranda said, “Two years from now, we’ll probably be talking about a whole new set of things in this category that probably none of us is even thinking about today.”

AI represents a new generation of SaaS products and the opportunity to embrace new ways to gain a market edge. We’re seeing many of the bigger players move into this space already and industry experts predict it will continue to grow.

Are AI and machine learning considerations for your SaaS? The market trends show that perhaps they should be…

Koombea builds engaging SaaS apps with the latest innovations. Talk to us about how we can help you today.

by Jonathan Tarud
Blog Post