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Closing the AI Gap: A Critical Opportunity for Enterprise Software Companies

4 minute read
Kaj van de Loo avatar
Why are so many vendors failing to incorporate AI capabilities into their software?

Artificial intelligence (AI) is everywhere. Its applications are plentiful and far-reaching, and its growth seems to be pandemic-proof. IDC forecasted that, even in the face of an economic downturn, the AI market would grow by 12.3% in 2020.

But there is a notable gap in where AI is taking hold. Enterprise software companies are lacking when it comes to building AI directly into their applications to create a more personalized experience for users. The majority of enterprise applications, like those for customer relationship management (CRM), enterprise resource planning (ERP), video conferencing, instant messaging and more still rely on a traditional interaction model. This model requires the user initiate actions versus AI working proactively to provide a better user experience, for example, by making recommendations. 

The product managers, product designers and application developers responsible for building these applications will increasingly get access to more AI capabilities. As this happens, we can expect to see AI more frequently incorporated into existing applications, bringing AI-based features to the workplace at large. Companies that get on board stand to benefit greatly, and those that do not will eventually be pushed out.

Let’s examine the reasons behind this gap, and how giving AI precedence can take enterprise applications to the next level. 

Related Article: Fact vs. Fiction: Artificial Intelligence in Digital Marketing

Why Aren’t All Software Companies Already Incorporating AI?

So, why aren’t all enterprise software companies building AI into their products by default?

There are a few reasons. 

Although the technology to do so has been around for a while, it can get lost in software companies’ long list of priorities. Additionally, some companies tend to get stuck on iterating on the current features of their product based on customer feedback. Getting bogged down with incremental improvements can keep software companies from seeing the bigger picture of how AI can benefit their customers. 

To some extent, AI has also been shrouded as a separate entity. It conjures up images of a dozen PhDs working siloed in the back room of an organization to create a machine the likes of an IBM Watson. But, in reality, it’s simply a matter of taking the time to build the correct capabilities and algorithms into products that already exist. And doing so will be vital for software companies to fend off the next wave of competition. 

Related Article: The 4 Foundations of Responsible AI

Learning Opportunities

Artificial Intelligence Opportunities Are Everywhere 

AI — particularly machine learning algorithms — are a powerful tool for creating better user experiences. By continuously looking at the data within a system, these algorithms gain insights regarding which users might be interested in certain data, which users should be doing what, and much more. By anticipating the user’s needs, and proactively providing suggestions or taking actions based on data, AI-based features can save humans time and prevent mistakes. 

For example, have you ever forgotten to record an important video conference call? Once you realize it’s too late, there’s no going back. Best case scenario, you have to interrupt the meeting to begin recording, only to end up with a partial recording. 

A machine learning algorithm can examine every video conference call you’ve ever had, including information on when you’ve recorded, played back those recordings, length of the call time, who the call was with, and more. It can then take that data and either begin recording automatically, or issue a pop up alert asking whether you’d like to record your call. Sounds handy, right? 

More importantly, these algorithms can learn from user feedback. If the pop up alert is declined by the user, say, on all calls that happen on Wednesday, it would quickly learn not to ask whether to record calls that day of the week. The user would also have the choice if and when to enable this feature in the first place. 

This is just one example of how AI-based features can anticipate a user's needs, prevent human error, and learn from users’ actions to provide more value in the future. But its utility extends to many other scenarios. Think email software that alerts you to extra-important messages. Work productivity software that reminds you to complete a task when it’s taken you longer than usual to address. Messaging software that flags conversations you should chime in on. The possibilities are endless. 

Related Article: 3 Misconceptions About AI in Marketing

AI or the Highway

As AI becomes more pervasive, companies that don’t prioritize building it into their products will become irrelevant. When it comes to increasing productivity and improving user experience, there’s no substitute for software that engages with and learns from its users. Human-initiated interaction models will continue to fall by the wayside as enterprise software with AI-powered features becomes the industry standard for companies wanting to empower end users.

About the author

Kaj van de Loo

Kaj van de Loo is CTO at UserTesting, a human insights platform. He runs everything from design and product management to engineering and operations.

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