Reading Time: 11 minutes

The legendary football coach Nick Saban has seen tremendous success on the NCAA football scene. His teams have dominated the highest levels of the sport for almost 20 years. In that time, the sport has changed dramatically. From ground and pound offenses of the 00’s to the record-setting air raids of the last few years, Saban’s teams have had to pivot and in some cases dramatically change strategies even when the current strategy was still working! The result? The most dominant school in the sport’s storied history, and a resume for Saban that is rivaled by no one.

At this point, you might be wondering how that illustration relates to the title of this post. How do Nick Saban and college football relate to a “smart enterprise”? Well, I’m glad you asked (even if I did put the words in your mouth)!

latest report
Learn why we are the Leaders in API management and iPaaS

To connect these two dots, we have to first ask what a “smart enterprise” is? What changes an enterprise from being like every other business, and makes it “smart”? Is it just having AI in your business and keeping up with all the hip terms like “data science,” “machine learning,” and “neural networks” or is there something more to it?

The short answer is no. Smart enterprises aren’t defined by having AI capabilities, but by how they use them! Just having AI in your business is not enough. This tech isn’t exactly new, but only a few businesses have implemented the technology and become “smart enterprises.” 

Nick Saban and his football teams are respected for their “process,” a method of focusing their organizations on things they can control. This scenario is no different, other than being business instead of football. Businesses that successfully become “smart” follow a process as well.

For this post, I’ve distilled this process down into a three-part mission statement for becoming a smart enterprise.

#1 Customer experience

First and foremost, businesses that make this transition use AI to create better customer experiences. This isn’t as simple as it initially sounds, but it’s also not so complex as to be out of reach. It’s not sufficient to just have a recommendation engine in your product or targeted offers delivered by mass email. Customers want to feel valued, whether their consumers or other businesses. A business that seeks to be good to its customers makes a difference. 

Relating back to our opening example, Saban notes in his books that he focuses his teams on “developing the product.” While football teams don’t have to worry so much about customer retention, they do need to build a quality product every year so that their fans have something enjoyable to watch. Businesses that make the transition to smart enterprises focus on using AI to develop their product and create great customer experiences.

While AI can create powerful experiences for customers, a “smart enterprise” must be thinking first of the customer and not the immediate impact to their bottom line. I’ve seen customer-facing AI implementations become intrusive and downright annoying at times. While it might meet the customer’s needs, it will actually detract from the customer experience if if it’s not implemented correctly. While bottom-line focus is definitely important in optimizing your business, it doesn’t drive growth and innovation. Focusing on wisely augmenting customer experience with AI will create brand loyalty and ambassadors that you don’t have to pay!

#2 Employee engagement

Secondly, these businesses create positive employee engagement through their use of AI. It’s often said to employees that they are “the company’s biggest asset,” but how often do they actually feel that? In the last decade, we’ve seen pretty significant growth in the capabilities of intelligent systems. “Smart Enterprises” leverage AI to allow employees to focus on more valuable work through things like RPA and decision augmentation. You hire smart people into your company, let them think and innovate for you! 

This doesn’t just apply to those expensive and admittedly smart “data scientists.” Innovation can come from anywhere, and while not everyone may be capable of building an AI system, you never know where the next great innovation in your business will come from. What does this mean? Data science and AI teams should be horizontally aligned so they can have the pulse on innovation across the business not just within IT or analytics. 

#3 Wise use of AI

Finally, these businesses are committed to wise and effective use of AI. They aren’t just implementing it as a “party trick,” they’re committed to making AI an effective piece of their organization and wisely considering it’s implementation without rushing into it. 

One of the flavors this takes is ethics. Consider the ethics of the use case before implementation. There have been far too many stories in the news over the past few years where businesses failed to consider the ethical problems and the results were catastrophic. One that comes to mind from a couple years ago is an AI system that was unleashed on Twitter to interact with users and became horribly racist! The implications of a poorly thought-out AI implementation warrant careful consideration of their impact both to your business and more broadly to society as a whole. 

I want to tie this whole post by returning to our example from the beginning and talking about what implementation of this mission statement looks like. As I mentioned earlier, Nick Saban is respected for his “process.” The process involves controlling the things that you can control, and focusing on doing what you can without being focused solely on the outcome. You might have noticed that none of the three pieces of my “mission statement” include market research or competitive analysis directly. That’s not because they aren’t important, but because the market and competition can’t be directly controlled! I’ve seen too many companies decide to build AI into their business solely because their competitors were doing it, or because they thought the market was demanding it! Often these implementations fail. Remember, it’s not about just having AI but about effectively using it to create great customer experiences and positive employee engagement.

In the next post, I’ll explore how API-led architecture goes hand-in-hand with a good AI implementation. API-led AI will help transform your business into a “smart enterprise” to create great customer and employee engagement and drive effective use of AI in your business.
To learn how to create a data-driven business, take a look at this whitepaper to begin your journey in becoming a smart enterprise.

Series NavigationWhat Do Integration and AI Have in Common? >>