AI - Taking Digitalization's Promise Further


In last week’s blog post we looked at the main benefits that digitalization can generate for companies that are willing to invest time and energy in leveraging new technologies in order to enhance their performance and market presence. This week I think it would be both interesting and useful to have a look at the newest component of the digitalization mix (and one of the most tossed around phrases as of late), Artificial Intelligence. The reason is that despite it having captured the minds and imaginations of many people only a small section of the public actually understand what AI is. Out of those, a smaller fraction yet can glimpse the business uses that hide within its subfields. So, today we’ll be exploring what AI is and then look at some of its most valuable business uses in order to understand why companies should add AI to their internal agenda.  

First of all, what is AI?  

Simply put, AI is an area of computer science that aims to create machines capable of intelligent behavior, e.g. solve a task they weren’t specifically programmed to solve. A machine exhibiting human-like behaviour is called general AI and at this point we’re still quite far away from creating one. Nonetheless, and this is where it gets exciting, there are many different instances of narrow AI being successfully deployed in business scenarios. Narrow AI refers to machines performing rather complex, yet still explicit tasks incredibly well, much better than humans or even conventional algorithms. Given more time to mature and gain broader exposure, it’s expected that instances of narrow AI in business scenarios will multiply at an exponential rate in the next decade.  

Now we have a little more background on the subject matter. So what are some of the main artificial intelligence technologies available today and how are early adopters employing them? 

The first item on the list is speech recognition. You might be thinking is that really AI? Well the answer is yes! Getting machines to make sense of natural language is a massive field and the reason is its applications carry serious implications. The AI subfield behind voice recognition is called deep learning. Grossly oversimplifying, it allows a machine to “learn” by analyzing incredibly large data sets, making predictions on an outcome, and then honing its predictions to the point of virtual perfection. 

Where does this come in handy? Imagine interacting with any device in the world by speech. Actually, you need not imagine anything, simply take your phone out and ask Google Now for directions. That’s AI right there, machines displaying human-like capabilities – after all, what’s more human than speech? The business applications of this are far-reaching. Because your voice is a unique trait, it could potentially be leveraged with great success in the financial services industry to add an extra layer of security. In this era of ever increasing hacking threats, a powerful authentication step enabled by voice recognition technology would be most welcome. For all we know, it may be right around the corner.  

Another fantastic application is phone and online chat bots. This has really helped elevate many businesses’ customer experience to a new level. The big winners here? Us, the public, who are no longer dependent on there being a free agent to talk to us. Virtual assistants are also an important development. I referenced Google Now already, but there are others out there and they’re getting ever more intelligent. When you allow for the IoT taking a hold in years to come, that vision of telling your devices what you want from them becomes a lot more solid.  

The second AI technology I want to mention is computer vision. This is some really cutting edge technology and its implications are staggering. Currently this is being used by Tesla, who shocked the world almost two years back by launching a self-driving car, but the technology is rapidly being pursued by other carmakers. Beyond the novelty points, this feature is a proper unique selling point, one that’s bound to show on more and more people’s radars. In taking steps to deploy it to their automobiles, manufacturers are actively fighting to ensure their survival in the future marketplace.  

Other areas where computer vision is seeing fantastic results is in the manufacturing industry. Industrial robots working side by side with humans holds much potential for improving the manufacturing cycle time, all the while minimizing accidents on the assembly lines. Industrial giants like Germany and Japan are investing heavily in enhancing their production lines with teams of so-called cobots. These human-robot teams combine benefits from both worlds to ultimately drive more value for their companies. Currently limited to factories, these types of partnerships may eventually become established in traditional outdoors activities like search and rescue, emergency relief, and counter-terrorism to name but a few. 

The last technology I want to mention is predictive modeling. This may not evoke quite the same vivid images as the other two, but it is undoubtedly just as important. Though you may not realize it, predictability has proven to be one of our species’ both great goal and enabler. You see, science’s big promise is being able to predict things. In order to take hold, civilization itself requires peace and order, therefore you could say a certain amount of predictability is needed if is to flourish (the assurance that if wronged, for instance, you will be offered compensation in the court of law). Put simply, being able to predict things is intrinsically valuable. Once you recognize this fact, the possibilities afforded by AI’s powerful predictive analytics modeling suddenly stand out as the huge opportunity that it is.  

Many people have already taken notice. Currently this technology is helping insurance companies to build accurate customer profiles, which allows them to offer cheaper, more attractive insurance plans. But charging people just the right amount for insurance isn’t the end of it. The tech giants have been at it for years now. You witness this technology at work every time you start typing something very specific in your search bar only to have your search engine offer you the full phrase, question format and everything. That’s AI at work, showcasing what it’s learned from countless previous searches, connecting your search history both old and recent, and performing what seems like a mind-reading act.  

Predictive modeling can be applied to most fields with decidedly positive results. In fact, that’s the thing about AI technologies, they won’t just sit quietly on the side. No, in the years and decades to come they will become a vital component of everything. AI will define our era. Predictive maintenance is already taking off in the airline industry. Astrophysics is employing it; it’s proving invaluable in genetics. Predictive modeling is even used to get a better idea of the effects of climate change, and the list can go on. 

What does the future hold? At a minimum, present applications will improve considerably. But judging from the speed of developments around us today, I think it’s safe to assume in years to come we’ll witness AI being deployed as part of ever more important functions. The increased visibility will undoubtedly help to familiarize people with the concept. As any instinctive push back slowly subsides, it’s likely we’ll see AI take a core role in critical fields such as healthcare, the military and even counter-intelligence. The possible applications are almost endless.