AI and Machine Learning in Practice

AI needs to be strategic. Playing with AI on the edges and deploying small prototypes and pilots isn’t going to help revolutionize your business model. Rather, taking a long look at your current business and deciding where AI has the potential to make the most significant impact is the way truly benefit from the machine learning revolution.

According to Bernard Marr, author and strategic advisor, we’re on the brink of a modern industrial revolution. He outlines some of the ways in which we may see the evolving uses of data in our everyday business life. Let’s take a look.

While AI has been around for about 50 years, we’ve never had the amount of data that we have today. Now, we merely give the algorithm data, and the machine figures it out without our direct input. Challenges remain, but those obstacles are similar to human obstacles, such as translations. And as data sets increase, those obstacles are getting smaller.

Since many of the systems are black boxes, we don’t always have the transparency we need to get these algorithms to scale. Companies are, fortunately, getting better at creating algorithms that are freely available.

[Related article: Innovators and Regulators Collaborate on Book Tackling AI’s Black Box Problem]

How AI Impacts Industry

Marr can’t think of a single area where machine learning isn’t changing everything we know, and cites fashion as a somewhat counterintuitive example. In the past, it was an entirely manual industry, using human labor for the entire pipeline from creation to implementation to sales.

Now that we have smarter products and services, the way a fashion organization performs is largely automated. Processes such as 3D printed customized shoes, for example, demonstrate how a service can be both automatized and fully customizable.

We also have smart clothing. With the number of internet-connected things slated to rise to as many as 200 billion items in the next three to five years, we can now have clothing to measure pulse rate, analyze your movements, and other options. Such innovations may transform how we interact with our clothing.

Even the humble subscription box has been transformed. StitchFix uses AI machine algorithms to identify your ideal clothing and personalize your box for style choices chosen just for you. We are using AI to automate a business model altogether.

Revising Your Business Model

This revolution will require complete revisions of business models. Slapping AI onto your existing structures may not be the best way to make use of these strategies.

• how you use AI to deliver products and services
• how you use AI to improve internal processes

Without these two components, you’re not making real use of AI.

In one hypothetical case, the smart diaper is a revision of how we think of diapers. A smart diaper that tells you when to change the diaper may not be what you’re really looking for. Why would you buy it? You already know when your baby is wet.

Revamping the business model could see smart diapers taking stock of urine and stool samples to send to the cloud for medical analysis. You can see a complete picture of your baby’s hydration levels or the sodium in their diet. It can also predict through machine learning the developments of infections before it actually happens. Now, you’re listening.

A real-life example of this transformation is John Deere. The famed tractor company embraced machine learning to help farmers know when, how, and what to plant using sensors that analyzed the soil. These sensors could also make recommendations about fertilization and then predictions about crop yields using external data.

Other companies using smart technology include Spotify with music recommendations, Disney with smart bands that both give you access and allow them to track customer movement, or FitBit with picture-based calorie predictions.

AI Automation

Companies are using AI to draw customers to their option. For example, elevators could make use of AI to schedule predictive maintenance. They also use AI to deliver real value, as with insurance companies who can tell you when you’re paying too much or a company that sends you a notice for when your deal is expiring, giving you time for negotiation.

Thanks to the incipient data revolution, concepts that may seem like science fiction are becoming reality. In Dubai, contractors are currently bidding for a project to have automated drones for transportation. In the same way you’d order an Uber now, you’ll be able to order your driverless drone. According to the Crown Prince, this service will be ready in soon as the next three years.

The automation of business process allows humans to get back to what adds value to the business. The deep value is the realm of humans, and machine learning can take the place of that massive amount of human labor dedicated to all the business minutia.

Even things like analyst reports from websites like Forbes are automated through natural language processing. Readers require much larger amounts of consumable data interpretation than what humans could produce, so machines analyze data and churn out those reports, giving human staff more time to write in-depth pieces. No one even spots the difference.

[Related article: Automated Machine Learning: Myth Versus Reality]

Preparing For The Fourth Industrial Revolution

Marr believes that businesses have to be smart about how they implement AI. Haphazard implementation is expensive and time consuming without delivering any real results. Looking at how AI can improve customer deliverables or the back end of your business and deciding where AI can have the most impact is the way forward. You must have an AI strategy in place now.

This video was taken at ODSC East 2018 — attend ODSC London 2019 this April 30 to May 3 for more unique content! Subscribe to our YouTube channel for more videos taken at past conferences.