You’re probably in one of three boats when it comes to AI and Machine Learning:
- It’s not going to be a thing until 10 years from now. It’s overhyped.
- It’s making a large impact right now.
- I honestly don’t even understand what AI is. And what does Machine Learning have to do with anything?
At the moment, I’m in between #1 and #2. Right now, as we speak, AI and Machine Learning have the potential to make the biggest impact on businesses, and I’ve seen first hand how this is impacting companies of all sizes. Even if you have a company of 10 people, this technology can help accelerate your decision-making process.
What is clear, however, is that the companies preparing their applications to utilize AI and Machine Learning will exceed the rest.
But, first, I think it’s important to simply explain the difference between Machine Learning and AI.
Machine Learning is based on creating computer algorithms that allow computer programs to automatically improve through experience.
A steam engine doesn’t replace one horse, it gives you 1,000 horses. The same applies for Machine Learning. Machine Learning allows us to perform tasks and automate things we couldn’t before. Machine Learning doesn’t replace one person, it gives you the capability to do what you would have only been able to do if you had 1,000 people.
Artificial Intelligence (AI) is the science and engineering of making computers behave in ways that, until recently, we thought required human intelligence.
You’re Already Using AI and Machine Learning in Your Everyday Life
My wife sets multiple wake-up alarms on her iPhone. In the morning, when it goes off, she’ll press snooze a couple of times and then eventually wake up. She does this every day. Last night, before she went to sleep, her iPhone prompts her with “Set an alarm at 7:47 a.m.?”
The 7:47 a.m. alarm suggestion was because she sets alarms at 7:30 a.m. and 8 a.m., so the phone figured out that this was the ideal time for her to wake up based on her snooze activities and what time she’s actually waking up.
You know when you take a picture and Facebook already has suggestions on who to tag or when Google Maps prompts you with directions to home every time you leave work, that’s also AI and Machine Learning in action. Anytime you find yourself with a personalized experience, chances are, AI and Machine Learning are behind it.
Machine Learning and AI are all about predicting what’s going to happen and how it will better benefit the user.
Why Do You Need to Be Thinking About This?
When Amazon pledges to upskill 100,000 U.S. employees for in-demand jobs by 2025 and opens up a Machine Learning University, that’s sign #1. Amazon sees something that most businesses don’t. Machine Learning and AI are the future of how companies will deliver the biggest impact.
Even Microsoft is getting heavily involved in AI by investing $1 billion in an Artificial-Intelligence Startup OpenAI to develop technologies for its Azure cloud-computing system. To top that off, most in-demand jobs just happen to be Data Scientists, Data Engineers, and Software Developers.
Every Industry Can Benefit
The use cases are growing by the day and have a real impact on how companies can improve.
“Because of the wide applicability of AI across the economy, the types of use cases with the greatest value potential vary by sector. In consumer-facing industries such as retail, for example, marketing and sales is the area with the most value.
In industries such as advanced manufacturing, in which operational performance drives corporate performance, the greatest potential is in supply chain, logistics, and manufacturing,” McKinsey Global Institute, Notes from the AI frontier: Applications and value of deep learning
Here are a few examples:
Make angry customers happier, quicker.
You can use these capabilities to analyze the emotional tone and sentiment of your customer support calls. Instead of waiting for a customer to fill out a feedback form, you can detect if they’re angry on the phone call itself.
And if the system detects that a customer is angry on a customer support call, the company can automatically suggest that the customer rep reroute the customer to a different department better suited to handle it. Even better, if a customer is yelling at the automated system, you can use this knowledge to re-route them automatically to the best-suited department.
Increase conversion rates through deep personalization.
“You should also buy this” isn’t just a tool for Amazon. With AI tools offered by all the major cloud providers, developers can feed their systems data to come up with dynamic recommendations.
The tools are available for a company of any size, with the right development help, to make this happen. The goal, of course, is to increase personalization which leads to more products purchased.
Automate trend analysis.
Finding trends can also be really useful. For example, you could use this tech to show the fashion trends of everyone in the past three months who has walked through a SOHO neighborhood in New York City as well as everybody in Berlin. What are they wearing now and what were they wearing six months ago are all questions that can be solved using AI/ML.
Personalized shopping has potential for every retailer. Outdoor apparel retailer, Icebreaker, uncovered that its shoppers clicked on personalized product recommendations 40% more often than non-personalized ones, leading to 28% more revenue and an 11% increase in average order value.
It’s Available to Any Company and Industry (Not Just Large Tech Companies)
If you’re trying to build a system that will beat the best Chess and Go players in the world, then yes, Google is probably the only company that will create that system.
But, with AWS and other major cloud providers investing in AI and Machine Learning tools, it is taking less and less to develop incredible systems you couldn't possibly create with humans.
Instacart recently built a system to optimize the routing of its personal shoppers through grocery stores that delivered a 50% improvement. It was built by just three engineers using Google's open-source tools Keras and Tensorflow.
So the next time you think of Machine Learning and AI, don’t think this tech can’t apply to you. With the right engineering help, you can utilize these tools to make a big impact.
Start With a Proof of Concept
As Vokal grows, and new tech becomes available, we are always looking at new ways that digital can make an impact on corporations. We learn by prototyping and experimenting with new emerging tech.
With Augmented Reality (which is a form of AI), you can layer vision on top of your camera.
As a prototype, we created a way to layer data on top of a camera. So instead of picking your desk on a screen, you can get real-time information about what cubicles are available just by pointing your camera at an open office.
And we thought it would be interesting to see how we can match voice with text-only data. We utilized AI and Machine Learning to create a voice-activated application to understand deeper context of content in a scanned document.
The reality is that AI and Machine Learning are still in their infancy, and the major cloud providers are making it as easy as possible for developers to build on top of their core AI and Machine Learning platforms.
The ability for businesses to use this technology to make better predictions with their data and offer better experiences for their customers is a no-brainer.
Get started today, and of course, let us know if Vokal can help you.