Artificial intelligence (AI) and machine learning (ML) are evolving at a rapid pace. These technologies have the power to change the way businesses operate and humans interact. AI/ML are no longer outliers in 2022—this technology is being applied to virtually every industry, across virtually all categories, with such major players as Google, Facebook, and Amazon investing billions of dollars in research and development. As a result, AI/ML has already transformed a vast array of industries and for the ones it has not, it’s only a matter of time.
When it comes to AI/ML, the question I get a lot is, “What does the rapid impact and growth of this technology mean for how we build software going forward?” The answer is that it is changing almost everything about how we think about building software. For the past several decades, we’ve considered software to be a tool that automates the tasks you want to complete. It’s lifeless and does tasks for you and rarely sparks any emotion from the user. Thanks to AI/ML, software is now taking on a persona of its own. It can now be a mentor, a CFO, a friend, or a cheerleader.
#3: For example, when you book a certain number of workouts or services on my company’s platform, it can congratulate and encourage you, telling you that you’re well on your way to achieving your goal. We’re implementing this technology to improve how wellness businesses are operating, and also the overall consumer experience—and we want to use it to spark positive emotions for users. We don’t want it to be a dry robotic voice, we don’t want it to feel “artificial.”
As a business leader, you should start thinking about how AI/ML fits into your industry—if you aren’t already. Below, find three key factors to consider as this realm of technology continues to expand.
Think about voice and persona.
No matter what your industry, one of the first things you must consider when wading into the AI/ML world is what kind of voice and persona you want consumers to engage with when they use your products. Think of it almost as creating a character. Ask yourself, “What kind of person does my customer want to work with? What will his or her relationship be with this persona?” Is your persona that of an advisor? A colleague? A concierge?
In Mindbody’s case, our persona is that of an encouraging coach, someone cheerleading consumers throughout their personal wellness journey. On the B2B side of the platform, depending on the company, that persona could easily be shifted to fit a business advisor role, highlighting when an owner reaches their first $10K revenue month or other milestones. Wherever you land, make sure your AI voice properly represents your brand and meets the needs of your user.
Weightloss app Noom has struck what seems to me to be an ideal balance between psychology and technology, finding just the right voice for its AI-enabled efforts while making sure the all-important human touch isn’t lost.
It’s not a simple process. At Mindbody, we’re constantly refining our persona. One of the best ways to do this is to test it on yourselves. Does the voice you’ve developed work for you personally? If it doesn’t, go back to the drawing board.
Look At AI/ML from an EDI POV.
One size does not fit all—a truism that’s even more true when it comes to AI/ML. As you move forward with your efforts, prioritize looking at AI/ML from an equality, diversity, and inclusion (EDI) point of view. You want to make sure you’re getting diverse data sets—especially if your own current data set is not diverse.
If you don’t keep EDI in mind, you’re likely to continue building the same thing for the same people, over and over again. That’s the opposite of the growth you want to achieve. By testing with a diverse data set and getting input from a wide range of people, you will be able to build something for new audiences.
A major part of our overarching mission is to make wellness available and accessible for all people. We don’t have a single type of customer in mind. That’s why we try to expand our knowledge about people from all walks of life.
Remember that AI/ML is not just a specialized technology to solve new problems.
AI/ML is not just for self-driving cars. This is a technology that improves every workflow and every task your software supports. The idea of it being something used only for specialty scenarios is old school, to say the least. This is a technology integrating information and analyzing data, and using the resulting insights to bolster decision-making at virtually every level.
Say your software is as straightforward as risk management: AI/ML can calculate the risk level for earthquake insurance. If your application is designed to figure out the best flight plans for planes, AI/ML will help make that process as streamlined as possible. Truly this technology can improve any industry’s operations and the overall consumer experience.
If you think that leveraging AI/ML is beyond your reach or falls outside of your needs today, I urge you to reconsider.