Among many trends, AI’s continuing rollout and use in the enterprise ranks near the top. I recently read an article in CMO.com on their Six Artificial Intelligence Predictions. I wanted to highlight what they said and react to it myself based on what we are seeing in the market. It’s worth it to read what CMO.com has to say.
Better Understanding of Context
The author, Alistair Cole, suggests that having data can improve results with a better experience.
In 2018, there are myriad sources for this information. It can be gleaned from shared content, human interactions, and device sensors—and used to generate more accurate views of real-time context.
It’s this data that’s fuelling the current phase of machine learning, one that has resulted in a dramatic decrease in the cost of prediction, thereby making it accessible to many brands. This new capability enables companies to fill gaps in their data, pattern-match more effectively, and forecast what customers might do next.
Frankly, I couldn’t agree more. How often do we all get the first “offer” from a company and it doesn’t come close to anything I would want. I hit a commerce site to do some research and three weeks later, advertisements still plague me. I view a product and ultimately buy it. Months later, I’m still asked if I want it. Credit Card companies, hotels, and airlines constantly send me emails with special experiences suggesting that I would really enjoy a wine tasting (don’t imbibe) or should attend a Taylor Swift concerts (I was born in the 80’s…)
So yes, context is king. The faster AI’s can take advantage of already existing data, the sooner, we can get on with our lives. The good news is that we are seeing much better predictive capabilities and learning from AI’s.
More Tailored Experiences
To quote Mr. Cole:
And we know that recommendations keep customers engaged longer. An Engine report about the state of the U.K.’s top 25 e-commerce fashion brands revealed that sites offering product recommendations saw 140% more page views and 10% higher task completion rates.
Credit Card companies, hotels, and airlines constantly send me emails with special experiences suggesting that I would really enjoy a wine tasting (don’t imbibe) or should attend a Taylor Swift concerts (I was born in the 80’s…) Imagine the world if the context discussed above with the tailored experiences means I would get the almost perfect experience: a Tears for Fears concert not in wine country but in Nashville during a beautiful fall night.
One thing will keep these first two items from becoming a short-term reality, data. Companies have it. They just have a hard time getting it to the right place where it can be analyzed and then acting on it. AI will have to be paired with Big Data (implied I know) and personalization engines to make this all work right. The building blocks exist. companies just need to take advantage of them.
Complex Task Automation
Having just seen a few demos from CRM vendors, I can understand how we stand on the cusp of AI helping with this. Alistair Cole has another example that’s interesting:
Airbnb has a track-record of innovation and has recently turned its attention to developing tools that streamline the design process. The company is building an early prototype of an AI-powered product development tool that, in real time, turns design sketches into product source code.
This hints at the employment implications for previously white collar jobs as well.
Logistics Support
The CMO article highlights Coca Cola’s use of AI to determine where to place vending machines. I’m not going to quibble about the difference between AI and predictive analytics because the two are related. We are seeing many more companies use these insights to do all sorts of interesting things:
- Determine when a part will fail and schedule a service call before then and when a service tech is in the area
- Determine placement of printers in an office
- etc.
So I’m going to rank this as closer to reality than some other predictions.
Computer Collaboration
Now this AI and human collaboration has possibilities. Here’s what Alistair sees in the retail world.
Few brands have embraced working intimately with machines. One that has is Stitch Fix, the online personal styling platform that converts $1 billion in sales annually and listed on the Nasdaq in November. The monthly subscription service is powered by recommendations that are generated by humans and AI working in harmony.
Customers provide preferences through style surveys, measurements, and Pinterest boards. The AI algorithms digest this unstructured information and pass recommendations to the company’s 3,000 fashion stylists. These human experts send out five items from a variety of brands, and returned items help improve the system.
In healthcare, they are plowing ahead with diagnosis tools to better assist a physician determine the underlying cause and hone treatment. This also is closer to reality although it depends on the industry. It will be those at the forefront working on this type of scenario.
The Changing Workforce
This is the last point but it could also act as the bottom line. To quote the article:
The acceleration in technological change means one thing for humans—we have to adapt, which is fine, because it’s all we’ve ever done, and we’re pretty good at it. Since the dawn of time (development of the first tool, mastery of fire, cross the oceans, etc.), we’ve courted what’s dangerous, tamed it, and turned it to our advantage.
This year AI will begin to change the workforce. It will open up your company to faster digital transformation. It will also change what your employees do and what types of jobs you offer.
