of a hypothetical manufacturer using hypothetical products from well-known brands, just a few years from now. (While Merrill Lynch, Grainger, and Expedia are real companies and may be working on chatbots, the bots in this scenario are invented representations of a fictional possible future.)
LIFE IN AN AI-POWERED WORLD
Allen Perkins feels powerful.
It is January of 2024. Perkins is the senior manufacturing manager for Hecker Heavy Locomotives, an Ohio company with a growing reputation for making the world’s highest-quality passenger train locomotives. Perkins feels powerful not because of the massive machines he helps to build, but because of the web of information that accommodates his every decision, whether at work or at home. His adept management of artificially intelligent resources has earned him a promotion, and now he must deliver.
As his self-driving Tesla heads for his office, Perkins can use the time to focus on his personal finances. The markets have been volatile, and he wonders if he should make any changes in his portfolio. He taps a button on the Tesla’s center console and speaks.
“Get me to Meryl,” he says.
“Meryl here,” a woman’s voice answers. Meryl is the bot for Bank of America/ Merrill Lynch, where Perkins’s investments reside. “What can I do for you today, Allen?”
“I’m a little nervous about the choppiness in the stock market. How am I doing these days?”
“Your net worth with us has risen by 2% in the last twelve months,” Meryl answers. “While the market has been going up and down by an average of half a percent a day for the last few weeks, we’ve got you in a pretty conservative mix of investments. So the value of your investments hasn’t been moving quite as much.”
“Are we on track with the kids’ college funds?”
“The investments for Ray and Sarah are likely to be sufficient to cover their tuition when they start college a few years from now,” Meryl replies. “I’ve been shifting those assets into more conservative positions because they’ll be in college so soon.”
“Is there a lot of cash in my account?”
“We’re about 10% in cash right now, Allen.”
“Can we invest some of that?”
“Sure, we could. But you’re going to need cash for that remodeling project you told me about last month. There’s not a whole lot lying around in your checking account right now. And don’t forget you just bought a bunch of new suits to go along with your promotion.”
“OK, leave the cash where it is,” Perkins says. “But let’s check back on this in a month or so. I may be getting a bonus.”
“Sure thing, Allen,” Meryl says. “Talk to you in February.”
Perkins’s Tesla pulls into a parking space near the front door and he strides into his office. After checking his emails, he begins the most important work of the day: selecting a new component supplier for six new locomotives for the California High-Speed Rail project.
He opens a browser and navigates to GraingerBot, a chatbot available from Grainger, one of the biggest suppliers to manufacturing companies like Hecker. He starts typing.
Hello, GraingerBot.
Hello, Mr. Perkins.
Let’s continue ordering parts for the California locomotives.
I have opened the file that we were working on yesterday. What would you like to work on?
Suspensions. Can you locate the suspension springs in the 3-D model?
I see eight helical springs that are 36.3 centimeters high.
What suppliers make springs like that?
Several make the chromium-vanadium steel specified in the drawings. But I’ve found some research that shows a new material may allow you to get more durability for the same cost. Shall I show it to you?
Please.
The GraingerBot pops up a twelve-page document from the International Journal of Engineering Research. Perkins reviews it and confirms that the GraingerBot is correct—this new material appears to be superior for this part. He resumes the typed conversation.
How many manufacturers can make this part from the new material?
Seven. That includes one parts supplier that you’ve already used for six other components; they’ll give you a discount if your order pushes the total over $35,000.
Get quotes on those, GraingerBot. And get a few quotes on the chromium-vanadium springs, too, just in case we decide to stick with them.
I’ll have those answers for you by 12:30. I’m connecting with the bots for those parts suppliers right now.
Perkins signs off. This has been productive. While he would have liked to complete the order for the springs now, it looks like he might have found a more durable material—and with Hecker now doing the maintenance as well as the manufacturing, that would save the company some serious cash.
Perkins turns his attention to an upcoming business trip. He is going to Sacramento to meet with the California transit team that is buying these locomotives. He puts on his Bluetooth headset and connects with Pete, his virtual travel agent from Expedia.
“Pete, get me a flight to Sacramento for next Tuesday.”
“Sure thing, Mr. Perkins,” says Pete. “When will you be returning?”
“Wednesday or Thursday. Look into both.”
“OK. I’m checking American Airlines, because that’s where you have the best status. I have 18 possible flight combinations. I’m afraid you will have to connect.”
“Yeah, nobody flies nonstop Dayton to Sacramento! Don’t route me through Chicago or Denver. Too much snow this time of year,” Perkins says.
“That leaves nine possible flights. Is this for the two o’clock meeting with the California rail project team?”
Perkins remembers that he has given Pete access to his schedule, and realizes the bot is figuring out flights that fit his existing appointments.
“Yes, that’s the meeting,” he says.
“I’ll make sure your flight gets in well before that. I see that one of your manufacturing partners is based in that area. In fact, it looks like GraingerBot is connecting with them right now to check on some springs. Should I set up a meeting?”
“Definitely. See if you can get me in to see them on Wednesday. I’d love to tour that facility.”
“Do you want to take a red-eye back?”
“No way,” Perkins replies. “Better make it Thursday morning.”
“OK, I see the best roundtrip now. It leaves at 7 a.m. on
