Obviously, as we have these massive advances in technology, entrepreneurs and business leaders are looking at how to use them for business.
I’m not going to go over 111 of these – that’s just a turn of phrase to highlight how Infinite the possibilities are with artificial intelligence today. The set of capabilities are expanding, as I’m going to point out a bit later. That has big ramifications for business.
But let’s lay out some of the fundamental ways that businesses are achieving more with artificial intelligence…
Engagement and Production
These are two fundamental pillars of how AI is transforming business. One is engagement – sales, customer service, outreach, AI helping the business to interact with its target audience.
The other is production – productivity, employee capability, efficiency, etc.
Both of these have a big role to play in terms of how we use AI to our advantage in business. For instance, these resources looking at customer service efficiencies focus on the first set of metrics, while so many other programs are more tuned to insider statistics, like how much product people can crank out in a day.
“With the help of AI, companies can gather insights into individual customers’ behavior, preferences, and needs in real time,” writes an unnamed analyst at Radar27. “This allows for targeted messaging and offerings that are more likely to resonate with each customer.”
That’s more on the engagement side, but the productivity is obviously important, too.
So look out for both of these in AI applications to business.
Human-Centered Applications
Some business experts also point out that you need to have these systems focused on how to support people. Human-centered design is important, because so many of these types of AI innovations are assistive to business people. They’re not replacing people. They’re helping people to work smarter, not harder. They’re decision support tools, not automatons that will build their own companies.
We should all keep that in mind as deployment happens.
The Value of a Pilot Program
There’s also the value of building things experimentally, to see what works.
This came up in a conversation I had recently with Andrew Ng about applying AI to business.
“The cost of experimentation has plummeted, because AI assisted prototyping is actually very efficient,” Ng said. I was interviewing him in a segment of our Imagination in Action conference at Davos, where so many people were getting together to come up with solutions to global issues. So I’m seeing a lot of businesses reorganize themselves to run many experiments and then, in a systematic way, to get the resources to then grow to scale. But I think this is an important process (for) many businesses to go through.”
I also wrote earlier this week about two pilot projects that Davos panelists talked about in a recent discussion moderated by Katie Rae of the Engine, and attended by an impressive set of MIT-affiliated people. Leah Ellis from Sublime talked about a pilot plant for green cement production, and Ally Yost from CFS talked about a pilot plant for fusion energy.
Both of these illustrate that concept that, as Ng also pointed out, prototypes are more possible now with AI, and digital twins can help us forecast what’s going to happen when we build something.
Other ROI Drivers
Ng had more to tell us about the business context of AI.
“Intel is using AI to help retailers with pricing analytics, helping increase profitability …. helping with legal compliance using (AI for) cross-border trade, but all around Davos, I’m seeing a lot of these valuable discussions of implementations of AI that are already starting to drive positive business ROI,” he said.
We talked about how AI can either double revenue, or cut it in half, which reminds me of the age-old axiom, that new tech should help, not hinder, a workforce, and that design is important.
It’s also important, Ng noted, to figure out what a competitor will do, and to think about what your company’s moat is, as things change quickly.
“A lot of this will be hard work, to figure out for your business, with your data, with your customer relations, with your assets, what are the unique things you could do that will build sustainable advantage … because the landscape has shifted, it also creates these competitive threats. So I’ve seen all the smart CEOs thinking through how to run internal processes to come up with ideas.”
I thought was an astute look at some of the conversation that’s happening in business.
Two Great Institutions
At the end of our talk, I suggested that MIT and Stanford should both be involved in a collaborative effort to move the ball forward.
Ng agreed.
“I think this has been an amazing event,” he said. “And having Stanford and MIT, both institutions that we’re privileged to have ties (to), seems like a wonderful thing to me.”
This was one of the more interesting moments at our IIA event in January, in looking at what the business impact of AI is likely to be soon.
