This month we're taking a decidedly different direction for our interchange session. We're going to delve into the question of artificial intelligence and the importance of beginning to experiment and adopt it right away….

Listed below is an article from Seth Godin, the point of which is that if we wait until AI is fully developed or integrated to implement it, we will all be behind the curve. He cites examples from the past in different industries where people were slow to implement new ideas or technologies and fell behind their competitors. It seems to me that given the speed with which AI is coming at us, if we don't jump in right away it will pass us like a freight train … the reference to the railroad industry is ironic and maybe appropriate.

Also attached is an article from Microsoft entitled “Will AI fix work?” In it you will see there are three findings:

First is the concept of digital debt, and the premise that digital debt is costing us innovation. My summary of what they're saying is that we have so much information; emails, podcasts, meeting notes, who knows what else, coming at us that we feel like debtors trying to dig out. I myself spend a significant amount of time every day trying to empty my inbox… for the sake of emptying my inbox. It's a great example of the tradeoff between urgency and importance.  Most of what is in my inbox feels urgent but is not important to the success of our business. Nevertheless I devote so much time to reducing digital debt that I have little energy left over to be creative. It's taken me three days to find the time and energy to write this e-mail as an example. So this brings us to the following questions:

1. What impact is digital debt having on you?

2. How might digital debt be contributing to burnout in your organization?

3. What might you do to reduce digital debt?

The other two findings in Microsoft's article are: 1. that employees are eager to use AI to reduce their workload, and 2. Therefore every employee needs AI aptitude. I believe that collectively we are interested in how AI could benefit us, but at the same time we’re a little intimidated at the prospect of plunging into it. Just yesterday I used an AI based app to take notes of a Zoom meeting I had with one of the interchange participants and write a summary. I found myself hesitant to use it …worried about what it might do. So these two points combined lead me to the following questions:

1. How might you launch AI in your organization?

2. How might you help people get over the intimidation factor if in fact that is a factor?

The 77% threshold

When the gas car was first introduced, it couldn’t compete with horses. After all, we’d had thousands of years to optimize our systems around horseback, and this new technology was still nascent. Roads were rare, gas stations were scarce and the cars themselves were unreliable.The same thing happened again when electric cars made a comeback a hundred years later. At first, they had limited range, limited space, low acceleration and charging was a hassle.

When a new technology arrives, it is almost always at a systemic disadvantage. If we wait until the new thing is better than the old thing, we’re taking a big risk. That’s because we have competitors who will spend the time to learn the new tech, and more importantly, build systems around it. They will gain customers you may have trouble getting back. They have a head start that can last a generation.

Herbie Hancock started experimenting with electronic instruments a decade before many of his peers. That enabled him to create not one but two of the most successful jazz singles of all time. If the local landscaping contractor sneers at electric weed whackers and leaf blowers because they’re not quite as cost-effective in the short run, they’ll probably lose some customers, and won’t develop what they need to know when the technology and systems catch up. And the new systems will catch up.

The same goes for media companies that are defending a model of expensive content that’s ad-supported, refusing to consider that it might not last. How much longer will Vogue matter?

When there’s an iterative cycle of new technology, the systems can’t help but improve, and the tech is likely to as well.When a new tech or system is 50% as effective as the old one, it’s our job to learn it and understand it. And when it hits 77%, we ought to consider creating a new division, a new product line or a new approach that adopts it. By the time it catches up, we’re either part of it or we’re too late.