76061.3663@compuserve.com
That odd configuration of numbers was my very first email address — from before email addresses could be personalized with identifiers as wild as our names. The older among you will remember those days. The younger ones will react the way my kids do. They assume any email sent via an address like that was etched onto a clay tablet and thrown out the window.
At that time, Compuserve was a giant in the internet space, competing with Prodigy and AOL, among others. The basis of their competition? Who had the best stuff inside their walled garden.
There was no World Wide Web. When I logged onto Compuserve (the familiar song of a dial up modem in the background) I was met with a bunch of icons for things like news, sports, games,etc. The reason someone would choose one of these competitors over the other was based on who had the best stuff inside their walled garden. It was like imposing the network TV content model onto the internet. Why choose ABC, NBC or CBS? Because you liked their programming better.
Why do I bring this up?
I’ve been in three meetings in the past two weeks where AI fatigue was a real factor. In each case, the topic of AI and its impact on the automotive industry was brought up, and quickly batted down. In one conversation, someone correctly noted that Canadian auto dealer magazine covered AI as our May cover story, so why did we need to continue to push it? As pleased as I always am to come across an avid reader, let’s be clear: Yes, AI was our May cover story. And no, we haven’t fully covered the topic. We have only scratched the surface.
I’m not surprised at the fatigue. So far we’ve all seen variations of articles, podcasts and other commentary that tell us how AI will completely change the world, and that we may already be behind. Panic stations, folks!
Actually, no.
It’s not time for panic stations but nor is it time to look away. We need to keep participating so that we can understand where AI is heading, how it is changing things, and how our businesses should plan, test and implement. It’s time to find articles, examples, presentations that make sense to you. Given how much is being produced on the topic, there is certainly plenty you can choose to ignore.
So for what it’s worth, here are a few of my rules of thumb as I try to figure out a learning and implementation plan through this. You might find some of these useful to your own journey:
I remind myself that at this stage in the timeline of the internet’s development, we were still guessing at what the real impacts would be. Remember the phrase “killer app,” like there were going to be a few applications that would really be impactful. That turned out to be wrong. Instead, the internet changed everything, and for the most part, in ways we didn’t foresee early on.
I accept that I can’t read everything. I have a full time job and a family. I’d like to keep both. So I’ve picked a few key sources that have become a habit for me. I squeeze all I can from them, and then scan lots of others to see what catches my eye. Over time my list of key sources will change, of course, but for now it’s really only a handful. More than that, and it becomes too much.
I balance the sense of urgency with the need to plan thoughtfully. Early adopters likely do have a chance to gain competitive advantage, but some of that advantage is coming from making and learning from mistakes, not from being the first to stake out a position your competitors can’t match. In fact, I think highly effective AI applications and use cases will get broadly adopted very quickly so playing fields will level. We’ll all use the tools. Those that win will be the ones that use them better.
I’m wary of anyone who says they have an application or unique selling proposition that is both hugely powerful and that no-one else has thought of. Sorry, that just doesn’t make sense to me. Given what Meta, OpenAI and others are spending on recruitment of engineers, visionaries and others, it’s fair to say I expect to see a lot of the wins coming from big players first. Given the very nature of artificial intelligence, it seems to me that this is a game where scale matters.
One last thing (For now. I will come back to this topic whether you like it or not): Listen to this podcast from the AI Daily Brief: Artificial Intelligence News (from one of my “habits”). It’s 23 minutes well spent, even if it seems a bit at odds with what I’ve already written. I don’t think it is: Why Your Company Needs to Move Faster on AI. You can find it easily on YouTube with the information I provided.
