There are a number of benefits that come from experience — or to be specific, learning from experience.

For example, I wrote recently about some parallels between the current state of AI and the early stages of the cloud computing market.

Another example, albeit flavoured with Schadenfreude, is watching large companies1 pivot their entire strategies every time the CIO changes. One CIO is all in on Vendor X, another is all in on Vendor Y — and so the dance of one vendor in, another vendor out, continues to play out on LinkedIn.

A very wandering path

I get how this churn can happen. Historically, CIOs didn’t have a very long tenure — although this is changing, with recent research showing average tenure for the top IT person increased from 6.3 years in 2023 to 7.3 years in 2024, as compared to as little as 3 years previously.

When CIOs could only plan three years ahead, that close horizon meant that new CIOs didn’t have much time to make their mark, so evaluations had to be cut short and over-hyped claims might go insufficiently tested. Instead, the focus had to be on bold claims and the promise of outsized results.

After all the excitement, the incoming vendor could never live up to the hype. Usually the failure modes fell into a couple of main categories:

  • Product’s features described over-optimistically: Maybe there was more custom configuration than is expected, or there was a dependency on something that was not part of the original scope, or maybe there turned out to be a lot of ongoing maintenance required. Either way, a few quarters in, nobody is happy and there are no concrete results to point to.
  • Project scope too broad: One of the hallmarks of the ambitious CIO’s pet project is the One True Platform that will work for everything and everyone everywhere. It’s very rare for this sort of thing to work out in practice; most broad platforms have both strong points and areas of weakness, and while the benefits of a comprehensive integrated platform may compensate for some of the weaknesses, this compensation only works as long as the weaknesses are not in areas that are strategic or particularly sensitive for the business.

And so, a few years later, a new CIO comes in, rips out the struggling platform of Vendor X, and pushes their own favoured solution from Vendor Y instead.

In full disclosure, I have never benefited from this cycle. In fact, a couple of times I have had an otherwise solid opportunity evaporate because of churn like this happening within prospective customers. The one silver lining is that I now have a spidey-sense for when these kinds of shenanigans are happening. At that point I find the best approach is to ask the question straight away: “Is there a deal here?” As a wise man told me, “‘No’ is my second-favourite answer!” A quick “no” lets me avoid a bunch of wasted work and heartbreak.

It all comes to a head

Right now there is a convergence happening, because all of the hype around GenAI means that both that it’s the obvious vehicle for an ambitious CIO wanting to make their mark, and there is real demand as boards and leaders of other functions are insistently asking IT people what they are doing with AI. VC-funded startups are writing memos to their investors detailing all of their AI-related activities — and you can be sure they are looking everywhere to find them. And the companies that are publicly funded are doing the same sort of thing, of course, in the press and in their keynote speeches.

Surfers trying to catch the next weave

Here is what happens next

Many of these AI initiatives will not be nearly as transformative as they are being built up to be. This is not a failure of the technology — although some of them will undoubtedly fail on that basis too; that’s intrinsic to experiments with novel technology. Some of them will be technical successes but fail to achieve adoption. And many of them will succeed but still fail to deliver on the transformation, simply because everyone ends up circling around the same set of use cases that turn out to work well and are relatively easy to implement without having to turn the whole organisation upside down.

In other words, they become the new table stakes.

Being the first business in your sector to move to the cloud was a game-changer and gave you a leg up on your competitors. Suddenly you were inside their decision loop, able to execute your strategy faster and pivot more rapidly to respond to changes in the market. But that advantage only lasted until all of the competitors also moved to the cloud (or got eaten up or left for dead by those who did). At that point, everyone had to find other avenues of competition, because there was no longer any meaningful acceleration to be had from simply being “in the cloud”.

AI will undoubtedly go the same way. If you’re the only one building software tools 10x faster2, that’s a huge advantage. Once all of your (surviving) competitors are also operating at that speed, there is no longer any advantage to be had simply from “doing AI”.

The danger of getting too far ahead

There is a particular risk to technological innovation, and it is that vendors cannot force the pace of innovation on their own. Customer organisations have to be ready to take advantage of what vendors are offering. When they are not adequately prepared, the result is news stories criticising the new technology for not delivering value, either at all, or not as much as was promised. Sound familiar?

Back in the early days of cloud adoption, this lack of readiness on the part of customers generally boiled down to treating the cloud like on-premises hardware they were used to. In these early days of GenAI adoption, the equivalent behaviour is focusing just on the most immediate point of application of the AI, without considering the whole process which that step is embedded in. What other steps need to be changed, which can maybe be skipped entirely, and which ones will have to be reinforced?

This tendency to apply existing categories to novel concepts is not a failure; rather, it’s an entirely normal and natural behaviour. Humans, upon encountering a new thing, first of all try to figure out how to fit it into the categories they already have in their minds. At one point the giraffe were called (by people who lived far away from its usual habitat) camelopardus — a “camel-leopard” — because the intersection of those two categories was the closest fit for it.

In fact this human tendency is even useful, because it means that we can get on with doing things without always having to work everything out from first principles, which while fun for a certain type of person, is not always the most practical response In the heat of the moment. However there is a transition point where someone has to go “hang on, that’s not really a camel-leopard, it’s a whole other type of animal!” and then act on that insight.

Vendors proposing a new technology can act to guide the market and their customers to success. That process is complicated and messy, irreducibly so, and if anyone is telling you that adopting a new technology — cloud, AI, or whatever comes next — is going to be easy, straightforward, quick, and painless, is LYING and you should immediately eject them from the premises. Unfortunately in these days of sales calls conducted over Zoom you can no longer release the hounds, and I think we are all worse off because of that.

🖼️  Photos by Amanshu Raikwar and Silas Baisch on Unsplash

  1. I am not going to name names here for the obvious reason that this sometimes feels like a very small industry, and I would like to continue to be gainfully employed in it for a while yet. ↩

  2. Yes yes, generating code faster without changing the rest of the pipeline just moves the bottleneck, but people will figure out what the new software development lifecycle best practices are in a world where everyone has access to AI. For more on that topic, I just recorded one of my Coffee Talk videos about patterns in AI adoption. ↩