The short answer seems to be “Yes.”

This isn’t really a new idea at this point. But I wanted to offer my take on it as I don’t think I’ve seen a good overall summary and I wanted to offer one.

The deeper questions seem to be: How will it hurt? How much? And what will Search companies and Publishers do in response? While Generative AI is different from Traditional Search and has different use cases, some aspects are taking market share from traditional search. According to Similarweb back in 2023 “ChatGPT Grew Another 55.8% in March, Overtaking Bing.” And there’s the early 2024 prediction by Gartner of Search volume dropping 25% by 2026. Then AdWeek said that Google’s use of AI alone could hit publishers with a $2B annual ad revenue loss.

This will likely continue and is somewhat ironic. Search will take market share hits because someone else is using content that isn’t theirs to create value. Sound familiar? Seems like the foot is on the other shoe. And yet, while Search might be facing some disruption, their core value propositions remain just fine. Also, they typically are integrated with several products; e.g., Google across web, video, maps, and more. The real question is how they’ll deploy billions to respond, not that anything’s replacing them soon. Still, with hundreds of billions at stake, even a small percentage hit is non-trivial. (Even if Google is growing ad revenue faster than others lately.) We should be more concerned with the smaller search engines and the publishers themselves.

I’m a huge fan of LLMs… but this will be some of the subtle dark side. This isn’t an attempt to show AI doing horrid things. No. My concern is more subtle. It’s about insidious degradation of thought; in spite of the awesome power of AI to also help us learn and produce new things. My concern is that AI, eventually feeding upon itself, will regress us to average faster than ever.

We may be reaching the point where fraud and fakes are becoming so prevalent that the costs and pain are overwhelming enough that we’re ready to take the effort to try new solutions. Blockchain technology might finally have a mass market use here. But we’re not quite there. Except for crypto most of the work has been in infrastructure. Consumer use cases are few. This might be a natural evolution. The progression from infrastructure to platforms to applications is a movie we’ve seen before. And consumers likely don’t see safety and security issues as the most fun to deal with. At a certain point though, the answer to “where do you want to take the pain” turns into “ok, we have to deal with this now.”

The challenge remains getting adoption when there’s serious effort. After all, isn’t it annoying enough to have to identify how many traffic lights are in a picture just to get to your own account somewhere? Well, dealing with today’s crop of blockchain identity solutions is a bit more of a hurdle. At least for now. You may be thinking, “But don’t we already have all manner of fraud solutions, from credit checks to heuristic rules and now even AI trust scores?” Yes we do. And how is all that working for us?

There are a fair number of articles on whether to choose a platform or a point solution. But what if you’re choosing to build one or the other? Some startup work I’ve been doing lately has wrestled with this challenge. So I thought I’d share some of the considerations.

Lessons come at us from many directions. Some – at least for me – have been most valuable when applying something to one area that came from a completely different area. Here’s a handful of thoughts I’ve found that cross over from aviation into business.

So why not force return to office? There’s clearly benefits to the traditional model, right? Well, it should be obvious at this point there’s a great many benefits for remote work and hybrid options – at least for roles where it’s possible – for both employees and employers. (See Remote Work Statistics & Trends.) Potentially reduced costs on both sides, better work/life balance for employees, wider range of talent selection, etc. (However, note that cost reduction might be less than originally thought; stipends for remote gear, travel costs for team meetings that might not otherwise have been necessary, etc. So cost issues will as always be highly situational.)

Welcome to Part 2 in this series. When I started Part 1, I had no idea how quickly a whole lot of thoughts would flow regarding the cross-over utility of some ideas from sometimes time-pressured or higher-stakes fields into general product management.

Train How You Fight

Another great line from a fire instructor, “You can never train too hard for a job that can kill you.” This stresses the importance of realistic training that prepares firefighters for real-life scenarios. And train we do. Beyond initial training, we have weekly sessions, special classes, and more. In aviation there’s recurrent medical and flight checks, etc. Now, in corporate, there are hopefully less things that will kill you than in emergency response situations. But there are systems and equipment breakdowns. There are high-stakes situations. Are you prepared? Have you practiced scenarios? Or is the book up there on the shelf getting dusty? The problem with risk mitigation is you don’t make money from it. It’s value preserving, not value accretive. It’s a cost item, not a revenue item. Backup systems, security efforts are necessary, but they are on the cost side. Regardless, the only way to be really ready is training. Some say – with some validity – that’s what insurance is for; to buy away risk. And yet, is that responsible? Is it ethical? Maybe. It depends on your situation. You have to assess that. It’s not all gloom and doom though. There’s items on the plus side here. What about customer training / onboarding? Or sales? Whether it’s to mitigate bad outcomes or drive towards good ones, are you constantly learning? The better the training, the better the game is likely to go. Train how you fight.