I'm seeing a lot of that in my own job. Every company has a top-down mandate to use more AI and a budget to back it up, my employer included. But we write software. Now this means we are chasing the AI dragon making LLM-based software in the hopes that we can capitalize on the hype. I would be more charitable in my description if I thought we were going after the high value targets, but our marketing strategy is literally "AI in everything". I'm all for selling what the customer wants to buy, but I don't think that's actually what we are making. Trying to make everything at once means making none of it well.
There's a huge disconnect between what customers think AI will do for them and what we are actually capable of delivering. When customers and colleagues alike complain that something doesn't work well and ask how we are going to fix it I have to keep reminding them "this is an open area of research in the field; nobody has found a solution to this yet." Nobody likes hearing that, but it's the truth.
It reminds me a lot of the dotcom bubble. People thought they could get rich just my making a web site that talked about their company. Even many of the biggest most successful early movers failed completely. We can all agree today that the Internet has provided tremendous value and really has changed the world, but not in the way most people thought it would then. Most of the startups being started didn't have a business plan beyond "it's on the web" and that's where I see a lot of the AI development right now. They think making the technology makes it profitable without asking what problems it solves better than our existing solutions. Some of what we are developing shows potential, but a lot of it is a solution in search of a problem.
It's definitely resulting in opportunity costs as we pour money and people into projects that only exist because we can put AI in the name, taking priority over projects that we had already planned and vetted with customers and market research. For a company that prides itself on slow and steady progress and long term stability, we sure are jumping head first into AI solutions and we are doing so at a rate that precludes any kind of design, testing, or quality control. We are selling shaky prototypes and our customers are happily paying for them. Everyone on both sides is so blinded by the hype that they are setting aside everything they've learned over decades of experience and success.
I can't wait for the hype to end so we can start talking about where LLMs and other generative AI are actually useful.
There's a huge disconnect between what customers think AI will do for them and what we are actually capable of delivering. When customers and colleagues alike complain that something doesn't work well and ask how we are going to fix it I have to keep reminding them "this is an open area of research in the field; nobody has found a solution to this yet." Nobody likes hearing that, but it's the truth.
It reminds me a lot of the dotcom bubble. People thought they could get rich just my making a web site that talked about their company. Even many of the biggest most successful early movers failed completely. We can all agree today that the Internet has provided tremendous value and really has changed the world, but not in the way most people thought it would then. Most of the startups being started didn't have a business plan beyond "it's on the web" and that's where I see a lot of the AI development right now. They think making the technology makes it profitable without asking what problems it solves better than our existing solutions. Some of what we are developing shows potential, but a lot of it is a solution in search of a problem.
It's definitely resulting in opportunity costs as we pour money and people into projects that only exist because we can put AI in the name, taking priority over projects that we had already planned and vetted with customers and market research. For a company that prides itself on slow and steady progress and long term stability, we sure are jumping head first into AI solutions and we are doing so at a rate that precludes any kind of design, testing, or quality control. We are selling shaky prototypes and our customers are happily paying for them. Everyone on both sides is so blinded by the hype that they are setting aside everything they've learned over decades of experience and success.
I can't wait for the hype to end so we can start talking about where LLMs and other generative AI are actually useful.