You have to admit – in tech, FOMO is very real. There’s a huge focus on keeping up on trends or having the latest devices. Being on the “cutting edge” and working with emerging tech is what most people strive for. And we get it. Tech is a real passion and nobody wants to be perceived to be falling behind. Especially not companies always trying to eke out a competitive edge. But is there a flip side?
It’s not always the first to market that dominate it. This has been demonstrated several times over in the world of tech giants. Often the companies that take the time to test and work through the bugs before they release end up gaining more of the market share. The simple truth is that while people like to have the latest products, they need to work!
With AI becoming more end user focussed, there has been a mad rush to integrate it into existing software and products. There’s a relatively strong business case to leverage the benefits of AI, but is it applicable to every product or service?
Yes, AI can work with large volumes of data in a way that humans can’t and at a speed that they can’t even begin to match. But in rushing to integrate AI into applications, how much thought has been given to whether it always adds real value to users? Do they really need or want another AI prompt telling them to make it better?
AI can do a lot, very effectively, but it takes a great deal of time and effort to make it work. Rushing to release an AI integration just to keep up to other market players is likely to end up with oversights.
AI can only do what it’s been trained to do. It may know how to process data but often lacks context. It doesn’t always understand why a user chose a specific parameter or wants a specific outcome.
Also, AI is only as good as the data it has to work with. Flawed or incomplete data is not going to generate a good result. If it takes a human to identify and correct the mistakes, is it really more efficient than if they’d done the whole process in the first place?
The main premise of AI integrations is that they help humans become more efficient at what they do. There’s also an assumption that what AI produces will be better and therefore people will want it. It doesn’t always define what “better” really looks like.
It’s like developing a new version of an egg slicer and insisting that this new egg slicer is what everyone needs. Then, when someone says: “Hey I don’t even eat boiled eggs, why would I want an egg slicer?”, companies are shocked that people don’t appreciate all the hard work that went into building it.
AI has many great use cases. Does this mean every company should integrate it? Programming needs to be well thought through. Integrations need to be designed and tested with a thorough understanding of what people are really looking for. It’s not about what AI can do, but rather what users need. When tempted to give into the AI FOMO, maybe this should be the main focus.
