Will generative AI be for businesses what ketchup is for fast-food?  

At the end of the 19th century and the beginning of the 20th, the world was going through the second industrial revolution. Every day, piles of new applications appeared on the desks of patent offices. Everyone wanted to invent something. We know examples of completely misguided ideas supposedly meant to make our lives easier or to make our work more productive and easier. From this time comes the most famous statement that "everything that can be invented has already been invented". This statement is attributed to Charles H. Duell, an American lawyer and government official who served as Commissioner of the United States Patent and Trademark Office (USPTO) from 1898 to 1901. Regardless of whether he said this or not, there is some irony in it. In most cases, inventions or rationalization designs are invented by people to improve existing solutions. Even the concept of innovation comes down to transferring a solution that works in one area (sector) to another, making it more effective. 

In January 2024 , I conducted a survey on LinkedIn asking where the biggest benefit of generative AI is seen. Of course, the survey is not representative, but I think it well reflects the current market trend. 67% of responses indicate that generative AI will be used to increase work efficiency (it should make the work I do easier), 19% and 13% respectively for making my life easier and developing my skills. These responses do not surprise me and confirm the research conducted by the Organisation for Economic Co-operation and Development (OECD) and the International Labour Organization (ILO). Looking at history, particularly the turn of the 19th and 20th centuries, over 70% of patents were issued for work-easing solutions. Wait a moment. Isn't the greatest fear of introducing AI or other modern technologies the loss of jobs? Of course, it is. It was, is, and will be because progress forces us to adapt and learn entirely new things useful in new conditions. This can be called development, competence change, or simply adaptation.

A few days ago, I had a discussion with one of my friends about why AI is a hot topic now. We pointed to solutions that have been working for at least 10 years, making our lives easier or our work more pleasant. And it's all based on AI. So why is there so much talk about generative AI now? Do companies need to find another topic for development (with the failure of METAVERSE, although I think in a few months it will be loud again when you can buy a new Apple VisionPro), or perhaps because technology company employees are being laid off en masse (though we are talking about single percentages and according to star theory those more administrative than substantive).In my opinion, about which I have already written in several previous articles, three conditions have been met. Cheap, quick results, and most importantly, easy to use. This is what generative AI is today. There is one more interesting (though not surprising) element. Dozens of organizations and startups are springing up, creating their own often open-source solutions. Most of them are trying to address some specific productivity enhancement problem or a scalable use case. One can certainly compare the patent fever with what is happening today. However, there is one significant difference that we do not notice at first glance. Boredom. After the crazy signing up of users for OpenAI subscriptions, the number of users in the last month has fallen by over 10%. And it will fall.

Those who saw the potential for REPEATABLE improvement, easing their work, will use it. Those who wanted to try but didn't change their habits will stop using or change the platform to see something new. Just like 20th-century inventions, some are with us today, while others have been forgotten. Those who stayed and are part of everyday life either changed our habits or cemented them. The same thing happened with the Google search engine or social networks. They're like bottle caps or straws for a frappuccino. We don't think, we just use – automatically. Generative AI and most of the use cases currently being tested will tend to hide (white label), weave between currently used solutions, and converge with other technologies. They will be like syrup for a drink or ketchup for fast food. Then we will stop asking ourselves whether AI will destroy us, replace us at work, and whether it will have a negative impact on our lives. Today we don't ask these questions when we think about the Internet. And what's more, we don't blame the Internet (as a technology) for pathologies or negative effects. We blame users for using it badly. And I wish the same for generative AI, that we could blame people for misuse, not the technology itself.