The 4 AI Narratives: No Wonder We Are Confused

Let's dive into these narratives.

We are now in mid-November 2025 and there now seem to be four narratives that are dominating news cycles when it comes to AI. None of these narratives fully aligns to any of the others, which seems to be creating a lot of confusion. Let’s try to sort though them.

The Technical Narrative

This is what dominates the “technical” community. AI is replicating what we first saw to some extent when the Internet started, and much more clearly when Big Data came to the fore around 2010. A set of new technologies has emerged that are clearly going to be in demand. The “tech bro’s” – the people who make a living from technologies – immediately understood that they needed to get AI on their resumes to stay relevant and command greater salaries during the inevitable growth phase of AI adoption.

These are not only programmer types, but also anyone needed to make AI successful. Management consultants providing strategic advice on AI, learning and development companies teaching AI skills, AI Governance professionals, and a myriad of others have all jumped on the AI bandwagon.

There is still a high level of evolution in AI technologies which requires this broader technical community to keep up with advances. For instance, initially there was Generative AI, and then Agentic AI appeared. There are plenty of all sorts of changes going on all the time. This rate of innovation requires constant attention that creates its own kind of enthusiasm among practitioners.

The newsflows from the companies that are developing AI technologies and the hyperscalers bolster the technical narrative massively. Overall, it is very positive and hopeful.

The Financial Narrative

AI is not just about technology, but also about money, or rather, credit. In the hyperfinancialized US economy the opportunities are seen as not just the technologies themselves but the ability to construct debt-based structures around AI. For instance, the financing of data centers with debt is a rapidly rising concern. Coreweave, an AI Cloud infrastructure company, lost 50% of its market value in the past month due to doubts about its ability to get the data centers built.

There is also a big controversy on how to amortize the depreciation of GPUs that is affecting many players in the AI infrastructure space. The effective lifespan of a GPU is not just a technical question – it affects the financial models built into the debt-based financing. This in turn elevates financial risk, which will inevitably lead to a rise in financing costs – or worse.

There is a lot more to the financial narrative, but suffice it to say that it is now very gloomy. There is talk of an “AI Bubble” – meaning a financial bubble that has nothing to do with technology. But you can see how this pessimism gets conflated with the extreme optimism of the technical narrative to cause confusion.

The Economic Narrative

The economic narrative has changed over the time since the end of 2022 when it first became apparent that new AI technologies were appearing. Initially, it seemed that AI would generate new opportunities for all, but especially the technical community as they would be needed to make it work.

However, it has become increasingly apparent that there is no single “killer use case” for AI that will generate massive economic gains across a broad range of economic sectors. Instead, we hear a lot about efficiency gains. In other words, people will be fired from their jobs and replaced by AI. Such efficiency gains will improve the bottom lines of companies. Something similar happened in the “downsizing” wave of the late 1980’s, when PC’s eliminated the need for secretarial support and a lot of middle managers.

But the big losers are developers. Based on anecdotes I have heard dating back to 2022, it was developers who were the first target. The legions of developers and the inefficient project management techniques used to develop software were seen as a huge problem by the leaders of technology companies. With AI able to generate code, what required a team of developers can now be done by one very competent person using AI coding assistants.

More suspiciously, we hear news of large-scale layoffs in many industries blamed on AI. It is suspicious because there is not the wide-scale adoption of AI that would trigger this. It seems that AI is an excuse rather than a reason, but it is certainly adding to the economic narrative.

What is not part of this narrative is my personal observation that AI is being used to solution a myriad of use cases that are very diverse, and have little in common. It seems to me that in these use cases AI is doing things that no human does today because it would be economically impossible. I have heard this from others too. However, it is not part of the economic narrative, which remains a mix of enthusiasm and gloom, trending gloomy.

The Infrastructure / Commodities Narrative

This narrative is definitely out there, but is not quite as prominent as the others.

AI does not live in isolation, but in data centers. Data centers are infrastructure that needs to be built and operated. The operation requires electricity – and lots of it. Electricity has to be generated from a source of energy, e.g. oil, natural gas. The electrical generation capacity has to exist, along with the transmission capability. This requires a lot of mechanical parts, like gas turbines. These in turn require commodities like copper , silver, and aluminum, as well as construction equipment and supplies. There is also the entire legal framework like permitting to be considered as data centers are built out. And don’t forget the engineers to build it all, of which the US produces rather few.

The part of this narrative that seems to be getting most attention is electrical demand. Ordinary people are seeing their electricity bills rise, and are blaming AI for it. The narrative is also leading a lot of people to ask if we can build all this infrastructure giving the lack of a solid manufacturing base, not to mention the timeframes involved. This narrative is making people hostile to AI, or the tech companies purveying it.

Too Many Narratives

There may be other AI narratives out there in the world (e.g. national security, general brain rot, AI enabled scams), but these 4 alone are driving confusion. Is AI a good thing, or bad thing? What are the priorities? What are the risks? How will it affect me and my family?

I am not sure we are going to get a coherent national AI strategy that will rationalize all these narratives. At the moment it seems we are letting evolution take its course, and will all just have to witness the outcome. After that, history can deal with the narratives.