Gen AI price changes in 2024

There seems to be a disconnect between forward-looking communications from CEOs or other senior people and what we see actually happening in companies.

Almost all CEOs say that generative AI will be very transformative. The business will be restructured. There is a lot in the press with examples of companies making big investments in generative AI. But much of this comes in the form of technology companies.

For example, consider the chips that power AI. There is a huge rush to build data centers and compute capacity to run generative AI models. These are the hardware players.

But when we look at actual usage in large organizations, who is using Gen AI? What is the gen AI wave creating?

At this point, it appears that much of the money being spent is not for businesses that use it. The actual consumption of generative AI by companies and individuals seems to be quite limited.

Yes, some generative AI applications have gone into production. But as I’ve blogged about in the past, it doesn’t look like a large proportion of those pilots that companies experienced in 2023 will go into production in 2024.

Where does the disconnection come from? We see tech companies making big spends, but there is limited visible use in business. There is no over consumption.

I think it’s very likely that most of the visible spending for compute capacity was created in anticipation of big companies moving quickly to adopt Gen AI broadly. And if it doesn’t happen like that? Are we looking for a premature set of investments?

The facts on the ground do not support the thesis that large organizations will be the main consumers. So we effectively have two sources of disconnect: those who sell generic AI and those who consume it.

Therefore, it is unlikely that we will see deep and large-scale adoption of gen AI in enterprises by 2024. This is not to say that we will not see examples of it having an impact. But in terms of broad consumption, no.

In addition, there is a rhetorical gap between senior managers and the companies they lead. Senior leaders may back off on their rhetoric over time. But now it is unknown how long it will take. They can leave a point of exuberance and enter a cycle of practical reality that does not match the exuberance.

As a result, gen AI prices will likely fall. We already see Microsoft lowering its price in multiple ways. It’s making its generic AI offering, Copilot, available to consumers and small businesses. It is also lowering the threshold for companies in terms of the number of places they must buy.

Basically, Microsoft is lowering the price for consumers instead of businesses. Effectively, the company is trying to segment the generic AI market and charge different prices in different parts of the market.

This premium pricing strategy makes sense. If consumption isn’t there to support it, we could start to see prices come down much more aggressively.

Another reason we could see the current prices of many of the models drop is that product companies are trying to price based on value rather than usage. They argue that this is a very powerful technology and creates a lot of commercial value; therefore, they can charge a high price for it.

History has not been kind to these models. Pricing models tend to follow the cost of production rather than the use of technology.

Another factor is that many pricing vehicles are complicated. They use several variables to calculate the time and some combination of seats that allow people to use IT for tokens when people actually use the product. This is in addition to traditional software costs.

This complexity must be resolved with much simpler models potentially a software and usage model. This will likely further lower the effective price of gen AI as companies and individuals move into 2024.

As I said, premium pricing is often based on value rather than cost of use. It may be that product companies set up compute capacity believing that a big wave is coming. But a more modest wave of consumption is likely. So there are sunk costs and excess capacity will drive prices down.

This does not mean that the AI ​​gene has a significant impact. Rather, it appears that companies and individuals will need time to absorb the implications that apply to their businesses and their own lives.

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