AI Monthly: AI revolution is a marathon, not a sprint

Tech executives are very optimistic about the productivity gains Gen AI could bring. Meta chief Mark Zuckerberg recently stated that the technology is already able to do the work of mid-level developers, while Sam Altman, chief executive officer of OpenAI, says the first autonomous agents will enter the workforce this year.

Not only is Gen AI entering the workplace, it is also making a name for itself among consumers: it has reached the consciousness of billions of people with an unprecedented speed for a novel technology. In Denmark, for instance, 60% of the population has heard of ChatGPT (Reuters Institute). These figures are similar in France, Japan and the UK. However, many consumers are still unclear about the specific use cases of the technology. In Denmark, roughly 10% of the population uses ChatGPT at least once a week, while this is just below 20% in the US. In short, a lot of people have heard about the technology, but are unsure what it could do for them, or do not have much use for it in their everyday lives.

Although many consumers are not yet GenAI power users, many corporations have implemented the technology in their daily operations. In the first quarter of 2024, 21% of corporations used a generative AI software application (in production) and in the third quarter, 41% of corporations did. This increase is not just limited to the software domain: in IT, sales and marketing use cases in production and pilot among corporates have increased dramatically.

What's more, half of the interviewed corporations stated that GenAI already delivered business value in the short time it has been implemented. In addition, according to the Morgan Stanley CIO Survey, almost 70% of all large corporations will have piloted generative AI in some part of their operations. In short, we are starting to see the AI revolution take shape.

There is no doubt that generative AI is the next platform shift in tech, as increasing adoption rates among corporations show. Still, the implementation of the technology is a marathon and not a sprint for several reasons. It is good news that a lot of use cases have been identified and are now in production. However, scaling the technology at an affordable price will be a significant challenge, as investments have been enormous up to this point and will likely increase further this year.

Generative AI still faces significant challenges, such as data centre capacity and the availability of natural resources. Additionally, the recent headlines about its potential have raised concerns among developers. Developers, who make up a small fraction of the workforce and spend only about a third of their time coding, are not the only ones affected. Therefore, companies considering the use of generative AI applications should first ensure they have structured in-house data. Next, they should identify which areas of the business could benefit from generative AI. Only then should they consider running a pilot. Otherwise, it's like trying to run before you can walk.