Truth is, and this applies to all companies regardless of size, is that you don't have to be first, best, biggest, fastest, or most well-known in order to win market share that out-paces your investment. The AI pie is going to be very, very big. To estimate this size, let's take McKinseys rough estimates of job displacement (~30% of ~60% of jobs, ~20% of work) and use that to estimate the actualized [US, apologies] GDP that can at some point be attributed to AI: it is in the 4-5 trillion range using today's figures.
To say a market that large will be owned by only 4-5 companies doesn't make sense. Let's take the PC market for example: there are roughly 6 companies that make up ~80% of the market, sure. However, let's look at a tiny participant compared to the total market (~65B): iBuyPower at rank #77 had sales of 40MM or 0.06% (small, expected) of the market with a much smaller capital investment. If look at this percent compared to 5T, we would be at 3B. While the 5B investment stated in the headline could result in a lower ranking and smaller share, the point stands that there is still a lot of money to be made on the long tail. Even if Anthropic fails, there will be other companies with similar infusions that succeed.
The AI (LLM) market as a whole is very immature, trying to guess today what it will look like in a decade based on the investments/behaviour of the first couple movers is pretty foolish. Even predicting for a specific submarket (ie, consumer LLM products like ChatGPT) is hard enough. Who knows what other categories could develop and be dominated by companies who narrow in on them and once the R&D progress starts flatlining like it always does.
It is not clear if (i) a lot of the surplus will be captured by the AI providers and (ii) that the impact will be anywhere as big as people now guess/want it to be. Making a bet on the future is fine, of course.
You don't need to just take one source. OpenAI authored their own paper [1] on the economic impacts of just LLMs: "Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted."
Goldman Sachs Research just pushlished their own analysis as well. [2] Their conclusions are "As tools using advances in natural language processing work their way into businesses and society, they could drive a 7% (or almost $7 trillion) increase in global GDP and lift productivity growth by 1.5 percentage points over a 10-year period." and "Analyzing databases detailing the task content of over 900 occupations, our economists estimate that roughly two-thirds of U.S. occupations are exposed to some degree of automation by AI. They further estimate that, of those occupations that are exposed, roughly a quarter to as much as half of their workload could be replaced."
From [1]: "In our study, we employ annotators who are familiar with LLM capabilities. However, this group is not occupationally diverse, potentially leading to biased judgments regarding LLMs’ reliability and effectiveness in performing tasks within unfamiliar occupations."
From [2]: "Analyzing databases detailing the task content of over 900 occupations, our economists estimate that roughly two-thirds of U.S. occupations are exposed to some degree of automation by AI."
These are people who do not understand the jobs they are claiming AI will do. Ultimately, I think they are not doing much better than guessing.
We’ve got a lot of data scientist talent but I wouldn’t put a lot of stock in this particular estimate. If McK is gonna produce a novel insight it’s usually derived from having the input of many businesses across an industry and experience looking at their problems. It’s hard to imagine this one isn’t more or less made up due to the number of assumptions required.
Likely not much and assuredly wrong, I just wanted to ground my argument with numbers that came from people who presumably did more research than I was willing to do for an HN post.
If anything McKinsey has a lot to gain from exaggerating the numbers so more companies come to them for AI solutions or whatever their next consulting product is.
Although a large total addressable market (TAM) is very alluring, know that most markets are dominated by a few players. For example, sugary beverages (Coca Cola), office software (Microsoft), or luxury sports cars (Ferrari). Exceptions are markets where companies cannot find a moat such as air travel or farming. In those markets, profit margins are tin.
At this point in time, it’s hard to tell whether moats will arise around large language models. Peter Tiels thinks so or he wouldn’t have invested (see his Competition is For Losers presentation).
What is unlikely is that semi-good companies will thrive. Maybe for a few years but at some point the smaller players will be pushed out of the market or need to find a specific niche. Just look at cars to see this. Around 1900 there were hundreds of car brands.
These studies seem to be largely focused on job displacement. There is is a reasonable likelihood that AI grows the overall economy.
I think we forget that our perspective of AI now is comparative, probably to that of a preindustrial worker worried about machines. Displacement, sure but complete replacement seems a non nuanced view of how it may all turn out.
To say a market that large will be owned by only 4-5 companies doesn't make sense. Let's take the PC market for example: there are roughly 6 companies that make up ~80% of the market, sure. However, let's look at a tiny participant compared to the total market (~65B): iBuyPower at rank #77 had sales of 40MM or 0.06% (small, expected) of the market with a much smaller capital investment. If look at this percent compared to 5T, we would be at 3B. While the 5B investment stated in the headline could result in a lower ranking and smaller share, the point stands that there is still a lot of money to be made on the long tail. Even if Anthropic fails, there will be other companies with similar infusions that succeed.