For whatever reason, Google announced their automated car project on a Saturday afternoon. It almost feels like they were trying to bury this story, but there have been a ton of posts on this already. However, the focus has typically been on the “wow factor” of the project. TechCrunch has had plenty of posts already on this subject, but I am focusing on one, the one that talks about money:

That’s great. But Google is still a public company in the business of making money for its shareholders. So one can’t help but wonder what, if any, money-making prospects there are here?

This is an excellent question, how is Google planning to make money from this project? The post goes on to talk about how gaining time in our cars means we will have more time where we can use other Google products, and that is how this technology becomes a money-maker. These assumptions are fundamentally wrong, mainly because they are assuming there is something about this project that means incremental revenue to their existing streams.

The proof is in the original announcement:

To develop this technology, we gathered some of the very best engineers from the DARPA Challenges, a series of autonomous vehicle races organized by the U.S. Government.

Google tends to hire very talented people for their normal software engineering jobs. For this project, they went to get the best researchers in the world on the topic. Granted, Google has done similar hiring in the past, but it rarely touts the these people in part of a major announcement like this. It is normally a quote somewhere in the post from the project lead.

Another short paragraph points to the true potential of the project:

According to the World Health Organization, more than 1.2 million lives are lost every year in road traffic accidents. We believe our technology has the potential to cut that number, perhaps by as much as half. We’re also confident that self-driving cars will transform car sharing, significantly reducing car usage, as well as help create the new “highway trains of tomorrow.”

The scope of this project is to change the way our highways are driven. This is not about putting Android into the car so that you can use voice commands to call home. They are targeting the fundamental act of driving on the highway and they want to create the “highway trains of tomorrow” . To do this, you need to put your technology into a majority of the cars on the road.

Why is this such a potential home-run for revenue? Technology licensing. When academic institutions create new technology like this, there is a tendency to create a startup whose sole purpose is licensing the technology to the various companies that will build something to use the technology. This is not in the form of patents, it is more like selling software that is really expensive and getting recurring revenue from usage of the technology. The actual dollar figures are hard to project, but we can make some decent guesses.

First, the actual licensing of the technology is not where the money is made. They could license access to this for $10 million to various automobile manufacturers but that caps the one-time revenue fairly quickly. The recurring license revenue is what can be huge. Imagine if they charge manufacturers $1000 for each car that is built to include this technology. Car makers will easily make their money as there would likely be a significant price increase for these types of cars.

Why is $1000 per car such a big number? If you look at some basic information, you will see that there are a lot of cars on the road. Based on that information, you can assume there are approximately 10 million cars sold in the US annually. If each car gives Google $1000 in revenue, $10 billion in total revenue. This is not the same as their current advertising revenue, but this is a significant business by itself using the simplest calculations. If you assume that the US is only half of the world automobile market, then you could be looking at $20 billion in annual revenue. The more interesting part is that this revenue is fairly stable and will not fluctuate greatly from year-to-year.

These figures are assuming normal passenger vehicles, so if this software gets extended for other uses like trucks, manufacturing or construction, you could quickly get into the $100 billion range. People have been looking for the next Google for a few years. What if we just found out that the next Google is Google?

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