In 2011, two Stanford students, Jorge Heraud and Lee Redden, decided to build an AI weed-killing machine and launched a company called Blue River. The company made a device with cameras, herbicide dispensers, and a computer that analyzed images in real time and triggered the dispensing. Farmers would tow this device across the field with a tractor, thus eliminating weeds with great precision, saving on the herbicide, and growing eco-friendly crops.
Blue River Technology
The crux of the system was the AI model accuracy – if the system did not kill weeds, the farmer would suffer yield losses.
The founders started working on this challenge by going to the fields and taking some cabbage and weed photos with their mobile phones. The first AI model was trained on this very limited dataset, and its accuracy was not very impressive. Yet, it was enough to convince a couple of farmers to give their system a try.
As the farmers were towing the device across their fields, Blue River was getting more images from its cameras. Then the company retrained the model on this extended dataset. The new model was still far from perfect, but it was better than the initial one, and the improvement was convincing enough for another handful of farmers. As they started using the device, Blue River added their images to the dataset and trained a new model.
Over time, Blue River collected a unique dataset of crop and weed images nobody else had. Google and other AI giants could have had more AI experts and more powerful hardware, but they did not have Blue River’s data. In 2017, John Deere acquired Blue River for 305 million dollars.
A competitive advantage is something your competitor cannot quickly copy. In the world of VC capital abundance, open science, and a global talent pool, engineering features do not provide such a competitive defense. The competitive advantage usually comes from some asymmetry: a resource, knowledge, or intellectual property that your competitor cannot quickly acquire. A recent prominence in AI position and value for the global business primarily comes from the ability of AI to turn the data your company has into a competitive advantage.
As your company develops, it acquires internal operational, market, and customer data. The best source of competitive advantage is customer data since that involves real customers and cannot be easily substituted with open-source or commercially accessible datasets. If you can build a feature that gets better with every new customer, you might be laying a foundation for a bright future for your entire enterprise.
The phenomenon that some products become more valuable with the growth of the customer base is known in economics as a network effect. It has been studied since the middle of the 20th century. The primary example was an early phone company: the more phone users you have, the more valuable your phone service offering gets for all of them. In the most recent history, the “big tech” companies’ not-so-secret sauce is the network effects underlying their core products. The “wintel” PC standard of Intel-powered IBM PC clones running Windows incentivized software developers to write software for Windows, and the more software supports Windows, the more valuable the operating system becomes to the users. This phenomenon made Microsoft the behemoth it is today and turned Bill Gates into one of the richest people in the world. Google search and ad placement business get better with more users as the company carefully analyzes the responses to the search results and ads and adjusts its algorithms. And obviously, Facebook and other social medial platforms bring more value to every user as more people join them.
AI technologies extend the opportunities for taking on network effect dramatically and thus open many new niches and competing strategies in various markets – the Blue River example demonstrates how the network effect could be grown literally off the cabbage field.
Being built right, the AI competitive advantage results in competitors perceiving your business in the following frame.
To compete with your company, I need to build a better product than yours.
To build a better product than yours, I need to get more data than you do.
To get more data than you do, I need to get more customers than you do.
To get more customers than you do, I need to have a better product than yours. Proven impossible by contradiction.
Yet, arbitrary AI features do not contribute to building such a competitive defense. To develop a competitive advantage, the AI strategy should be aligned with the product strategy and be a part of the general business strategy. AI businesses have not the first but the fastest mover advantage – those companies that get the right AI cycle in place and acquire the right customer data eventually win, outcompeting those already on the market.
This blog is dedicated to AI competitive advantage, and we are doing our best to explain how it works and how you can build one for your product or company. You can check our other posts to get an extensive explanation of what the network effect is and how AI enables it, how to build an AI competitive advantage for your company, what culture helps you build the right AI products, what to avoid in your AI strategy and execution, and more.
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