How AI Is Changing The Game
AI, and the economics of SEO
SEO success really comes down to two things: choosing what to write, and writing it well. Byword handles the latter of these two, and so the focus really shifts onto the former: choosing what inputs to give Byword.
Traditional SEO has long worked by compiling a large list of search terms that are relevant to a particular brand, and filtering for those that are high-volume (meaning the rewards of ranking are high) and low-competition (the chances of ranking are high).
Underneath this equation lies the unit economics of human content production. It costs a certain amount to pay a human to write a piece, and so brands would typically only write content to rank on terms that were sufficiently high volume. If a term is too low volume, it could be the case that it's just not economical for a brand to pay a human to write content around that term, even if position #1 on the results page was guaranteed.
Since the rise of AI language models over the past few years, it's become substantially cheaper to write content that can rank on SEO. This has effectively made a whole host of search terms suddenly economically viable to write for, and which weren't viable previously due to the much higher costs of human writers.
We're currently at somewhat of an arbitrage moment in SEO, where well-equipped brands using AI content production can rank on these terms with relative ease. The fact that they are terms that haven't been covered well previously means that they are low-competition, and simply having relevant content covering the topic is in many cases sufficient to rank well.