Royston G King has spent close to a decade in digital marketing, long enough to have watched search engine optimisation become the dominant discipline in his field and then watch its foundations shift. Here he explains what he thinks practitioners are still getting wrong about AI-driven discovery.
For most of the past two decades the question of how a business appeared online had a stable answer. Search engines returned a list, users chose from it, and improving position within that list became a well documented profession with an established set of techniques. Royston G King built a substantial part of his career inside that system, and has been direct that the system has changed underneath the people working in it.
King began in digital marketing while studying business administration at the University of Southern California, founded his own firm in 2018, and was later named to the Forbes 30 Under 30 Monaco list. He has advised more than 1,000 clients across over 100 industries in markets including North America, Europe, Asia Pacific and Australia.
“A search engine gives you options and lets you decide. A generative system just gives you the answer,” said Royston G King. “That sounds like a small difference and it is not. It removes the moment where somebody actually looks at competing sources and forms a view. If you are not in the material behind the answer, you are not in the conversation, and nobody is going to scroll down to find you because there is nothing to scroll.”
The consequence, in his account, is that a great deal of accumulated professional knowledge remains partially valid, which he considers harder to navigate than knowledge becoming entirely obsolete. Techniques built around the mechanics of ranking address a problem that generative systems do not have, since they do not order results in a list. Practitioners applying them can produce real improvements in metrics that no longer connect to the outcome a client cares about.
King has identified consistency of description as the variable that has grown most in importance. Systems trained on large volumes of text build associations between entities and topics based on how often and in what context they appear together. A business described the same way across many independent sources becomes associated with its category. A business described differently in each place does not.
“The fix is boring and that is exactly why people skip it,” said Royston G King. “Go and read how your own company is described on your site, in your listings, in your coverage, in your executives’ profiles. Most companies find four or five different versions. You are handing a system a pile of contradictory information and then wondering why it describes you vaguely.”
“If you are not in the material behind the answer, you are not in the conversation.” Royston G King
There is a measurement problem underneath this that King has raised repeatedly. Search visibility could be observed directly, because a ranking is a fact. Presence inside a generated answer varies between users, between sessions and between systems, and the reasons are not exposed. Firms accustomed to precise reporting find this uncomfortable, and the temptation is to retreat to metrics that remain measurable but no longer reflect what matters.
He is careful about the limits of what anyone currently knows.
“I would be sceptical of anyone selling you a method for this, including me, if the method depends on some specific mechanism inside a model,” said Royston G King. “That mechanism might not survive the next release. What survives is being described accurately in a lot of places by people who are not you. That has been true through every version of search and I do not expect it to stop.”
King has said his cross-industry vantage point gives him an earlier view of the transition than a sector specialist would have, since it is arriving at different speeds depending on how buyers in a given market search. He has also applied the thinking to his own channels, which he reports at more than 15 million followers with over a billion views, and describes that internal work as a testing ground where approaches can fail without consequence to anyone outside his own accounts.
His view of the current moment is that the ambiguity is a property of the transition rather than a temporary inconvenience, and that practitioners waiting for the old clarity to return will be waiting a long time.
