There was a time when advertising followed intent.
People searched for information, and businesses met them there with relevant answers. A second key attribute of the ‘old’ system was that advertising created mental availability. This resulted in a brand presence and positioning being already established when someone ventured towards a market. In other words, ‘Brand building’, a set of disciplines too often ignored by those injected with digital as a panacea to all marketing challenges. The exchange was simple: attention for information, need for solution.
That model has been inverted.
Accuracy and relevance are up for auction. Today, marketers rely on platforms like Google and Facebook to push ads towards loosely defined behavioural categories.
Whether the recipient is a genuine prospect or a bot farm is often beside the point. The system optimises for delivery, not relevance. In some cases, it seems that simply being human is no longer the qualifying criterion.
What used to be information-led discovery has become auction-driven visibility.
“Information” is now whatever wins the bid inside an opaque algorithm. The bidder willing to pay enough, while satisfying the platform’s quality formula gets the privileged slot, whether or not they offer the best answer.
It begins to resemble a protection racket worthy of the Corleone family more than a marketplace.
If you do not pay, you do not appear. Visibility is no longer earned through relevance or quality, but purchased through participation.
If we reverse the model, and are prepared to pay for clarity and priority for the needs of the information seeker rather than the advertiser, the logic shifts quickly towards paid access.
AI search sits awkwardly in a new middle ground we have yet to adequately define. It promises a clean, single ‘best’ answer without the clutter of ads. However, the definition of what constitutes a ‘best’ answer is unclear.
What it delivers is not truth., it is probability. A compressed synthesis of what has been said before, shaped into what is most likely to satisfy the query.
That works well for established facts. Ask for a public figure’s birth year, and you will probably get an accurate answer.
Move into ambiguity or historical uncertainty, however, and the cracks appear. The system does not “know” in any meaningful sense. It predicts.
Its goal is coherence, not correctness.
This creates a subtle but important risk: the illusion of authority without the guarantee of accuracy.
Meanwhile, alternatives are available, and more are emerging, where the user once again, becomes the customer.
Smaller search platforms are experimenting with models that shift incentives away from attention and towards trust. Some rely on subscriptions. Others allow limited, user-controlled advertising or blend in affiliate models.
What unites them is a simple premise: you are the customer, not the product.
Today, their market share is marginal, but the underlying value proposition is strong.
As digital environments grow noisier and more manipulative, the ability to control what reaches you becomes a premium feature.
That control will not be free.
But as with any system where incentives shape outcomes, which is most of them, paying for alignment rather than being monetised through distraction may prove to be a far better deal most of the time.
