Productive Use of AI in Marketing: An Introduction baixar epub

Marketing has just lost the advantage it was built on.

For most of its history, a company's edge came from its capacity to produce. Making the film, writing the thousand product descriptions, reading twelve thousand customer conversations — these things were expensive and slow, and being able to do them well was a moat. Generative AI has pushed the cost of all of it towards zero. And when a scarce resource becomes abundant, value moves to whatever is still scarce.

Productive Use of AI in Marketing is an introduction to what the job becomes on the other side of that shift. It is written for the general business reader: no marketing background assumed, no technical knowledge required, and not a single product name in the entire book. The tools change every few months. The thinking does not.

The central argument is simple and uncomfortable. A marketing department can adopt every one of these technologies, become measurably faster and cheaper at everything it does, and end up worse off than when it started. That is not a hypothetical failure mode. It is currently the common one — and it happens because the metrics that improve are immediate and visible, while the ones that decay are slow and appear in a report nobody reads.

Across fourteen chapters, the book works through what actually changes:

• A plain-language model of what these systems really do, and why understanding them as superb pattern-continuers with no reliable connection to truth explains everything they are good and bad at.
• Why unmanaged adoption pulls a whole industry towards the same voice, the same imagery and the same claims — and what it takes to build against that current.
• The most valuable asset most companies own and have never read: the record of what their own customers have already told them.
• What happens to discovery when people stop searching and start asking, and the answer arrives without anyone visiting your website.
• Why platform-reported performance is a self-scoring system marking its own work, and which measurement methods survive when the tracking data no longer can be trusted.
• The collision between transparency law and the evidence that telling people content was machine-made causes them to think less of it.
• How teams, budgets and junior roles genuinely change — and the long bill that arrives from getting that last one wrong.

The book closes with a ninety-day plan for a department starting from scratch, notes for specific sectors from B2B to non-profits, straight answers to the questions people ask most, a guide to evaluating vendors without being sold to, and a full glossary.

This is not a collection of prompts, tools or tactics. It is a book about judgement: knowing which of the machine's forty competent options is worth the money, what to stop doing, what to measure, and what to protect while everyone around you is busy producing more.

The technology has made a great deal possible. Deciding what is worth doing is still the job — and it has never been worth more.