A business card used to say “consultant”. LinkedIn upgraded that to “thought leader”. The latest version is more impressive: “author of 17 books on leadership”.
That phrase still sounds like evidence. It suggests years of work, accumulated judgment and the sort of career in which somebody has occasionally had to tell a real employee that the budget does not exist. But as a recent Hublcore exclusive argues, self-publishing and generative AI have made the appearance of expertise dramatically cheaper to produce.
The point is not that self-published authors are unserious. Many are not. Nor is the point that AI automatically makes a book worthless. Used well, it can edit, translate, organise notes or accelerate research. The problem is simpler: the signal has changed.
A book title once represented friction. There were editors, language barriers, production costs, distribution negotiations and, usually, time. Now some of those barriers can be compressed into software and a marketplace account. Amazon KDP explicitly has a category for AI-generated text and translation, which publishers must disclose to the platform.
That changes how readers should interpret prolific output. Ten books may reflect ten substantial arguments. Or they may reflect one template, nine variations and an extremely energetic afternoon.
For leadership publishing, this matters because authority is the product. A novel can succeed because it is entertaining. A management book asks the reader to trust that the author knows something about organisations, people, incentives and failure. The cover may promise “strategic transformation”, but the useful question is still pedestrian: what, exactly, did the author transform?
The new prestige trap is confusing production with experience. A person can now build an impressive catalogue faster than a conventional executive can accumulate the situations those books claim to explain. The bibliography can race ahead of the biography.
That is why book count should probably join follower count in the category of metrics that look meaningful until inspected closely. The better questions are old-fashioned: Where has the author worked? What decisions did they own? Are the case studies identifiable? Do other professionals recognise the expertise? Is the book offering evidence, or merely fluent confidence?
Publishing has become more democratic. Expertise has not become automatic.
The management guru of the AI era may still be brilliant. But “author of 17 books” now deserves the same follow-up question as “serial entrepreneur”: how many of them involved actual work?