Al bring e-printing on demand to publish utility on demand and supply theory AI can bring utility advantage to e-publish industry. The product becomes a commodity and its functionality is wrapped up with other services. Think Amazon Print on Demand. Shifting this example sideways and into the creative author and publishing market and you can see an interesting shift taking place. Publishing itself is increasingly becoming a commodity. Many authors do it themselves.However, using creativity and imagination to produce a new work to be published remains in the custom build period. Before we can move into the utility phase, we will pass through the production phase. The question is, who will produce the products that enable the production phase, who will exploit them and who will lead the giants in the market? It's unlikely to be the publishing houses as they are already deep into the utility war (a period where there is intense competition, mostly over price since the primary product is usually cheap and the features consistent. Finally, back to the original thought... WHEN will AI be a serious threat to the part time author?There had to be a better way for books to find their readership by analyzing the content itself and linking it to reader experience. Using machine learning-a branch of artificial intelligence, Booxby identifies, quantifies and predicts reader experience based on the text itself, representing the foundation for a radical new way to approach book discovery. However, AI applies to e-publish on demand print, it can bring the sale number of paper books number reduces to any book shop when readers choose to buy any paper books from on demand print e-publishers. The number of books published annually in the U.S. has exploded by 400% in the last decade, according to Berrett-Koehler's September 2016 report. With 1 million books published each year, publishers find it increasingly difficult to find readers for each book, making book discovery the publishing industry's biggest problem.Two waves of technological disruption drove this book discovery dilemma. For example, Amazon disrupted procurement and distribution by opening the first online bookstore in 1995. Second, digital publishing disrupted production, making it easy for anyone to publish a book via ebook or POD (print on demand) with companies like Lightning Source, Smashwords, CreateSpace, Lulu and others offering easy and affordable ways for independent authors to produce a book. Compounding the disruption was the closing of big chain bookstores, the shrinking size of newspaper book review sections (and in some cases, their total elimination) and the shifting center of the conversation around books with so many other forms of media to compete with the attention and time of consumers. Over time, these forces made book discovery a huge problem. The resulting signal-to-noise crisis has forced traditional publishers to "pulp" or destroy 25% of their inventory, according to The Latest Outrage Dec. 11, 2009 piece "Pulping is The Publishing Industry's Dirty Little Secret." This is a wasted opportunity, considering that roughly 3% of books make a return yet account for nearly $28 billion in annual sales. Clearly, the problem of book discovery looms large for authors, publishers and readers. Authors and publishers lose money, and readers waste time trying to find what works for them. We simply don't have the human resources to surmount the problem. This is where artificial intelligence can step in and provide meaningful analytics to inform acquisition decisions, understand a book's full market potential, and create an effective mechanism to connect books to the readers who would most enjoy them-none of which currently exist. Through innovations in machine learning backed by a grant from the National Science Foundation, Booxby is addressing these challenges.