“Mass Automation” envisions containerized companies, data marketplaces, and shapeshifter firms that change industries overnight, offering a practical blueprint for leaders, entrepreneurs, and regulators navigating the AI era

NEW YORK, April 22, 2026 /PRNewswire/ — Imagine describing a children’s toy idea to a central orchestrating system. Within days, it has designed the product, contracted a factory, secured permits, launched marketing and negotiated retail contracts—with almost no employees involved. Even in this scenario, however, the entrepreneur’s vision and key decisions remain essential. This is the world described in “Mass Automation,” a new book by Nick Pogrebnyakov that explores how the convergence of AI, robotics, and data sensing could allow companies to operate nearly autonomously, and what that means for leaders, entrepreneurs, and regulators who need to prepare.

Pogrebnyakov frames automation through three pillars that mirror core human capabilities: AI for decision-making, robotics for physical action and sensing for data perception. But the book’s real contribution is showing what happens when all three converge inside a company. He introduces “containerized companies,” prepackaged with all the automated capabilities needed to operate, purchasable from a marketplace and deployable much like a software container. He describes “shapeshifter companies” that use automation to jump between industries and product lines, accumulating competitive advantage from the path they travel across markets.

Pogrebnyakov argues that companies go through two modes: development, where humans build products and shape processes, and maintenance, where the company runs largely on its own. Since most of a company’s lifespan is spent in maintenance, automation frees skilled people to move between companies that need them most, offering expertise in development mode rather than staying on payroll indefinitely. Using fictional scenarios alongside real-world examples, he maps these ideas across company functions from R&D to logistics to strategy, then beyond the firm to supply chains, data marketplaces and regulation.

“Science fiction inspired the products of the future. Now we need ‘business fiction’: narratives that help managers, entrepreneurs and policymakers imagine how companies and economies work as AI becomes pervasive,” said Pogrebnyakov. “The development of technology is outpacing our thinking on how to use it. What’s missing is the blueprint for applying it, and that’s what this book tries to provide.”

After twenty years at the intersection of academic strategy research and senior engineering roles at Twitter (now X) and Sparrow Bioacoustics alongside an associate professorship at Copenhagen Business School, Pogrebnyakov wanted to describe business thinking deeply informed by how he’s observed today’s technology working.

“Most discussions of AI focus on individual tools or individual jobs,” said Pogrebnyakov. “This book asks a bigger question: what happens when you automate an entire company—its decisions, its physical operations, and its ability to sense the world—all at once? The answer changes how we think about competition, supply chains, and even regulation.”

“Mass Automation: Rethinking Companies for an AI Era When They Can Operate Autonomously” By Nick Pogrebnyakov
ISBN: 9781665781961 (softcover); 9781665781954 (electronic)
Available at Archway Publishing, Amazon and Barnes & Noble

About the author

Nick Pogrebnyakov holds a PhD in Information Sciences and Technology from Penn State and was an Associate Professor of International Business at Copenhagen Business School, Denmark and was a visiting scholar at Stanford. He has held senior engineering roles at Twitter (now X), Thomson Reuters and Sparrow Bioacoustics and currently teaches a highly ranked course on strategy implementation on Coursera. Pogrebnyakov is a recipient of an Excellence in Teaching award from the Danish Society for Education and Business. To learn more, please visit www.archwaypublishing.com/en/bookstore/bookdetails/867743-mass-automation.

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