The next test of Apple’s A.I. strategy may have little to do with Siri. The bigger question for John Ternus is whether the organizational model that made Apple successful can keep pace with A.I. Photo by Kevin Winter/Getty Images

John Ternus inherits Apple at an unusual moment. The company remains one of the most valuable organizations in the world, but it is entering an A.I. race from a position that is less comfortable than its dominance in hardware and consumer software would suggest. Siri has yet to establish itself as a leading A.I. assistant, and Apple is still figuring out how its models, products and broader A.I. strategy should fit together.

Much of the conversation about Apple and A.I. has understandably focused on those products: whether Siri can catch up, how Apple will build its models and how quickly it can bring A.I. into its devices. For Ternus, though, the more consequential question may have less to do with what Apple builds than with how Apple itself is built. 

A.I. is changing the economics of software development and knowledge work, and that inevitably changes how large technology companies must organize themselves to compete. For a company of Apple’s size, the stakes are especially high. 

The traditional relationship between company size and company capability is breaking down. For most of the modern technology industry, growth has come with a predictable cost. More engineers require more managers, finance staff, compliance teams and other functions to support them. A company gains productive capacity with every new employee, but it also accumulates another layer of organizational work around that capacity.

A.I. changes that equation. A system that once routed a request to an employee can increasingly resolve the request itself; a workflow that once required several people to move information between systems can increasingly run on its own. The result could be an organization with fewer layers between an employee having an idea and the company acting on it. Or, put simply, an organization that can move faster.

Speed is essential in a field where models and products are improving at an extraordinary pace. Organizational mass can become a disadvantage surprisingly quickly when information has to travel, decisions have to be approved and teams have to coordinate before anything ships. Ternus should ask a key question: If Apple were being designed today, with the capabilities of modern A.I. available from the beginning, which parts of the organization would he build differently?

Apple has massive complexity that comes with its business: a global supply chain, thousands of storefronts and intense regulatory scrutiny. But some of the complexity inside any large company exists because the software supporting it was designed to track work and keep people organized rather than to actually carry work forward. Ternus has an opportunity to examine how Apple organizes itself: putting highly capable people closer to important decisions, giving teams more autonomy and reducing the coordination required to move an idea from research to product.

Every hour an engineer spends navigating an internal process, every additional approval required to assemble a team and every administrative function that scales linearly with headcount is an organizational tax. Historically, those taxes were an unavoidable consequence of becoming enormous. A.I. makes some of them less necessary. If Apple can use A.I. internally to absorb more of that work, its engineers and researchers could spend more of their time building, experimenting and making decisions.

Companies like OpenAI and Anthropic can change direction quickly because they were built around a technology that is still evolving in real time. Apple has the advantage of extraordinary resources, talent, distribution and a massive installed base. Ternus’s challenge is to make those advantages easier to mobilize rather than allowing the organization’s size to slow them down.

If Ternus succeeds, Apple’s A.I. progress will be visible in more than Siri or the next generation of devices. It will show up in how quickly teams form around new problems, how much an exceptional engineer can accomplish and how rapidly an idea can move from research into a product. For a company trying to compete in a technology race that is moving this quickly, Ternus should be asking whether the organizational model that made Apple successful is also the one that will make it competitive in A.I.