Apple’s ambitions to overhaul its artificial intelligence strategy culminated in the long-awaited Apple Intelligence and enhanced Siri in 2025—a rollout that was, by most industry standards, a high-stakes bid to redefine the company’s place in the AI race.

But as Bloomberg detailed in its recent feature, the reality fell far short of Apple’s reputation for polish and reliability, exposing the company to rare criticism and raising questions about its innovation culture.

When Apple first previewed its so-called “Apple Intelligence” suite, it promised the integration would be seamless and privacy-centric, leveraging on-device processing and a refined Siri to bring generative AI features to millions of users. The expectation was that Apple, known for its careful, secretive approach and attention to user data protection, would bring a much-needed trustworthiness to AI assistants that competing platforms from Google and OpenAI struggled to match. But as internal sources told Bloomberg, the result was an “uncharacteristic misstep”—one that became evident almost as soon as the software landed in users’ hands.

The new Siri, heavily marketed as a context-aware, conversational AI, reportedly struggled with basic queries, performed inconsistently, and at times exhibited embarrassing lapses in understanding. According to Bloomberg’s reporting, some Apple engineers privately described the revamped Siri as “less reliable” than its predecessor, while several former employees suggested the rushed timeline for launch contributed to technical debt and organizational chaos.

Equally damaging was the handling of privacy. Apple’s commitment to on-device AI had forced its teams to work with limited data, constraining the model’s capabilities compared to rivals who enjoyed cloud-scale analytics. While this approach was lauded by privacy advocates, Bloomberg noted that it resulted in a notable performance gap. Apple’s internal AI researchers reportedly warned leadership that the company’s closed ecosystem was becoming a liability, not a strength.

Behind the scenes, Bloomberg reported, Apple’s internal culture of secrecy and compartmentalization created roadblocks to effective development. Engineers described “balkanized” teams and a lack of communication between hardware and software divisions, which hampered the kind of iterative, data-driven experimentation that is the foundation of successful machine learning projects at companies like Google or Microsoft. As a result, features like real-time voice recognition and context switching were far less robust than promised.

Moreover, Apple’s hesitance to collaborate widely with the external developer and academic communities further isolated its AI efforts. Multiple ex-employees told Bloomberg that Apple missed opportunities to learn from open-source advances and failed to attract the level of AI research talent that competitors lured with a more open, collaborative environment. This “not invented here” mentality slowed progress and made it difficult for Apple to adapt when early feedback on Apple Intelligence was critical or negative.

The commercial fallout was immediate. User forums and social media quickly filled with complaints about Siri’s regression, leading to a rare public apology from Apple’s executive team and promises of rapid updates to address shortcomings. Industry analysts told Bloomberg the misfire could have lasting repercussions for Apple’s premium brand, which has historically commanded trust based on reliability and user experience, even as competitors offered more experimental features.

This episode marks an inflection point in Apple’s relationship with AI—and with its users. As Bloomberg concluded, the Apple Intelligence and Siri saga underscores the risks tech giants face when they sacrifice their engineering fundamentals and cultural strengths in pursuit of headlines. For Apple, the path forward will likely require not just technical fixes but a re-evaluation of its approach to innovation, openness, and the realities of competing in a rapidly evolving AI landscape.