Apple's slow AI pace becomes a strength as market grows weary of spending

Perception of Apple’s “Slow AI” Strategy

• Many see Apple’s caution as deliberate “second mover” strategy: let others burn cash, find real use cases, then ship tightly integrated, polished features.
• Others argue the slowness is dysfunction, not wisdom: Siri has stagnated, key AI products were delayed or shipped half‑baked, and internal management/quality problems are blamed more than strategy.
• Comparisons are made to COVID hiring: Apple avoided overexpansion and later looked prudent when peers had to cut.

User Demand and Attitudes Toward AI

• Several commenters say ordinary users are not clamoring for “AI,” just for things like a competent assistant, better search, and automation.
• There’s strong pushback against “AI everywhere” experiences (e.g., Copilot in Windows, Gemini in Android) that feel intrusive or degrade core functionality.
• Others counter that LLMs and AI art are already widely used in practice, even by vocal critics, and that anxiety about AI’s societal impact is common in “real life.”

On‑Device vs Cloud AI

• A major thread: Apple’s focus on small, on‑device models as privacy‑preserving and economically sustainable, offloading compute and power costs to users.
• Skeptics argue local models are currently too weak, slow, and RAM‑constrained; for most users, a fast, more capable cloud model is preferable.
• Some see Apple’s unified memory and Neural Engine as a long‑term advantage once small models improve; others note most consumers won’t care about local vs cloud if cloud just “works.”

Siri and Product Quality

• Siri is widely described as bad or regressing, especially versus Gemini or Alexa; examples include simple location and timer failures.
• Several say Apple has abandoned its old “ship only when it really works” ethos; recent OS releases (Tahoe, iOS 26) are criticized as buggy, slow, and overdesigned.
• A minority note useful low‑key ML features (photo search, notification summaries, app suggestions) and decent built‑in small models in the latest OS.

Financial and Ecosystem Angle

• Some expect Apple to win by distribution: hundreds of millions of Apple Silicon devices with a built‑in LLM and a unified API for developers.
• Others doubt on‑device AI will matter much if users continue to rely on cross‑platform cloud agents like ChatGPT or Gemini.
• Several predict an upcoming AI “enshittification” (ads, manipulation) that could drive users toward trusted, on‑device assistants—potentially favoring Apple.