As the lunar Year of the Horse begins, one word will define the consumer electronics landscape: AI. Across both software and hardware, manufacturers are moving from proof-of-concept features toward deeper, device-level intelligence that aims to reshape how people interact with phones, wearables and home gadgets.
Expect on-device AI to accelerate. Companies are investing in neural processing units, optimized chips and software stacks that run models locally for faster responses, lower latency and better privacy guarantees. This shift reduces dependence on the cloud for everyday tasks — from camera scene recognition and predictive typing to intelligent battery management and contextual assistant responses — and changes product engineering priorities away from raw clock speed toward efficient, mixed-model compute.
Hardware design will follow software capability. Sensors, displays and battery systems are being rethought to support always-on, multimodal AI; cameras will feed richer inputs for computer vision models, microphones and haptics will tie into conversational agents, and power management will be tuned for intermittent inference workloads. These are incremental but cumulative changes: the overall user experience improves as each subsystem becomes AI-aware rather than AI-augmented after the fact.
The foldable question sits at the intersection of these trends. Foldable phones have graduated from novelty to a mainstream alternative in several Asian markets, and manufacturers including Chinese rivals have pushed aggressive form-factor experimentation. For Apple, a foldable model would be both a design and software challenge: engineers must solve hinge reliability, thinness, display durability and battery life while product teams adapt iOS and the app ecosystem to flexible screen states. If Apple times such a launch right, it could convert premium upgrade cycles; if not, it risks repeating earlier stumbles of first-generation foldables while handing rivals a marketing advantage.
Market dynamics in China matter globally. Domestic brands have become faster at iterating hardware and integrating bespoke AI features tailored to local services, which pressures incumbents to accelerate. At the same time, supply-chain constraints and component costs — displays, advanced semiconductors and high-density batteries — will govern how quickly AI-rich devices and folding screens reach affordable mainstream volumes.
Regulation and user trust will shape adoption. Greater on-device AI can mitigate privacy concerns, but governments and platform owners still face questions about data governance, model transparency and security. How manufacturers communicate trade-offs between cloud and edge processing, and how regulators define acceptable uses of embedded AI, will affect both consumer confidence and the pace of rollout.
For consumers, the coming year will look less like a single radical breakthrough and more like a series of layered improvements: smarter cameras, assistants that understand context across apps, longer real-world battery life when AI is used judiciously, and new form factors that alter how devices are held and used. Whether Apple’s next "blockbuster" will be a foldable remains an open bet, but the strategic imperative is clear: deliver tangible AI advantages that justify premium prices and lock in ecosystems.
In short, the Year of the Horse will be a test of integration. Success will go to the firms that marry efficient on-device models with hardware engineered around AI tasks, while navigating costs, supply chains and regulatory headwinds. For global players and regional challengers alike, the opportunity is to turn intelligence from a marketing claim into an everyday, reliable product difference.