Honor Integrates AI into Power Efficiency Features

Honor added a dedicated power-saving suggestion feature in MagicOS 11 this time. It looks like a small easter egg in the system. Officially, they say it combines recent usage habits to identify features that consume high power but are rarely used, then provides targeted optimization suggestions. At first glance, I didn't see it as a power-saving feature, but rather like a car starting to record how you press the gas pedal, then reminding you later that a certain habit is wasting fuel.

In the short term, updates like this are very practical for phone manufacturers. Battery life issues are too common; users don't care how advanced the model is, they only ask why it's full charge in the morning but weak in the afternoon. Past system optimizations relied mainly on battery capacity, fast charging, background freezing, and power scheduling—hard metrics. Now adding personal habits turns power saving from a generic strategy into personalized advice. It might not directly drive device upgrades, but it enters the realm of experience reputation. For Honor, a manufacturer needing differentiation via system capabilities, small features can accumulate trust.

In the long run, this matter is more noteworthy for investors than just power saving. Phone operating systems naturally have permission to know how users launch apps, when they are active in the background, which features are occasionally opened and quickly left, and where battery is drained in which scenarios. The "identifying high-power-consuming but rarely used features" mentioned in the news is essentially on-device behavioral modeling. Once the model stabilizes, the system can organize scattered habits into executable tasks. Today it suggests turning off a resident feature; tomorrow it might suggest adjusting notifications, switching power modes, or recommending a service; the day after, it might link with earphones, watches, car systems, and home appliances.

Where is the ceiling for this track? If it's just a power-saving popup, the ceiling is low; phone makers can do it themselves, and users won't pay for it. If it's the entry point for a system-level Agent, the logic changes. Agents need to execute; chatting alone isn't enough. They need context, permissions, and the ability to turn suggestions into setting actions. Phones happen to be the best place to build personal context; they know when you wake up, commute, attend meetings, play games, or scroll messages. Power-saving suggestions are just packaging this data into a low-risk entry point, getting users to accept the system making small decisions for them first.

Valuation logic also needs to be broken down. Looking at a single feature, there's nothing to value. Look at three things: Is the data kept on-device and sustainably updated? Are users willing to authorize execution? Can the system invoke across devices? Without on-device privacy, users worry about habits being uploaded; without execution authorization, suggestions are just notifications; without cross-device linkage, value returns to within the phone. Only when all three work together is there a platform premium. Conversely, if manufacturers just use it for marketing or turn suggestions into service traffic diversion, short-term traffic exists, but long-term trust may drop.

Recently, when looking at AI and robotics projects, I often encounter a misconception. Many teams like to talk about large models, generation, and companionship, but don't talk about whether it can change the state of devices. If a home robot only chats, plays music, and tells jokes, its ceiling will be suppressed by entertainment products.

Its true value lies in taking over a class of low-friction, high-frequency, verifiable small tasks. Honor's power-saving suggestion is like a small sample, telling hardware companies that when AI lands in the system, it doesn't have to start grandly; it can begin by observing user power consumption anomalies.

Competitive barriers aren't in the algorithm either. Power-saving algorithms, recommendation algorithms, and anomaly detection can be done by mature teams. The difficulty lies in permissions and ecosystem. Phone manufacturers have system entry points, hardware data, long-term user retention, and can turn suggestions directly into setting actions. Startups building device managers often get stuck on permissions, install base, and cross-brand compatibility. If Apple, Huawei, Xiaomi, and Honor all embed similar capabilities into their systems, standalone tools will be squeezed. Those that survive will either master a vertical scenario or make automation sufficiently explainable and minimally intrusive.

Of course, the risks are not small. The more the system understands the user, the easier it is to overstep boundaries. Users might agree today to let it suggest power savings, but might not agree tomorrow to let it automatically close a feature. Personalized recommendations have been validated as effective on content platforms, but device systems are different; erroneous execution brings real costs. For example, misjudging an app as rarely used, causing the user to lose important data the next day; or closing a background task, leading to failure in watch, car, or smart home linkage. Therefore, restraint is crucial for such features.

My judgment is that Honor's update itself isn't worth writing a separate investment memo for, but it is a signal. Mobile OS is shifting from feature stacking to personal context services. Short term, it improves battery life experience and system reputation; long term, it may become the entry point for on-device AI, system Agents, and cross-device services. For startups, don't rush to build a universal assistant; first find a small cut-in point like power saving, and complete the loop of observation, explanation, authorization, execution, and feedback. For investors, I will pay more attention to projects that can continuously record device states, user habits, and automation results; products that only demo chat interfaces don't count.

Looking ahead, these exclusive suggestions in phone systems will increase. Whether users buy in depends on whether it truly saves power, reduces intrusion, and makes fewer errors.