Behind the "Hundred Glasses Battle" lies a collective anxiety among tech giants about missing the next entry point, driving an ecological gamble where success hinges not on hardware specs but on closed-loop vertical scenarios and control over physical-world data.

Content/Sophisticated

Edited by/Singing Goose

Proofread by/Rustic Man

Unlike a few years ago, the AI glasses sector is no longer a playground for a few geeks but a relentless marathon. Google has relaunched its Glass project, Alibaba has unveiled six new products, and even automaker Li Auto has joined the fray. Tech giants are flooding in, reviving the "machine sea" tactics.

Capital fervor contrasts sharply with market caution. While the global AI glasses market is projected to hit $4.2 billion by 2025, up 67.2% year-on-year, consumers remain hesitant, hovering between wait and see (observation) and attempt (experimentation).

The real question is whether this hardware frenzy, driven by both technology and capital, represents an inevitable evolution in smart interaction or just another overhyped bubble. Will it be the next super terminal to revolutionize human-machine interaction or repeat Google Glass's fate of critical acclaim but commercial failure?

Part.1

Phenomenon

Why Are Tech Giants All "Wearing Glasses"?

Latest data shows global smart glasses shipments hit 1.487 million units in Q1 2025, surging 82.3% year-on-year, with China's market growing even faster at 116.1%, delivering 494,000 units.

By late 2025, the AI glasses sector resembles a fierce battleground.

In just one month, Kuake (Alibaba's brand) launched six AI glasses models, covering consumer to professional scenarios. Google quietly relaunched Glass Enterprise Edition, with a new Project Aura collaboration with XREAL expected by year-end. Adding Huawei, Xiaomi, Meta, and others already in the fray, the sector has rapidly evolved from edge experimentation to full-scale war.

「Zhengjian TrueView」observes three distinct categories among current AI glasses players:

1. Platform giants like Alibaba, Google, and Meta, which hold vast user bases and data entry points. Their entry logic is fundamentally about ecosystem extension and defense.

2. Smartphone makers with hardware-software synergy, such as Huawei and Xiaomi, which excel at integrating hardware capabilities with system experiences.

3. Vertical scenario and tech-fusion players like Rokid, which deeply integrate "AI+AR" to establish differentiated barriers in scenarios like smart prompting, cross-language meetings, and industrial inspections.

Each player, vendor, and model operates under its own rules, technologies, and user profiles, creating a market so diverse that entry strategies and product positioning vary sharply.

Take Alibaba as an example. Its entry follows a disciplined approach, aligning with this year's group-wide "ecosystem integration" strategy. It strongly enters the consumer market with starting prices below 2,000 yuan, deeply integrating core ecosystem resources like Tongyi Qianwen large model, Alipay, and Gaode Maps.

Its Kuake AI Glasses S1 supports voice or photo-based AI Q&A. Its self-developed Master Agent large model control system can autonomously break down complex instructions for multi-round dialogues. Job platform data also reveals Alibaba's low-key expansion into offline channels, potentially partnering with traditional eyewear stores to fully connect its online ecosystem with offline touchpoints.

In contrast, Li Auto's AI Glasses Livis support remote vehicle control, such as opening electric side sliding doors, pre-activating In car air conditioning (in-car air conditioning), and seat heating (seat heating), while maintaining general-purpose functions but leaning toward automotive scenarios. Smartphone makers like Xiaomi are building advantages in flexible OLED technology, health monitoring, and all-scenario perception.

Across the industry, this tech giant-led hardware surge spawned at least 40 new AI glasses products in the first half of 2025, 2.3 times the total for 2024.

However, the "machine sea" tactics haven't triggered explosive sales growth. An industry observer told 「Zhengjian TrueView」 that AI glasses are still in a phase of cultivating market awareness and user habits. The core goal isn't rapid scaling or blockbuster sales but lowering user barriers, fostering habits, building brand recognition, and nurturing scenario stickiness. The strategy is to quickly seize market share with cost-effective products and then achieve commercial closure through ecosystem services.

The broad, scattered layouts of major players reflect widespread anxiety. Functions like AI assistants, object recognition, music playback, and photography are highly homogeneous. Even with saturated resource inputs, significant generational gaps are unlikely to emerge shortly. Many small and medium-sized vendors can even catch up quickly.

This contrasts sharply with smartphones, which took over a decade to homogenize, prompting giants to avoid over-investing in marketing. The competition's core has long shifted beyond hardware itself.

Part.2

Comparison

A Tougher "Entry Point" Climb Than Smartwatches

The rise of AI glasses validates the triangular law of technology, cost, and scenario. Yet its story isn't unique; its evolution path deeply mirrors and diverges from the smartwatch market.

Like smartwatches' early reliance on smartphone linkage and limited functions to notifications and health tracking, today's AI glasses are undergoing a transformation from accessories to terminals.

The driving force lies in breakthroughs in lightweight on-device large models. Models like Tongyi Qianwen Mini and Gemini Nano have seen reasoning efficiency soar severalfold compared to 2023, with latency dropping below 100 milliseconds, enabling real-time, natural voice interactions.

This mirrors how smartwatch chip energy efficiency improvements and sensor miniaturization paved the way for independent health and fitness monitoring.

At its commercial core, all hardware waves revolve around entry point competition. Smartwatches established the value of wrist-based entry, integrating into users' lives through health and fitness data. AI glasses aim higher, seeking to break free from handheld constraints and become contextual intelligence terminals covering vision and space with "all-day wear, effortless interaction" potential.

This means AI glasses will collect data beyond heart rates and steps, ascending to first-person continuous real-world visuals, ambient sounds, and interaction intents, thereby constructing deeper ecological barriers. This aligns with OpenAI leader Altman's vision of "next-generation devices that deeply understand scenarios and manage tasks for extended periods."

Smartwatches succeeded by precisely addressing health management and efficient notification needs, around which they built hardware-software ecosystems. AI glasses face both challenges and opportunities here.

B2B scenarios show promise, such as Google Glass identifying equipment failures in industrial maintenance, echoing smartwatches' vertical deepening in professional sports.

B2C breakthroughs require equally universal scenarios. Alibaba's approach is to vocalize and visualize high-frequency services like navigation and payment for "what you see is what you get." But this demands experiences surpassing smartphones and watches. Why use glasses when lifting your wrist suffices for payment and navigation?

Smartwatches took years to balance battery life, comfort, and ecosystems. AI glasses face steeper challenges: excelling in wear comfort, battery life (currently 4-6 hours mainstream), heat dissipation, and privacy security. Ecologically, they can't settle for mirroring smartphones like early watches but must create unique scenario closures, akin to how Apple Watch built independent services around health.

This requires vendors to simultaneously excel in hardware integration, AI technology, and cross-ecosystem integration.

Part.3

Crux

The Underlying Logic and Decisive Factors Behind Giants' Bets

Peering beneath the surface of giants' dense (intense) entry, two intertwined strategic threads emerge: ecological positioning for the next interaction entry point and an insatiable hunger for physical-world data. These form the bedrock logic driving the industry's rapid advancement and point to future decisive factors.

The "Hundred Glasses Battle" is essentially an ecological defense and expansion war that cannot afford failure. For omnipotent giants like Alibaba, Google, and Baidu, AI glasses represent the missing piece in their vast digital empires.

They possess all elements—computing power, large models, payments, navigation, content—except a hardware entry point that can attach to users 24/7 for effortless interaction.

Alibaba's strategic shift is highly representative, rapidly escalating from a tool-centric approach around Kuake to an ecosystem-decisive battle centered on Qianwen App.

Internally, Alibaba positions Qianwen as the "symbol of Alibaba's AI C-end mindshare" and, in a rare overall war posture, assembled over 500 elites into an independent project team within 96 hours, abandoning traditional OKRs to go all-in.

This isn't merely for a pair of glasses or an app but to forge a super AI entry point capable of carrying and connecting all core businesses—e-commerce, local services, cloud services, etc. Both glasses and the app are just tangible touchpoints of this ecosystem.

Similar logic applies to Baidu and Google, the "foreign twins." Baidu defines AI glasses as an "S-level strategy," while Google relaunched its project and partnered with supply chain giants. They're not vying for glasses market share but for their ecosystems' moats and user mindshare high ground in the next decade.

The "Hundred Glasses Battle" is equally a future-oriented physical-world data war. Current large model evolution faces bottlenecks, with internet text and video data becoming redundant while physical spacetime data reflecting real-world operations remains scarce.

Li Auto's Li Xiang predicted three years ago that "AI glasses are the best carrier (vehicle) for collecting real-world data," a insight now becoming industry consensus.

As the only device capable of perceiving users' environments, behaviors, and even intents from a first-person, all-day perspective, glasses will become the ultimate sensor for collecting multidimensional continuous data, including visuals, sounds, locations, and gaze points. This data is crucial for training world models that understand and interact with the physical world.

Thus, giants betting on glasses are also stockpiling the most critical strategic resource for the next AI competition: high-quality real-world data fuel. Whoever masters this data may gain the upper hand in the AGI race.

When ecological and data wars overlap, the industry's competitive dimension is thoroughly (thoroughly) reconstructed. Hardware homogenization accelerates the shift in competition focus to software, ecosystems, and user experiences.

In the next phase, competitive barriers among players will shift from hardware innovation to ecosystem integration capabilities. Success hinges on seamlessly embedding glasses into a rigid, high-frequency service closure.

Alibaba's approach integrates navigation, scanning, and payment for "one-glance access," while Li Auto combines vehicle control for a "human-vehicle integration" experience. Pure hardware vendors unable to build unique ecological value will struggle.

The "barrel effect" of user experience will also be infinitely amplified. Beneath the ecosystem and data narratives, any product shortcoming (shortcoming) becomes fatal.

Xiaomi's first-generation glasses saw a 40% return rate, while other brands failed due to Bluetooth connectivity or chip compatibility issues, all confirming this. Users won't tolerate poor wearability, short battery life, or sluggish interactions for the sake of a grand ecological vision.

Meanwhile, strategic patience will become a scarce resource. Both ecosystem cultivation and effective data accumulation require long-term, sustained investment without shortcuts. Alibaba's calm and restraint in traffic investment reflect a sober awareness that this is a marathon.

While giants have resources, only those willing to endure early losses, continuously iterate products, and patiently nurture scenarios will prevail.

The current AI glasses frenzy is essentially giants building new-era infrastructure. It's both a defensive extension of the mobile internet ecosystem and a proactive positioning for the general artificial intelligence era.

Hardware is the carrier, ecosystems the moat, and data the future currency. The "Hundred Glasses Battle" endgame won't be decided by a single "blockbuster" product but by who finds the most stable, sustainable balance among hardware experience, ecological synergy, and data value—the impossible trinity.

Greatness will arrive, just never as we preset (presuppose). For AI glasses, let's exercise more patience and less myth-making.