对话一苇资本、声智科技、灵宇宙、中博聚力：AI智能硬件赛道的机遇与挑战

IT桔子 2026-07-07 15:12

IT桔子 2026/07/07 15:12

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这篇文章整理了AI智能硬件赛道行业沙龙的核心干货，包含赛道整体重点信息与适合普通读者的实操参考，具体如下：

1. 当前AI智能硬件赛道热度远超预期，2023年后成立的431家新锐公司中，融资率高达75.9%，赛道仍处于早期阶段，创业窗口尚未关闭，地理上形成京深双核格局，深圳拥有全球领先的硬件供应链优势。

2. 对意向创业者而言，建议不要盲目追求颠覆式创新，可聚焦细分场景和目标人群做微创新，不必等技术尽善尽美，可先进入市场获取用户验证再逐步迭代。

3. 对消费者而言，当前主动交互技术尚未成熟，AI耳机行业平均退货率达30%-50%，不必盲目追新，可等待技术落地成熟后再尝试。

本文为AI智能硬件品牌商提供了赛道趋势、产品研发与竞争策略等多维度干货，具体如下：

1. 消费趋势层面，当前AI智能硬件处于早期红利期，可穿戴设备、垂直场景专属硬件增速明显，用户越来越看重产品的情感陪伴属性与细分场景功能，主动交互是未来核心演进方向。

2. 产品研发层面，建议走微创新路线，平衡技术能力、用户需求、成本控制三者关系，不必盲目追求颠覆式创新，可采用概念款+量产款双线策略，量产款靠性价比和颜值建立品牌心智，概念款布局未来技术。

3. 竞争策略层面，大厂无法覆盖所有垂直领域，品牌可依托自身核心优势做单点突破，切入已有强势玩家的品类时，需先做好基础功能，再叠加AI能力打造差异化。

本文为AI智能硬件领域的卖家梳理了当前赛道的机会、风险与可落地的经营经验，具体如下：

1. 机会层面，当前赛道整体热度居高不下，仍处于早期发展阶段，创业窗口敞开，智能戒指、AI眼镜、AI玩具、健康可穿戴等多个细分赛道增速快、想象空间大，深圳完整成熟的供应链能显著降低试错成本，适合卖家切入布局。

2. 风险提示，当前赛道热钱涌入存在泡沫，AI硬件的退货、售后成本远高于软件，AI耳机行业平均退货率达30%-50%，若探索硬件不赚钱靠订阅盈利的模式，必须严格控制硬件BOM成本与模型推理成本，避免出现两头亏损的情况。

3. 经营建议，不必等技术完美再入场，先切入市场拿到真实用户反馈再迭代优化，尽快打通商业化闭环，保障现金流健康。

本文为布局AI智能硬件领域的工厂提供了产品需求、商业机会与转型方向等干货参考，具体如下：

1. 产品生产设计需求，当前AI硬件主流开发路线是用新AI技术改造旧品类，走微创新路线，不同人群对硬件设计的需求差异明显，女性更看重外观，儿童要求轻量易操作，工厂可针对性调整生产设计方案，贴合市场需求。

2. 商业机会，当前赛道融资热度高，大量初创AI硬件公司诞生，对优质供应链的需求旺盛，深圳已经成为全球AI硬件创业的供应链核心聚集地，工厂落地或对接深圳供应链，能更便捷对接创业客户，降低试错与沟通成本。

3. 转型启示，AI技术正在向终端下沉，工厂可对接成熟的AI技术方案商，为传统硬件产品赋能AI能力，开发符合市场需求的新产品，抓住赛道早期红利完成转型。

本文为AI智能硬件领域的服务商梳理了行业发展趋势、客户核心痛点与服务方向，具体如下：

1. 行业发展趋势，AI智能硬件正从被动应答向主动感知交互演进，需要多模态感知、端侧推理、长期记忆、传感器升级等多领域技术支持，当前赛道处于早期阶段，大量创业公司涌入，对技术方案、供应链服务、品牌战略、融资对接的需求十分旺盛。

2. 客户核心痛点，AI硬件创业普遍面临“锤子找钉子”困境，手握技术找不到合适的量产载体，多数创业团队缺乏硬件实操经验，摸不透硬件选型、成本管控等非透明信息，多数项目尚未跑通商业化闭环，面临现金流压力，投资端也需要筛选优质项目的相关支持。

3. 服务方向，可针对细分赛道开发成熟的AI技术方案，降低创业公司的技术门槛，也可提供供应链对接、成本管控咨询服务，帮助创业公司降低试错成本。

本文为布局AI智能硬件领域的平台商梳理了参与者需求、运营方向与风险规避要点，具体如下：

1. 市场需求层面，AI智能硬件创业公司对成熟供应链资源的依赖度很高，有降低试错成本、对接供应链的强烈需求，同时超过半数的项目处于天使轮早期阶段，有很强的融资对接需求，大量项目需要产业服务支持快速落地。

2. 运营与招商方向，平台可重点吸引AI硬件初创公司、深圳本地供应链企业、AI技术方案商、投资机构入驻，打造“技术+供应链+资本”的产业服务生态，针对不同发展阶段的项目推出差异化服务，满足多元需求。

3. 风险规避要点，当前赛道热钱涌入存在泡沫，多数项目还处于原型验证阶段，尚未跑通商业化，平台招商时要筛选已经验证应用场景、有清晰现金流规划的项目，提示入驻项目控制成本，尽快打通商业化闭环，规避泡沫风险。

本文汇总了国内AI智能硬件赛道的最新产业动向、新问题与商业模式探索，对产业研究有较高的参考价值，具体如下：

1. 产业新动向，当前国内AI智能硬件掀起新一轮创业浪潮，2023年后成立的新锐公司融资率高达75.9%，赛道仍处于早期，格局远未定型，地理上形成京深双核的产业布局，深圳依托供应链优势成为核心聚集地，具身智能机器人是当前融资热点，可穿戴等垂直赛道增速明显，主流路线是旧品类叠加AI微创新。

2. 行业新问题，当前行业普遍存在“锤子找钉子”的技术落地困境，主动交互技术面临大模型幻觉、端侧推理与隐私保护平衡、成本控制难等技术关卡，赛道热钱涌入存在泡沫，大量项目未打通商业化闭环，AI硬件退货率居高不下，AI耳机平均退货率达30%-50%。

3. 商业模式与格局展望，当前行业已经探索出概念款+量产款双线布局、硬件订阅制等新模式，未来将形成大厂占据核心统一终端、创业公司深耕垂直场景的多层次生态格局。

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Quick Summary

This article compiles key takeaways from an industry salon on the AI smart hardware track, featuring core information on the overall sector and practical guidance for general readers, as summarized below:

1. The AI smart hardware track is far hotter than expected. Among 431 new startups founded after 2023, as many as 75.9% have secured funding. The track remains in its early stage, and the window for entrepreneurship is still open. Geographically, it has formed a dual-core pattern with Beijing and Shenzhen at its center, with Shenzhen boasting globally leading hardware supply chain advantages.

2. For aspiring entrepreneurs, the article advises against blindly pursuing disruptive innovation. Instead, founders should focus on micro-innovation tailored to niche scenarios and target user groups, and do not need to wait for perfect technology: they can enter the market first to obtain user validation, then iterate products gradually.

3. For consumers, current active interaction technology is not yet mature, and the average return rate for AI headphones reaches 30% to 50%. Consumers do not need to blindly chase new trends, and can wait for the technology to mature and stabilize before adopting new products.

This article provides multi-dimensional insights for AI smart hardware brands on track trends, product R&D and competitive strategies, summarized below:

1. In terms of consumer trends, AI smart hardware is currently in an early-stage period of dividends. Wearable devices and vertical scenario-specific hardware are growing rapidly. Consumers increasingly value the emotional companionship attributes and niche scenario functions of products, and active interaction is the core direction of future evolution.

2. For product R&D, brands are advised to adopt a micro-innovation approach to balance technical capability, user demand and cost control, rather than blindly pursuing disruptive innovation. Brands can adopt a dual-line strategy of concept models + mass-produced models: mass-produced models build brand mindshare through cost-performance and design appeal, while concept models lay the groundwork for future technology development.

3. In terms of competitive strategy, large tech players cannot cover all vertical segments. Brands can achieve single-point breakthroughs by leveraging their own core advantages. When entering categories already dominated by strong incumbents, brands should first perfect basic functions, then add AI capabilities to build differentiation.

This article sorts out current track opportunities, risks and actionable operating insights for sellers in the AI smart hardware sector, summarized below:

1. In terms of opportunities, the overall track remains highly popular and is still in its early development stage, with the window for entrepreneurship still open. Multiple niche tracks including smart rings, AI glasses, AI toys and health wearables are growing rapidly with large room for imagination. Shenzhen's complete, mature supply chain can significantly reduce trial-and-error costs, making it ideal for sellers to enter and布局 the sector.

2. For risk warnings, the influx of hot capital has created froth in the sector. Return and after-sales costs for AI hardware are far higher than for software, with the average return rate for AI headphones reaching 30% to 50%. If sellers pursue a "hardware as a loss leader, profit from subscriptions" model, they must strictly control BOM and model inference costs to avoid losses on both ends.

3. For operating advice, sellers do not need to wait for perfect technology to enter the market. They should enter the market first to obtain real user feedback, then iterate and optimize, and close the commercialization loop as soon as possible to maintain healthy cash flow.

This article provides actionable insights on product demand, business opportunities and transformation directions for factories布局 the AI smart hardware sector, summarized below:

1. In terms of product design and manufacturing requirements, the mainstream development route for current AI hardware is to upgrade traditional categories with new AI technology through micro-innovation. Demand for hardware design varies significantly across user groups: women prioritize appearance, while children require lightweight, easy-to-use designs. Factories can adjust their production and design plans accordingly to better align with market demand.

2. In terms of business opportunities, the track currently sees high financing activity, with a large number of new AI hardware startups emerging, creating strong demand for high-quality supply chains. Shenzhen has become the core global supply chain hub for AI hardware entrepreneurship. Factories that locate in or partner with Shenzhen's supply chain ecosystem can more easily connect with startup clients and lower trial-and-error and communication costs.

3. For transformation insights, AI technology is increasingly moving from cloud to edge devices. Factories can partner with mature AI solution providers to add AI capabilities to traditional hardware products, develop new products that fit market demand, and capture early-stage dividends to complete their transformation.

This article sorts out industry development trends, core client pain points and service directions for service providers in the AI smart hardware sector, summarized below:

1. In terms of industry trends, AI smart hardware is evolving from passive response to active perception and interaction, which requires technical support across multiple fields including multimodal perception, edge inference, long-term memory and sensor upgrades. The track is still in its early stage, with a large influx of startups creating strong demand for technical solutions, supply chain services, brand strategy and financing matchmaking.

2. In terms of core client pain points, AI hardware startups generally face the "hammer looking for a nail" dilemma: they have technology but cannot find a suitable mass production载体. Most startup teams lack hands-on hardware experience, and struggle with non-transparent information such as hardware selection and cost control. Most projects have not yet achieved commercialization, and face cash flow pressure, while investors also need support to screen high-quality projects.

3. In terms of service directions, providers can develop mature AI solutions tailored for niche tracks to lower the technical barrier for startups. They can also offer supply chain matchmaking and cost control consulting services to help startups reduce trial-and-error costs.

This article sorts out participant demands, operation directions and risk mitigation guidelines for platforms布局 the AI smart hardware sector, summarized below:

1. In terms of market demand, AI smart hardware startups rely heavily on mature supply chain resources, and have strong demand to reduce trial-and-error costs and connect with supply chain partners. At the same time, more than half of all projects are in the early angel round stage, with strong demand for financing matchmaking, and a large number of projects need industrial support to accelerate go-to-market.

2. In terms of operation and recruitment direction, platforms can prioritize attracting AI hardware startups, local Shenzhen supply chain companies, AI solution providers and investment institutions to settle, build an industrial service ecosystem of "technology + supply chain + capital", and launch differentiated services for projects at different development stages to meet diverse needs.

3. In terms of risk mitigation, the current influx of hot capital has created froth in the track, and most projects are still in the prototype validation stage and have not yet achieved commercialization. When recruiting new projects, platforms should screen for projects that have already validated their application scenarios and have clear cash flow planning, and remind settled projects to control costs, close the commercialization loop as soon as possible, and mitigate froth-related risks.

This article summarizes the latest industry trends, emerging problems and business model explorations in China's AI smart hardware track, offering high reference value for industry research, summarized below:

1. In terms of new industry trends, China's AI smart hardware sector is experiencing a new wave of entrepreneurship. Among new startups founded after 2023, 75.9% have secured financing. The track remains in its early stage, and the market structure is far from set. Geographically, it has formed a dual-core industrial布局 with Beijing and Shenzhen, with Shenzhen emerging as the core hub thanks to its supply chain advantages. Embodied intelligent robots are the current hot spot for financing, while vertical tracks such as wearables are growing rapidly, and the mainstream development route is adding AI capabilities to traditional categories through micro-innovation.

2. In terms of new industry problems, the sector generally faces the "hammer looking for a nail" technology commercialization dilemma. Active interaction technology still faces technical hurdles including large model hallucinations, balancing edge inference and privacy protection, and difficult cost control. The influx of hot capital has created froth, with a large number of projects failing to close the commercialization loop, and AI hardware return rates remain high: the average return rate for AI headphones reaches 30% to 50%.

3. In terms of business model and outlook, the sector has already explored new models such as the dual-line concept+mass production layout and hardware subscription. In the future, it will form a multi-layered ecosystem where large tech players dominate core unified end devices, while startups focus on deep cultivation of vertical scenarios.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

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来源 |IT桔子

2026年6 月28日，由IT桔子主办、一苇资本与中关村科学城公司联合主办的「AI智能硬件新机遇，交互入口争夺战打响」活动在北京举行。汇集到了来自IT桔子、一苇资本、声智科技、灵宇宙、中博聚力等机构的高管出席。

一、报告发布：

AI硬件/智能硬件赛道新锐公司洞察报告

活动开场，IT桔子高级分析师吴梅梅女士发表了IT桔子智能硬件行业分析报告。报告指出这几年中国AI硬件与智能硬件赛道掀起了一波密集的创业浪潮。

通过梳理2023年后成立的新锐公司，总结这个赛道的四大趋势：

1.赛道热度超乎想象。431家创业公司中，已有327家完成融资，融资率高达75.9%。其中，2026上半年就有179家公司获投，资本共识极为罕见。

2.融资生态格局智能机器人主导，百花齐放。具身智能机器人融资比较突出、吸金能力最强。智能戒指、AI眼镜、运动健康穿戴等可穿戴赛道虽体量较小，但增速明显、想象空间大。融资结构上，天使轮占半数以上，仍处早期，格局远未定型，窗口仍然敞开。

3.地理分布：深圳独占鳌头，京深双核成型。深圳以95家高居第一（占22%），北京44家、上海50家紧随其后。中国深圳的世界级硬件供应链在全球具有领先独特的优势。

4.典型案例：六大细分赛道各有微创新。智能戒指正从健康监测走向触觉AI交互；AI眼镜有文博导览、户外影像等多个垂直场景；AI玩具引入情感引擎和虚拟人格系统，陪伴属性强；这些公司基本都在用新的AI技术做旧的品类。人形机器人中，交互派、本体派、大脑派等路线多元，智元率先量产商业化，赛道竞争进入白热化阶段。

一句话总结：“整个赛道非常广阔，当技术下沉，创业者“不用重复造轮子”，着眼于微创新，专注在细分场景及人群中建立壁垒。”

二、声智科技：

从声学推动感知交互升级

声智科技首席产品官黄赟贺女士在《AI技术向终端渗透推动感知交互智能升级》的主题分享环节指出，AI硬件创业普遍面临“锤子找钉子”困境——手握技术却找不到可量产的产品载体。她强调，产品创新需兼顾技术能力与市场接受度，阶段性成功应立足于当前技术门槛、用户需求、成本控制与形态微创新的平衡，而非盲目追求颠覆式创新。

黄赟贺女士介绍在技术层面，声智科技专注于声学AI模型技术研发，深耕Physical AI领域。目前，公司已形成成熟的声学AI技术方案，可为机器人提供高精度听觉感知能力，并赋能L3、L4级高阶自动驾驶，实现非视距、超视距风险感知与预警，进一步提升复杂场景下的安全性和环境感知能力。在硬件产品上，声智科技AI耳饰耳机凭借高颜值创新形态快速打开市场，团队依托海外用户付费偏好持续迭代产品，验证了技术升级必须依托真实用户数据。

当前语音交互仍依赖唤醒指令，多轮自然交互尚未真正落地。黄赟贺女士表示未来AI硬件需依托传感器升级和物理AI发展，实现无唤醒主动感知交互，并立足本土需求自主创新，打造属于中国的下一代AI终端产品。

三、圆桌对话：

智能硬件创业者、投资人的观察与洞见

声智科技首席产品官黄赟贺、灵宇宙资深产品负责人刘翠涛、中博聚力品牌战略负责人刘红艳出席了以《AI智能硬件新机遇，交互入口争夺战打响》为主题的圆桌对话环节，一苇资本董事王思萌担任主持。

以下为圆桌对话内容：

一苇资本董事王思萌：过去如果说到交互入口，大家一定第一个想到的就是手机，想到苹果、三星、HMOV这些大厂；那在ai时代下，不知道大家觉得未来的交互入口仍然会走向大一统的超级硬件，还是会分割成更加碎片化、场景化的专属硬件？在这个新的时代背景下，大厂与创业公司又会是怎样的竞争关系呢？

声智科技首席产品官黄赟贺：统一性终端依然会占据重要位置，但面向特定场景的垂直功能载体同样会不断涌现。目前AI终端有两条发展路径——为AI匹配硬件载体，或为场景硬件赋予AI能力，创业公司可以基于目标人群、技术能力和市场环境等多重因素来定义产品形态。当市场需求明确、用户付费意愿成立时，不必等技术尽善尽美，可以先进入市场获取验证。

灵宇宙资深产品负责人刘翠涛：初创团队短期内可以选择更细分的场景和更垂直的人群，以此积累足够的数据反哺产品迭代。在硬件选型上，可以审视该品类是否已被头部品牌占据心智，若选择手表、戒指等已有强势玩家的形态，用户对基础体验已有较高预期，需要先做好基础功能，再叠加AI能力作为差异化，而非一上来就比拼智能化。

中博聚力品牌战略负责人刘红艳：未来AI硬件领域可能会形成多层次的生态格局。大厂虽然拥有生态、供应链和资源聚合的优势，但其触角也未必能覆盖所有垂直领域。创业企业可以基于自身资源禀赋和核心优势，做好中长期战略规划，选准赛道后在软硬件协同、产品商业化上持续深耕，完全有可能凭借某个单点爆发脱颖而出。

一苇资本董事王思萌：现在大家争夺入口，表层看上去是硬件产品的pk，底层是操作系统、交互算法、用户数据的比拼。关于ai硬件的壁垒，到底是在软件还是硬件呢？从商业化的角度，是先铺硬件占领用户心智，还是先打磨交互技术再量产产品呢？

声智科技首席产品官黄赟贺：AI硬件创业需兼顾消费与科技双重视角：消费投资人会关注情绪价值与品牌心智，科技投资人会看重技术壁垒与团队背景。声智科技采取"概念款+量产款"双线策略：量产款以高性价比和颜值建立品牌心智；概念款着眼未来技术突破。硬件退货、售后成本高，行业经营压力大，需贴合市场灵活经营才能穿越周期存活。

灵宇宙资深产品负责人刘翠涛：当前AI硬件创业主力为大央企与字节系出身者，两者融资逻辑不同，但在产品落地上面临共同挑战：一是对AI模型的深度理解，二是硬件实操经验，如何摸透硬件选型、成本差异等非透明信息。商业模式上，AI硬件可探索硬件不赚钱、靠订阅盈利的模式，但前提是同步控制硬件BOM成本与模型推理成本，否则两头亏损难以为继。

中博聚力品牌战略负责人刘红艳：投资核心在于验证AI技术的落地载体与应用场景。产品完美固然重要，但市场能否接受、销量能否打开、现金流能否持续才是根本。当前AI企业普遍烧钱，关键在于找准切入场景，通过端侧算力与软硬协同适配市场，最终实现销售增长与可持续发展，完成技术到场景的商业化闭环才是重中之重。

一苇资本主持人王思萌：刚才黄总也提到了退货率这一块，想与黄总与刘总了解一下，咱们行业的平均退货率大概是多少？一个比较成功的硬件产品的退货率水平是什么范围？

声智科技首席产品官黄赟贺：声目前耳机行业退货率情况的话，据悉AI耳机平均达30%~50%，海外因退货成本顾虑可能反而会低一些。

灵宇宙资深产品负责人刘翠涛：退货率需分阶段看：早期极客与媒体用户包容度高、退货少，但其使用习惯与目标用户差异大，反馈的代表性有限。量产进入大众市场后，真实问题才集中暴露，此时方能获取有效反馈驱动产品迭代。灵宇宙推出的教育陪伴类产品量产后退货率仅为行业均值的一半。

一苇资本董事王思萌：因为大模型现在正在向端侧下沉，很多本地硬件开始从被动应答升级为主动感知用户需求。所以这里也想跟大家一起展望下，主动式人机交互会催生哪些全新的硬件品类？未来2—3年，国内AI智能硬件最大的产业红利会集中在哪些场景？

声智科技首席产品官黄赟贺：主动交互技术因大模型幻觉、物理约束缺失及环境感知不足，实际体验尚未成熟，仅健康可穿戴设备实现有限主动提醒。行业应借鉴互联网早期经验，找准细分人群并放大优势而非纠结普遍存在的技术局限。中国创业者具备营销、产品定义等独特优势，核心在于找到目标用户、建立连贯使用体验，先跑通市场再逐步迭代，静待技术成熟与爆发点。

灵宇宙资深产品负责人刘翠涛：主动交互是AI硬件的重要演进方向。设备通过多模态感知（视觉、听觉、生理信号等）判断合适时机，发起有意义的互动，建立用户理解与情感链接。实现这一能力需要解决两个核心问题。一是时机判断。做到避免打扰， "该说话时说话"。二是长期记忆：积累用户偏好与交互历史，让互动越来越自然。工程化落地是当下难题，尤其在端侧推理能力与隐私保护的平衡上。硬件形态需因人群而异，如女性重外观，儿童需轻量易操作。

中博聚力品牌战略负责人刘红艳：中博聚力近期投资的星尘智能是全球首家实现绳驱AI机器人量产的企业，目前估值已突破百亿人民币。对于AI硬件赛道持续观望，细分赛道成果难判。当前一级、二级市场AI赛道热度高，热钱涌入伴生泡沫，未来将经历大浪淘沙与赛道分化。行业尚处于商业化早期，多处于原型验证阶段。判断未来趋势需综合各赛道比较概率，审慎评估哪些细分方向能真正跑通。

一苇资本董事王思萌：请教中博聚力刘总，目前AI硬件的融资热度一直居高不下，风口项目也是层出不穷，但泡沫其实也同步显现。站在投资人的角度，您筛选优质项目、避开同质化泡沫，会重点参考哪几条核心标准？

中博聚力品牌战略负责人刘红艳：AI赛道火热但优质项目甄选难度高。中博聚力以"真一新"为投资理念：真，即真愿景、真实力、真可靠的团队；一，即只投大赛道中的龙头或头部企业；新，必须是新世界产物、最前沿技术。AI赛道虽热，但整体商业化尚处早期，技术关口待突破，产业生态搭建路长。中博聚力将沿着国家先导战略方向指引，持续发掘代表未来方向、市场空间广阔的高成长企业。

一苇资本董事王思萌：请三位嘉宾用一句话总结，在这场交互入口大战中，企业想要最终胜出，最核心的制胜关键是什么？

声智科技首席产品官黄赟贺：我的一句话是“Hardware is hard”，声智科技早期业务主要构成是向终端公司提供远场语音交互服务里涉及的声学AI底层算法和声学阵列模组等。但发展阶段里开始拓展自主品牌的AI硬件，也是在于自己下场做ai硬件可直接获取用户的需求反馈，助力算法迭代。AI硬件创业涵盖软件、硬件、供应链、营销多层挑战，敢入局者需勇气与坚持。AI硬件亦是中国企业走向世界、展现创新力的最佳载体之一。

灵宇宙资深产品负责人刘翠涛：硬件创业在团队布局上需因地制宜。品牌、市场和融资团队适合设在北上广，但供应链建议优先落地深圳。从硬件选型、模具开发到模组采购，深圳完整成熟的产业链具备突出优势，能显著降低硬件落地过程中的试错成本。

中博聚力品牌战略负责人刘红艳：未来脱颖而出的AI企业，必先选准有前景的赛道，并能打通从技术、产品到商业化落地的完美闭环。虽处烧钱阶段，但能否烧出可持续盈利模式是关键。企业需让产品获市场认可，形成收入与利润的增长飞轮，实现长期价值提升，这不仅是投资人关注的重点，也是企业能否长期稳健发展的根本所在。

注：文/IT桔子，文章来源：IT桔子(公众号ID：itjuzi521)，本文为作者独立观点，不代表亿邦动力立场。

文章来源：IT桔子

FAQ回顾

AI智能硬件赛道当前有哪些发展趋势？

2023年后成立的AI智能硬件新锐公司共431家，融资率高达75.9%，2026上半年就有179家获投；融资生态以具身智能机器人为主导，智能戒指、AI眼镜等可穿戴赛道增速明显；地域上形成京深双核，深圳以95家企业居首，赛道整体仍处早期，格局未定。

AI智能硬件创业公司有哪些生存发展建议？

创业公司可优先选择细分场景与垂直人群切入，平衡技术能力、用户需求、成本控制与形态微创新，不必盲目追求颠覆式创新；可将供应链落地深圳降低试错成本，打通技术到场景的商业化闭环，获取真实用户反馈反哺产品迭代。

AI耳机行业的平均退货率大概是多少？

当前AI耳机行业平均退货率达30%~50%，海外市场因退货成本顾虑，退货率相对更低；产品早期面向极客、媒体用户时退货率较低，量产进入大众市场后真实问题才会集中暴露，此时方能获取有效用户反馈。

AI智能硬件赛道投资人筛选项目的核心标准是什么？

中博聚力等投资机构以「真一新」为核心筛选标准：「真」指团队有真愿景、真实力、真可靠；「一」指优先选择大赛道中的龙头或头部企业；「新」指项目为前沿技术、属于符合未来发展方向的新市场产物。