On December 24th, the 2025 Smart Home Innovation Conference concluded as scheduled. The impressive lineup of guests outlined the core landscape of the industry, from leaders of major home appliance companies to AI business heads of tech giants, and core component suppliers across the supply chain. This star-studded list of attendees underscored the industry’s status as a core application scenario for AI. The atmosphere throughout the conference, where “no topic is complete without AI,” further amplified the excitement. From keynote speeches to roundtable discussions, from product demonstrations to technology releases, AI was the undisputed protagonist, seemingly heralding the arrival of a fully intelligent era for smart homes. However, behind the excitement, the industry’s inherent pattern of “entry-focused enthusiasm, outside-focused indifference” remained unbroken. For markets outside the smart home industry, AI functionality remains largely a “cool” concept, failing to generate genuine consumer demand. Meanwhile, the heated discussions within the industry seem more like a self-congratulatory frenzy among practitioners. Alarmingly, even in one of the industries closest to AI, the smart home sector is revealing increasingly prominent problems, the most critical being the lagging AI application model. The current mainstream model remains stuck in the traditional approach of “passively processing sensor data to trigger preset scenarios,” failing to keep pace with the new trend of “active perception and intelligent scenario generation” driven by large-scale models by 2025. This gap in modeling has become a key bottleneck hindering industry breakthroughs. The most pressing issue is the technological gap, which directly prevents the industry from achieving a leap from “passive triggering” to “active generation.” 2025 is a crucial year for AI large-scale models to move from “accumulating computing power” to “being able to get things done.” Six core breakthroughs, including training paradigm innovation, native multimodal unification, and the maturity of intelligent agents, form the technological foundation for “proactive perception and intelligent scene generation.” However, the smart home industry is lagging behind by several generations in absorbing and transforming these cutting-edge technologies. In particular, the core track of generative AI has almost become a “marginal topic” in the various topics of the conference; and AI programming, as an important breakthrough for improving industry efficiency and promoting model upgrades, is rarely mentioned by companies. This contrasts sharply with the active exploration of AI programming by Alibaba’s Qoder and ByteDance’s related tools, causing the industry to miss the opportunity to promote the implementation of scene generation models through the iteration of technical tools.
What’s more prominent is the ambiguity and outdated nature of the technology applications. Essentially, this stems from a lack of understanding within the industry regarding the core capabilities of “active generation” of large models, remaining trapped within the framework of traditional passive models. Currently, the industry’s positioning of large and small models remains unclear. Most companies’ large model solutions either remain in the experimental and theoretical stages, lacking viable commercial applications; or they continue to focus on concepts like image recognition and behavioral data processing, which have been repeatedly hyped since 2024. Essentially, these are still pattern matching based on traditional probability statistics, only supporting “passive response to sensor data and triggering preset scenarios,” unable to achieve the upgrade to “active perception and intelligent scenario generation.” Looking back at the leapfrog development of generative AI in 2025, the most crucial breakthrough lies in moving beyond the underlying logic of traditional large models that “merely fit the probability distribution of data,” and entering a new stage of “probabilistic engineering + proactive cognitive construction.” This breakthrough provides the underlying support for “intelligent scene generation,” allowing AI’s capabilities in areas such as environmental perception, aesthetics, and ethical considerations to be applied to home scenarios, achieving more user-friendly intelligent processing. This “proactive perception, intelligent scene generation” model essentially transforms AI from a “scene executor” to a “scene planner.” Its intelligence is not only based on fundamental conditions such as user habits and device deployment, but also deeply integrates diverse capabilities such as environmental perception and aesthetic cognition. At the environmental perception level, the new generation of large-scale models has achieved a leap from “single-parameter recognition” to “full-scene dynamic cognition,” which is a prerequisite for proactive scene generation. In the aesthetic field, the large-scale models have broken through the limitations of “style imitation,” forming a deep understanding and creative output of aesthetic logic, making scene generation more in line with user aesthetics. The integration of civilization and ethics makes “intelligent scene generation” more in line with social order and family needs, serving as an important guarantee for model upgrades. Reviewing the AI development trend of the smart home industry in 2025, a contradictory situation is evident: while the industry’s enthusiasm for AI continues to rise, companies within the sector are becoming increasingly rational in their investments, with few new large-scale investments being implemented. This phenomenon is certainly related to the intensified inflation within the industry and increased pressure on corporate profits, but the deeper reason lies in the rational return after the AI hype subsides. However, this “excessive rationality” may be causing the smart home industry to miss a historic opportunity—the window of opportunity for a model transformation from “passive triggering” to “proactive generation.” By 2025, generative AI had already achieved a significant breakthrough, and smart homes, as a core application scenario for AI, are inevitably undergoing model upgrades. If the industry continues to merely repeat hype of old, passive models and fails to keep up with the wave of model transformation driven by generative AI, it will not only struggle to gain genuine market recognition for the value of smart homes but may also be marginalized in future competition. The conclusion of the 2025 Smart Home Innovation Conference served as both a summary of the industry’s current AI development and a wake-up call for model transformation. The AI boom continues, but the window for technological iteration and model upgrades never waits for those who hesitate. Smart home companies need to rationally assess and re-examine the core value of generative AI, proactively bridge the technological gap, and integrate aesthetics, cognition, and ethics into scenario design. Only by breaking free from the vicious cycle of traditional passive models can they truly transform the technological advantages of AI into market competitiveness and seize the initiative in the industrial transformation of the smart era.
