On New Year’s Eve 2026, a surge of customers returned to KTV rooms across Chinese cities. The scene that greets many young guests today, however, is different: beside the microphone sits an AI system that scores, coaches and ranks every performance in real time, turning a once private ritual of singing and letting go into a competitive, quantified spectacle.
Operators hope technology will arrest a decade-long slide. Once ubiquitous, with over 120,000 storefronts at its peak, China’s KTV sector had shrunk to fewer than 50,000 venues by 2024 as younger consumers drifted to concerts, immersive games and app-based social entertainment. Faced with empty rooms on weekdays and an aging core clientele, several chains have chosen AI as their rehabilitation plan — investing heavily in scoring engines, automatic music videos and algorithmic promotions.
MeiKTV (魅KTV), one of the most conspicuous experimenters, has poured more than RMB 200 million into research and development since 2018. Its system captures singers’ voices, compares waveforms to original recordings and produces instant diagnostics: pitch deviations, rhythm errors and prescriptive prompts such as “increase chest resonance.” For many users those pop-up evaluations read less like coaching than public adjudication.
The technology is not merely diagnostic; it is gamified. Customers who pick AI-equipped rooms are automatically entered into daily national rankings, and chains tie concrete rewards — for example a COACH handbag reported worth RMB 5,000–8,000 — to top placements. That incentive has created a small but intense subculture of “score hunters” who repeatedly sing the same high-scoring track until the algorithm yields an awardable mark.
Pushback has been swift. Social media is full of complaints that the systems are cold, intrusive and commercially coercive: higher-priced AI rooms cannot be switched to manual mode, automatic MVs are sometimes jarring, and post-performance clips can be awkwardly circulated by friends. Some venues charge extra for AI-based pitch correction, and generated MVs — which reduce operators’ need to license original video content — often pair melancholic ballads with incongruous, algorithmically produced visuals that undermine emotional immersion.
Technically, the systems do what they are designed to do: quantify objective features such as pitch accuracy, timing and timbre similarity to a reference recording. That makes them vulnerable to optimisation strategies that have nothing to do with artistry — choosing songs with similar vocal timbre or repeating performances to game the score. What they do not do well is judge the subjective qualities of performance: phrasing, emotional depth and audience connection remain resistant to robust algorithmic evaluation.
For operators the arithmetic is straightforward. AI MVs and automated scoring can cut costs tied to licensing and staffing, while marketing narratives about “tech-enabled” venues help attract a younger demographic. But the conversion between novelty and repeat business is not guaranteed. Early adopters like MeiKTV and peer chain Xingjuhui (星聚会) publicly cite nine-figure investments and multi-year development cycles, yet consumer complaints suggest technology can be a double-edged sword: it draws customers with prizes and spectacle, but it also risks hollowing out the social atmosphere that made KTVs durable.
The broader implications go beyond karaoke. China’s KTV experiment is an instructive case of how consumer services deploy AI to cut costs, gather behavioural data and create new monetisation levers, while running into limits of social acceptability, artistic nuance and regulatory friction around copyright and synthetic media. Whether AI ends up as an invisible service layer that subtly smooths the customer experience or as a visible, contest-driven feature will determine if the industry’s technological bet pays off.