生产力应用ARR已超6亿元，美图找到了更“值钱”的需求

This article shares the latest development direction of AI productivity applications and Meitu's latest business results after its transformation, with plenty of core information and practical insights.

1. Today's AI productivity tools have shifted from helping people create content to helping people run businesses, targeting small and medium-sized business owners who understand their operations but lack content production expertise. These tools drastically lower the professional barrier to content creation, allowing ordinary people to produce qualified marketing content without a dedicated professional team.

2. By the first half of 2026, Meitu's productivity applications delivered impressive growth: annual recurring revenue (ARR) reached 620 million RMB, monthly active users (MAU) hit 33 million, and paid subscribers reached 2.35 million. Core products including Kaipai, Meitu Design Studio, and overseas product Vmake Labs all maintained strong high-speed growth.

3. AI has now deeply integrated into actual production workflows, and users are willing to pay for clear efficiency gains and tangible business outcomes. Meitu's new products achieve an average revenue per paying user (ARPPU) up to 13 times that of traditional applications, validating the commercial viability of this market direction.

This article outlines new consumer trends in brand content marketing, and provides actionable directions for brands to cut costs, boost efficiency, and build out their content marketing strategy.

1. User demand and market conditions have shifted significantly. A large number of small and medium-sized brands and offline merchants understand their own business but lack professional content production capabilities, and users are willing to pay for content production capabilities that directly drive commercial returns. This market demand remains largely unmet.

2. AI enables brands to convert industry expertise into professional content, covering core brand needs including short video scriptwriting and editing, marketing material production, and e-commerce visual output. It can drastically cut labor costs for in-house content teams and improve content production efficiency.

3. Drawing from Meitu's operational experience, high-value vertical sectors including healthcare, education, beauty, insurance and real estate are the highest-demand segments for AI-powered content production. Entering these sectors delivers far higher average user payments than the broader market, and brands can leverage these AI tools to quickly close gaps in their in-house content capabilities.

This article outlines new shifts in the content e-commerce space, points out new growth opportunities for sellers, and provides risk warnings and actionable guidance.

1. Current market shifts and opportunities: Social commerce platforms such as TikTok have no shortage of general creators, but lack sellers that can consistently produce professional content and convert content into commercial revenue. There is a large unmet demand among small and medium-sized sellers who understand their business but lack content capabilities, which represents a new growth opportunity.

2. Actionable solution: Mature AI tools now exist that cover the entire content production workflow, from topic selection and script generation to editing and e-commerce visual output, with customization options for different vertical industries. Small and medium-sized sellers can produce professional marketing materials without building an in-house professional content team by leveraging these tools.

3. Risk warning: Content production has been fully integrated with AI. Sellers that do not adopt AI tools to improve efficiency will fall behind competitors in both output speed and production costs, putting them at a disadvantage in traffic competition. Adopting AI tools early helps sellers secure first-mover advantage.

Meitu's exploration of AI productivity applications offers valuable insights for factories pursuing digital transformation and expanding new business opportunities.

1. Demand for production and marketing: If factories develop their own brands and operate direct-to-consumer retail, most face the pain point of lacking a professional content team. AI productivity tools help factories quickly produce qualified marketing materials, lower barriers to content production, and resolve the content gap for private brand marketing.

2. Insights for digital transformation: AI has been deeply integrated into real-world commercial production processes and delivers direct cost reduction and efficiency gains. For factories pursuing digital transformation, prioritizing AI application scenarios that directly generate commercial returns allows them to see transformation gains much faster.

3. New business opportunities: Many factories that provide original equipment manufacturing (OEM) services for brands can leverage their deep industry knowledge and combine it with AI content production capabilities to offer supporting marketing content production services to partner brands, opening up a new revenue stream. This is an emerging direction amid the current AI boom.

This article outlines new development trends in the AI services industry, clarifies core customer pain points, and provides feasible directions for solutions.

1. Core customer pain points in the market: A large number of small and medium-sized enterprises and offline merchants understand their business but lack professional content production capabilities, and cannot meet the requirement of social and e-commerce platforms for consistent marketing content output. This pain point represents a large unmet market gap that has not been fully addressed.

2. New industry development trends: AI productivity applications have shifted from simply assisting creation to empowering business operations, with their scope continuously expanding. The upgrade of traditional software to AI-native products is a clear major trend, and building products around proprietary data and closed-end workflows is the core opportunity direction.

3. Feasible implementation path: Following Meitu's example, providers can build end-to-end closed content production workflows for high-value vertical sectors such as healthcare and beauty, and integrate multiple AI agents to collaboratively meet user demand. These products deliver far higher user willingness to pay and ARPPU than general products, with larger commercialization potential.

Meitu's transformation from a photo editing tool provider to an AI productivity application provider points out a new development direction for all types of platforms, and provides guidance for risk mitigation.

1. Core demand of platform merchants: For small and medium merchant creators on platforms, the core need is the ability to consistently produce professional content and convert content into commercial value. Most existing tools only solve single-step creation problems and do not cover end-to-end workflow needs, which represents an area for platforms to optimize.

2. Actionable latest practices for platforms: Platforms can launch integrated end-to-end AI content production tools with custom settings for different vertical industries. This not only serves platform merchants to improve retention, but also opens up new revenue streams. Per Meitu's data, the ARPPU of this type of business is far higher than that of general tool-based businesses, with much larger revenue potential.

3. Risk mitigation guidance: When rolling out AI applications, platforms should avoid pure concept projects with no real practical value, and focus on specific production scenarios that directly deliver commercial returns to users. This is the only way to achieve sustained paid growth and avoid the problem of pouring resources into projects that deliver no actual returns.

This article presents new trends in the current AI application industry, provides a new case study and research direction for AI industry research, and offers substantial reference value.

1. New industry trends: Current AI applications have shifted from early-stage B2C entertainment and consumption scenarios to B2B business operation scenarios. Their core positioning has shifted from assisting creation to empowering business operations, and the blue ocean market consists of small and medium-sized business operators who understand their business but lack professional content capabilities. The payment logic has shifted from paying for functional experience to paying for efficiency and results, with ARPPU far higher than that of traditional application scenarios.

2. Business model validation: Meitu's practice validates the three major opportunity directions for AI applications proposed by industry analysts: the evolution of traditional software to AI-native products, software taking over work previously completed by humans, and building new applications around closed-end workflows. It proves this business model is viable, and provides a reference sample for the transformation of traditional tool-based enterprises.

3. New questions for future research: This direction is still in the early validation stage. The long-term implementation effects and ultimate commercial returns across different vertical scenarios remain to be observed, and the full impact of AI's deep penetration into commercial production scenarios on the entire content industry requires continuous follow-up research.