Why Capital Prefers "Profitable" AI Applications in 2026?
In 2026, the logic for AI capital valuation shifts from "scale priority" to "commercialization quality validation," with positive gross margin and high retention becoming core metrics. Moonshot abandoned DAU assessment to focus on Agents, while companies like Haiyi demonstrated high-quality commercialization feasibility through 40%+ gross margins, $60 ARPU, and 60%+ renewal rates. Haiyi achieved rapid iteration across three product lines by leveraging "capability interlocking" (generation/intera
Analysis
Summary
In 2026, the logic for AI capital valuation shifts from "scale priority" to "commercialization quality validation," with positive gross margin and high retention becoming core metrics. Moonshot abandoned DAU assessment to focus on Agents, while companies like Haiyi demonstrated high-quality commercialization feasibility through 40%+ gross margins, $60 ARPU, and 60%+ renewal rates. Haiyi achieved rapid iteration across three product lines by leveraging "capability interlocking" (generation/interaction/distribution/monetization) and a "closed user journey loop" (character entry → story consumption → interaction accumulation). The tripartite synergy of "capital + industry + government" investment validated Haiyi's comprehensive advantages in commercial data, ecosystem scalability, and regional impact, establishing global content assets as a competitive moor. AI applications must move beyond internet-style land-grabbing; continuous compute costs require clear unit economics, or scaling will lead to degraded experience and retention collapse.
Deep Analysis
TL;DR
- In 2026, the logic for AI capital valuation shifts from "scale priority" to "commercialization quality validation," with positive gross margin and high retention becoming core metrics.
- Moonshot abandoned DAU assessment to focus on Agents, while companies like Haiyi demonstrated high-quality commercialization feasibility through 40%+ gross margins, $60 ARPU, and 60%+ renewal rates.
- Haiyi achieved rapid iteration across three product lines by leveraging "capability interlocking" (generation/interaction/distribution/monetization) and a "closed user journey loop" (character entry → story consumption → interaction accumulation).
- The tripartite synergy of "capital + industry + government" investment validated Haiyi's comprehensive advantages in commercial data, ecosystem scalability, and regional impact, establishing global content assets as a competitive moor.
- AI applications must move beyond internet-style land-grabbing; continuous compute costs require clear unit economics, or scaling will lead to degraded experience and retention collapse.
Why It Matters
This article reveals a fundamental shift in the 2026 AI industry valuation paradigm: moving from chasing DAU to validating sustainable commercialization capabilities, providing practitioners with a core framework for assessing long-term AI application value. By analyzing cases like Haiyi, the article explains how to build a virtuous cycle of positive gross margins and high retention under high compute costs, offering direct guidance for AI entrepreneurs on product strategy and fundraising.
Technical Breakthroughs
- New Commercialization Benchmarks: Replacing DAU as the sole hard metric with gross margin (covering compute and acquisition costs), ARPU (average revenue per paying user), and renewal rate—these three collectively determine true product value and risk resistance.
- Capability Interlocking Architecture: Decomposing the product system into five reusable capability modules—multimodal generation, agent interaction, content distribution/recommendation, ad growth, and monetization. After SeaArt community validated basic logic, capabilities migrated to MoreShort (short dramas) and SeaSoul (character interaction), compressing new product validation cycles from 36 months to 4–6 months.
- Closed User Behavior Path: Unified underlying logic—"characters are entry points, stories are consumption, interactions are relationship building." Though the three product lines differ in form (creation/consumption/interaction), they share the same user behavior model, ensuring consistency in asset accumulation and commercial conversion.
- Global Operation Data Support: Cumulative 65 million registered users, over 30 million monthly active users (90%+ overseas), generating 10 million images and 500,000 videos daily, forming a scalable AI creation asset library (including models, LoRAs, workflows) to support commercialization.
- Ecosystem Collaboration Infrastructure: Offering B-end/P-end/OPC model services, AI asset management, and advertising tools to support creators from character setting to commercial distribution; partnering with Visual China Group to address compliance/channel issues, cultivating solo-founder ecosystems via Tianfu New Area.
Industry Insights
- Strategic Shift: AI enterprises should stop relying on compute subsidies for scale-driven internet approaches, prioritizing business models with clear unit economics to ensure positive gross margins and sustainable retention—or scaling will accelerate losses.
- Key Product Matrix Construction: Successful applications require complete capability loops (generation + distribution + monetization); single-point breakthroughs are hard to replicate.建议 using core scenarios (e.g., character interaction) as entry points to connect content consumption and social accumulation, creating flywheel effects.
- Ecosystem Collaboration as New Barrier: No single company can independently tackle global compliance and channel challenges; actively integrating industry partners (e.g., copyright platforms), local government funds, and developer ecosystems builds "capital + industry + government" collaborative networks to accelerate commercialization.
Disclaimer: The above content is generated by AI and is for reference only.