When the “Cognitive Bottleneck” Becomes the Hidden Ceiling on Industry Growth
Over the past decade of rapid expansion in China’s gaming industry, 37 Interactive Entertainment has grown into a company with annual revenues approaching tens of billions of RMB and a complex global operating footprint. Extensive R&D pipelines, cross-market content production, and multi-language publishing have collectively pushed its requirements for information processing, creative productivity, and global response speed to unprecedented levels.
From 2020 onwards, however, structural shifts in the industry cycle became increasingly visible: user needs fragmented, regulation tightened, content competition intensified, and internal data volumes grew exponentially. Decision-making efficiency began to decline in structural ways—information fragmentation, delayed cross-team collaboration, rising costs of creative evaluation, and slower market response all started to surface. Put differently, the constraint on organizational growth was no longer “business capacity” but cognitive processing capacity.
This is the real backdrop against which 37 Interactive Entertainment entered its strategic inflection point in AI.
Problem Recognition and Internal Reflection: From Production Issues to Structural Cognitive Deficits
The earliest warning signs did not come from external shocks, but from internal research reports. These reports highlighted three categories of structural weaknesses:
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Excessive decision latency: key review cycles from game green-lighting to launch were 15–30% longer than top-tier industry benchmarks.
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Increasing friction in information flow: marketing, data, and R&D teams frequently suffered from “semantic misalignment,” leading to duplicated analysis and repeated creative rework.
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Misalignment between creative output and global publishing: the pace of overseas localization was insufficient, constraining the window of opportunity in fast-moving overseas markets.
At root, these were not problems of effort or diligence. They reflected a deeper mismatch between the organization’s information-processing capability and the complexity of its business—a classic case of “cognitive structure ageing”.
The Turning Point and the Introduction of an AI Strategy: From Technical Pilots to Systemic Intelligent Transformation
The genuine strategic turn came after three developments:
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Breakthroughs in natural language and vision models in 2022, which convinced internal teams that text and visual production were on the verge of an industry-scale transformation;
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The explosive advancement of GPT-class models in 2023, which signaled a paradigm shift toward “model-first” thinking across the sector;
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Intensifying competition in game exports, which made content production and publishing cadence far more time-sensitive.
Against this backdrop, 37 Interactive Entertainment formally launched its “AI Full-Chain Re-engineering Program.” The goal was not to build yet another tool, but to create an intelligent decision system spanning R&D, marketing, operations, and customer service. Notably, the first deployment scenario was not R&D, but the most standardizable use case: meeting minutes and internal knowledge capture.
The industry-specific large model “Xiao Qi” was born in this context.
Within five minutes of a meeting ending, Xiao Qi can generate high-quality minutes, automatically segment tasks based on business semantics, cluster topics, and extract risk points. As a result, meetings shift from being “information output venues” to “decision-structuring venues.” Internal feedback indicates that manual post-meeting text processing time has fallen by more than 70%.
This marked the starting point for AI’s full-scale penetration across 37 Interactive Entertainment.
Organizational Intelligent Reconfiguration: From Digital Systems to Cognitive Infrastructure
Unlike many companies that introduce AI merely as a tool, 37 Interactive Entertainment has pursued a path of systemic reconfiguration.
1. Building a Unified AI Capability Foundation
On top of existing digital systems—such as Quantum for user acquisition and Tianji for operations data—the company constructed an AI capability foundation that serves as a shared semantic and knowledge layer, connecting game development, operations, and marketing.
2. Xiao Qi as the Organization’s “Cognitive Orchestrator”
Xiao Qi currently provides more than 40 AI capabilities, covering:
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Market analysis
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Product ideation and green-lighting
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Art production
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Development assistance
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Operations analytics
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Advertising and user acquisition
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Automated customer support
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General office productivity
Each capability is more than a simple model call; it is built as a scenario-specific “cognitive chain” workflow. Users do not need to know which model is being invoked. The intelligent agent handles orchestration, verification, and model selection automatically.
3. Re-industrializing the Creative Production Chain
Within art teams, Xiao Qi does more than improve efficiency—it enables a form of creative industrialization:
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Over 500,000 2D assets produced in a single quarter (an efficiency gain of more than 80%);
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Over 300 3D assets, accounting for around 30% of the total;
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Artists shifting from “asset producers” to curators of aesthetics and creativity.
This shift is a core marker of change in the organization’s cognitive structure.
4. Significantly Enhanced Risk Sensing and Global Coordination
AI-based translation has raised coverage of overseas game localization to more than 85%, with accuracy rates around 95%.
AI customer service has achieved an accuracy level of roughly 80%, equivalent to the output of a 30-person team.
AI-driven infringement detection has compressed response times from “by day” to “by minute,” sharply improving advertising efficiency and speeding legal response.
For the first time, the organization has acquired the capacity to understand global content risk in near real time.
Performance Outcomes: Quantifying the Cognitive Dividend
Based on publicly shared internal data and industry benchmarking, the core results of the AI strategy can be summarized as follows:
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Internal documentation and meeting-related workflows are 60–80% more efficient;
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R&D creative production efficiency is up by 50–80%;
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AI customer service effectively replaces a 30-person team, with response speeds more than tripled;
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AI translation shortens overseas launch cycles by 30–40%;
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Ad creative infringement detection now operates on a minute-level cycle, cutting legal and marketing costs by roughly 20–30%.
These figures do not merely represent “automation-driven cost savings.” They are the systemic returns of an upgraded organizational cognition.
Governance and Reflection: The Art of Balance in the Age of Intelligent Systems
37 Interactive Entertainment’s internal reflection is notably sober.
1. AI Cannot Replace Value Judgement
Wang Chuanpeng frames the issue this way: “Let the thinkers make the choices, and let the dreamers create.” Even when AI can generate more options at higher quality, the questions of what to choose and why remain firmly in the realm of human creators.
2. Model Transparency and Algorithm Governance Are Non-Negotiable
The company has gradually established:
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Model bias assessment protocols;
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Output reliability and confidence-level checks;
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AI ethics review processes;
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Layered data governance and access-control frameworks.
These mechanisms are designed to ensure that “controllability” takes precedence over mere “advancement.”
3. The Industrialization Baseline Determines AI’s Upper Bound
If organizational processes, data, and standards are not sufficiently mature, AI’s value will be severely constrained. The experience at 37 Interactive Entertainment suggests a clear conclusion:
AI does not automatically create miracles; it amplifies whatever strengths and weaknesses already exist.
Appendix: Snapshot of AI Application Value
| Application Scenario | AI Capabilities Used | Practical Effect | Quantitative Outcome | Strategic Significance |
|---|---|---|---|---|
| Meeting minutes system | NLP + semantic search | Automatically distills action items, reduces noise in discussions | Review cycles shortened by 35% | Lowers organizational decision-making friction |
| Infringement detection | Risk prediction + graph neural nets | Rapidly flags non-compliant creatives and alerts legal teams | Early warnings up to 2 weeks in advance | Strengthens end-to-end risk sensing |
| Overseas localization | Multilingual LLMs + semantic alignment | Cuts translation costs and speeds time-to-market | 95% accuracy; cycles shortened by 40% | Enhances global competitiveness |
| Art production | Text-to-image + generative modeling | Mass generation of high-quality creative assets | Efficiency gains of around 80% | Underpins creative industrialization |
| Intelligent customer care | Multi-turn dialogue + intent recognition | Automatically resolves player inquiries | Output equivalent to a 30-person team | Reduces operating costs while improving experience consistency |
The True Nature of the Intelligent Leap
The 37 Interactive Entertainment case highlights a frequently overlooked truth:
The revolution brought by AI is not a revolution in tools, but a revolution in cognitive structure.
In traditional organizations, information is treated primarily as a cost;
in intelligent organizations, information becomes a compressible, transformable, and reusable factor of production.
37 Interactive Entertainment’s success does not stem solely from technological leadership. It comes from upgrading its way of thinking at a critical turning point in the industry cycle—from being a mere processor of information to becoming an architect of organizational cognition.
In the competitive landscape ahead, the decisive factor will not be who has more headcount or more content, but who can build a clearer, more efficient, and more discerning “organizational brain.” AI is only the entry point. The true upper bound is set by an organization’s capacity to understand the future—and its willingness to redesign itself in light of that understanding.
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