From GameFi to AI GameFi: Evolution Path and Trend Insights into the Next-Generation On-Chain Game Economy Model

On July 23, 2026, the global crypto market exhibited a choppy, volatile pattern amid macro uncertainty and geopolitical risks. Short-term volatility in the macro market has not obscured a structurally accelerating trend from taking shape: the convergence of artificial intelligence and blockchain gaming is redefining the underlying economic logic of GameFi. From “Play-to-Earn” to “Play-to-Own,” from human-driven to AI Agents in symbiosis, GameFi is undergoing a deep overhaul that shifts from gameplay patterns to infrastructure. Starting from the current state of the GameFi industry, this article systematically reviews how AI technology drives a paradigm shift in GameFi economic models and discusses the core logic and potential risks throughout this evolution.

Structural Divergence in GameFi: Elimination and Concentration Behind the Appearance of Prosperity

In 2026, the market size across the entire GameFi sector reached $29.9 billion, and is expected to grow to $259.28 billion by 2035 at a 27% compound annual growth rate. Daily active unique wallets for blockchain games surpassed 7 million, accounting for 28% of the total active usage across decentralized applications on the network. The total number of global blockchain gaming players exceeded 102 million. Judging from macro data, GameFi appears to be in a golden period of rapid growth.

However, micro-level data tells a completely different story. According to industry statistics, 93% of blockchain gaming projects that have accumulated historically have already stopped operating. In early 2026, there were about 2,000 active blockchain games, and the monthly active user retention rate was only about 12%, far below the 25% industry benchmark for traditional mobile games. More than 300 blockchain game projects announced they would shut down in the second quarter of 2025. On average, a GameFi project’s lifecycle lasts only about four months. Industry funding fell from a peak of $5.56 billion in 2022 to $293 million in 2025.

These two sets of data are not contradictory; rather, they are an inevitable result of structural divergence. Only a tiny number of sustainable top-tier projects contribute the vast majority of the industry’s market value and user activity. The top 10% of projects account for 90% of user volume and capital volume. Market size forecasts are based on an assumption that resources continuously concentrate on high-quality projects—not on the assumption that most projects will succeed.

Behind this divergence, three structural shortcomings of the GameFi 1.0 model are reflected:

First, single-utility asset design. In the traditional Play-to-Earn model, the value of in-game NFT assets depends heavily on a single game’s economic model and user activity. Once the game’s popularity declines or the token price collapses, the asset value effectively goes to zero. NFTs held by players lack liquidity, cross-game and cross-ecosystem portability, and reuse capability.

Second, a content supply bottleneck. Blockchain game development cycles are long and costs are high, making the traditional game studio model unable to support high-frequency content updates and gameplay iteration. When content supply cannot keep up with user consumption speed, user churn remains persistently high.

Third, an unsustainable economic model. Most GameFi projects rely on a steady influx of new users to support token prices and asset valuations. Once user growth slows, the economic flywheel reverses immediately. This “Ponzi-like structure” fundamentally limits the long-term development space for blockchain gaming.

AI-Driven Paradigm Shift in Blockchain Gaming: From Tools to Infrastructure

The combination of artificial intelligence and blockchain gaming is not a simple technological overlay, but rather a reconstruction of the production relationships and value distribution logic within blockchain gaming. In 2026, the application of AI Agents in Web3 games is no longer limited to simple script automation; instead, it has evolved into multiple forms of deep integration.

From the perspective of the technical evolution path, AI’s transformation of GameFi can be divided into three layers:

First layer: AI as a content generation tool. This is currently the most widely implemented scenario. Multi-agent AI game engines represented by AKEDO (AKE)—using modular division of labor (world building, rule design, balance tuning, and story filling)—can dramatically lower the threshold for game creation. Users only need to describe their needs in natural language, and the AI agent can collaboratively generate a playable game prototype in about two minutes. This “vibe coding” style of content generation is freeing game creation from professional developers and putting it into the hands of ordinary users. The Sandbox also announced in 2026 the launch of its AI-driven game engine, “The Sandbox Studio,” positioned as a tool for the next generation of creators.

Second layer: AI as autonomous entities within games. AI Agents are evolving from auxiliary tools into “first-class citizens” within game ecosystems. In projects such as TEN Protocol, AI Arena, and Satoshi Strike Force (SSF), agents participate in games as independent entrants, while players take on “brokers” or “coaches” roles—sharing rewards through training, strategy configuration, and staking. This model shifts players from “operators” to “managers,” changing the game’s value creation and distribution logic.

In April 2026, Somnia completed a major positioning transformation and officially became an “Agentic L1”—an ultra-high-performance Layer 1 blockchain built specifically for AI Agents. This infrastructure-level setup indicates that the role of AI Agents in blockchain gaming is extending from the application layer toward the protocol layer.

Third layer: AI as the governance and regulator of economic systems. A more forward-looking application is AI’s dynamic adjustment of a game’s economic system. AI can monitor, in real time, in-game asset prices, trading behavior, and economic indicators, and automatically adjust parameters to maintain stability in the economic system. This “algorithmic central bank” mechanism design is expected to address the key pain point in GameFi 1.0: an economic model that cannot be sustained.

Reconstructing Economic Models: The Triangular Closed Loop of NFT Game Assets, the Creator Economy, and AI

The core innovation of AI GameFi is not a breakthrough in any single technology, but rather the reshaping of the relationships among value creation, value attribution, and value allocation within GameFi economic models.

NFT Game Assets: From Collectibles to Production Inputs

In the GameFi 1.0 era, NFT game assets were more often regarded as collectibles with speculative attributes, whose values fluctuated sharply and lacked practical use cases. In the AI GameFi stage, the positioning of NFTs is undergoing a fundamental shift—from “tradable digital items” to “programmable production inputs.”

Taking the AKEDO ecosystem as an example, its NFT assets (such as AKEDOG NFT) are not only symbols of community identity, but also proof of rights to participate in AI content creation, game publishing, and revenue sharing. The deep binding between NFTs and AI-generated content means that their value no longer depends solely on market speculation; instead, it is linked to real economic output.

From the perspective of market size, the NFT game market is expanding rapidly. According to Research and Markets data, the NFT game market is expected to grow from $582.53 billion in 2025 to $683.79 billion in 2026, with a 17.4% compound annual growth rate. Also, according to Fortune Business Insights statistics, the global NFT game market had a valuation of $6.1 billion in 2025, which is expected to grow to $7.63 billion in 2026 and reach $45.88 billion by 2034. Different statistical scopes lead to different numerical results, but the growth trend is highly consistent.

Creator Economy: From Consumers to Co-builders

AI-driven, low-threshold creation tools are transforming blockchain gaming ecosystems from a one-way model of “developers produce content and players consume content” into a co-creation model of “everyone can create, and everyone can benefit.”

In 2026, the global creator economy market in the gaming sector is expected to grow from $39.06 billion in 2025 to $49.3 billion, with a 26.2% compound annual growth rate. This growth is supported by increased console penetration, expanded broadband networks, the rise of livestreaming platforms, and social media driving gaming content.

In a Web3 context, the meaning of the creator economy becomes even deeper: creators can not only earn revenue through ad revenue sharing and tips, but also realize diversified value monetization by issuing personal tokens, selling NFT assets, and participating in protocol revenue sharing. The NEXUS platform launched a “Streamer Token” feature in July 2026, enabling game creators to issue personal assets and build an on-chain economic ecosystem where fans and creators grow together. This model shifts the creator economy from the Web2-era logic of “platform take-rate” to the Web3-era logic of “value co-creation and shared value.”

AI as the Adhesive in a Closed Loop

AI plays three roles in this triangular closed loop:

• Productivity engine: lowers the barrier to creation, expands the content supply, and provides value carriers for NFT assets and the creator economy.
• Matching and distribution mechanism: efficiently connects users, creators, and assets through algorithmic recommendations and intelligent matching.
• Economic regulator: dynamically monitors and adjusts economic parameters to maintain the system’s long-term sustainability.

The closed loop formed by these three—AI producing content, NFT verified ownership/attribution of assets, and creator economy distribution of value—has become the core economic paradigm of AI GameFi.

Risks and Challenges: Uncertainty Factors in the Paradigm Shift

While the evolution path of AI GameFi is clear, the risks and challenges involved also cannot be ignored.

Risk of technological maturity. The quality of AI-generated game content is still at an early stage, and there remains a gap from truly playable, high-quality games that users can keep over time. The autonomous decision-making ability of AI Agents also faces the “black box” problem—when an agent’s behavior cannot be understood or predicted by humans, its impact on the game’s economic system becomes difficult to control.

Risk of economic models. Although AI-driven creation lowers the threshold on the supply side, it may also result in uneven content quality, where high-quality content is overwhelmed by a large volume of low-quality content. How to strike a balance between “open creation” and “quality control” is a question AI GameFi must answer.

Risk of asset bubbles. With AI empowerment, the value of NFT game assets may again be distorted by excessive speculation. When the financial attributes of assets far outweigh their practical attributes, the market is likely to repeat the cycle of failure from GameFi 1.0. According to industry statistics, 93% of blockchain gaming projects have stopped operating—this reminds us that technological innovation does not automatically translate into commercial success.

Regulatory uncertainty. Issues such as the copyright attribution of AI-generated content and the responsibility attribution for AI Agents’ on-chain actions are still in legal and regulatory grey areas. As the scale of AI GameFi expands, the likelihood of regulatory intervention will rise significantly.

Conclusion

From GameFi to AI GameFi, the evolution of the blockchain gaming economic model is fundamentally a paradigm shift from “finance-driven” to “production-driven.” In the GameFi 1.0 era, the core logic was “using financial incentives to drive user growth,” while in AI GameFi, the core logic is “using AI to lower production barriers, unlock creative potential, and reconstruct value distribution.”

The significance of this shift is that the sustainability of blockchain gaming no longer depends on a continuous influx of new users; instead, it is built on real content production and real economic output. NFT game asset value is supported by practical use cases. The creator economy provides a steady stream of content supply for the ecosystem, and AI, as underlying infrastructure, connects everything into a self-regulating economic system.

Of course, this evolution is still in its early stages. Technological maturity, market validation, and regulatory adaptation all require time. But the direction is already clear: when AI becomes the “new productive force” of blockchain gaming, when every player can become a creator, and when every game asset carries real economic value, the next era of GameFi is just beginning.

FAQ

Q: What is the core difference between GameFi and AI GameFi?

GameFi 1.0 is centered on “Play-to-Earn,” relying on token incentives to drive user growth, and its economic model sustainability is weaker. AI GameFi, on the other hand, reduces the barrier to creation through AI, empowers content production, shifts blockchain gaming from “finance-driven” to “production-driven,” and emphasizes players’ roles as creators along with value distribution changes.

Q: What specific role does an AI Agent play in Web3 games?

AI Agents in Web3 games have three main roles: as a content generation tool assisting game development; as autonomous entities that participate in competitions and economic systems within games; and as economic governors that dynamically adjust game parameters. In 2026, AI Agents have evolved from auxiliary tools into “first-class citizens” in game ecosystems.

Q: How does the value logic of NFT game assets change in AI GameFi?

In AI GameFi, NFTs upgrade from speculative collectibles to programmable production inputs. Their value no longer depends solely on market hype; instead, it is tied to actual economic activities such as using AI-generated content, participating in the game ecosystem, and revenue sharing—making the value support more diverse and stable.

Q: How does the creator economy integrate with blockchain games?

In blockchain games, the creator economy allows creators to realize value monetization by issuing personal tokens, selling NFT assets, and participating in protocol revenue sharing. AI tools lower the creation barrier so more users can take part in content production, forming a complete closed loop of “creation—asset tokenization—revenue generation.”

Q: What are the main risks AI GameFi faces today?

The main risks include: technical risks from inconsistent quality of AI-generated content; risks of asset bubbles caused by improper economic model design; systemic risks arising from unpredictable AI behavior; and legal risks stemming from unclear copyright attribution and regulatory responsibility. Historical data shows that 93% of blockchain gaming projects have stopped operating, and technological innovation is not the same as commercial success.