"Build for where the industry is going, not for where it is." This mantra has fueled disruptive innovations for decades — Microsoft capitalized on microprocessors, Salesforce leveraged the cloud and Uber thrived in the mobile revolution.

The same principle applies to AI — generative models are evolving so rapidly that building today's capabilities risks obsolescence. Historically, Web3 has played little role in AI evolution. But can it adapt to the latest trends reshaping the industry?

2024 was a pivotal year for generative AI, with groundbreaking research and engineering advancements. It was also the year that the Web3-AI narrative transitioned from speculative hype to glimpses of real utility. While the first wave of AI revolved around mega-models, long training cycles, vast compute clusters and deep enterprise pockets — making them largely inaccessible to Web3 — newer trends in 2024 are opening doors for meaningful Web3 integration.

On the Web3-AI front, 2024 was dominated by speculative projects such as meme-driven agentic platforms that reflected bullish market sentiment but offered little real-world utility. As that hype fades, a window of opportunity is emerging to refocus on tangible use cases. The generative AI landscape of 2025 will be vastly different, with transformative shifts in research and technology. Many of these changes could catalyze Web3 adoption, but only if the industry builds for the future.

Let's examine five key trends shaping AI and the potential they present for Web3.

1. The reasoning race

Reasoning has become the next frontier for large language models (LLMs). Recent models like GPT-01, DeepSeek R1, and Gemini Flash place reasoning capabilities at the core of their advancements. Functionally, reasoning allows AI to break down complex inference tasks into structured, multi-step processes, often leveraging Chain of Thought (CoT) techniques. Just as instruction-following became a standard for LLMs, reasoning will soon be a baseline capability for all major models.

The Web3-AI opportunity

Reasoning involves intricate workflows that require traceability and transparency — an area where Web3 shines. Imagine an AI-generated article where every reasoning step is verifiable on-chain, providing an immutable record of its logical sequence. In a world dominated by generative AI, this level of provenance could become a fundamental need. Web3 can provide a decentralized, trustless layer to verify AI reasoning pathways, bridging a critical gap in today's AI ecosystem.