Why Agentic AI Could Be the Turning Point for Mass Adoption of Crypto.

6 min readMay 14, 2025

# AgenticAI #AI #Crypto

In the past few articles, we spent a significant amount of content analyzing the trend reversal in the current crypto market and the general uptrend across the board. All analyses were based on objectively existing market data and grounded in respect for objective facts. However, since the market started rising, one key metric has been consistently overlooked — the number of new users entering the ecosystem.

Simply put, although the current market uptrend is clear, with major coins like BTC and ETH surging, overall market traffic (especially retail users) has not substantially increased. Whether it’s the number of active on-chain addresses or the real user growth on Web3 platforms, these metrics have merely started approaching pre-crash levels, without any qualitative breakthroughs. In other words, this round of “rally” feels more like a return of old users rather than an expansion of new ones.

In fact, this is also one of the major bottlenecks facing the current crypto market: traditional users simply cannot accept the high volatility that is typical in crypto. For example, even in the U.S. — a country considered a “pioneer nation” in the crypto space — 63% of Americans still do not trust the security and reliability of cryptocurrencies, so it’s no surprise that mass adoption remains a distant goal.

Against this backdrop, what we need is a true variable that can bring in new users, and Agentic AI just might be that variable.

From Agent to Agentic: Ushering in a New Era of AI

In the AI space, AI Agents are widely known, but Agentic AI may be a new term for many. The earliest mention of the concept dates back to the 2024 Snowflake Summit, where AI pioneer Andrew Ng delivered a keynote titled “How AI Agentic workflows could drive more AI progress than even the next generation of foundation models”. His talk unveiled the mystery of Agentic AI and pointed out that it could be an AI development direction even more promising than the next generation of foundation models.

What truly brought Agentic AI into the public spotlight was NVIDIA CEO Jensen Huang’s keynote at the GTC 2025 held in San Jose, California, on March 18, 2025. In his speech, Huang described four waves of artificial intelligence, putting Agentic AI under the spotlight once again:

Perception AI: Launched roughly a decade ago, focusing on speech recognition and other simple tasks.
Generative AI: The focus of the past five years, involving text and image creation based on pattern prediction.
Agentic AI: The current phase, where AI interacts digitally and autonomously executes tasks, characterized by reasoning models.
Physical AI: The future of AI, powering humanoid robots and real-world applications.

Unlike traditional Agents that are locked into fixed workflows, Agentic AI is like a conductor who has broken free from restraints, free to think and plan as it pleases. Simply put, Agentic AI is an artificial intelligence agent with autonomous decision-making and execution capabilities. It no longer passively responds to user commands but can actively perceive context, set goals, plan tasks, and execute complex operations by calling tools or accessing external systems.

AI Agent VS Agentic AI

As mentioned, unlike fixed-path Agents, Agentic AI is like a conductor free from constraints, able to think and plan freely. This marks a leap from “tool” to “intelligent agent.”

A traditional AI Agent is like the voice assistant on your phone — Siri, Alexa, etc. — that follows a predefined route to complete tasks. Say, “Check the weather,” and it fetches data from a weather API and returns the result. It has no independent judgment and won’t proactively solve complex problems.

Agentic AI is a completely different story. It behaves like an agent with a sense of purpose, capable of planning how to accomplish tasks on its own. For example, it can automatically detect which assets are in your wallet, how much gas you have, which DeFi protocol offers the highest yield, then help you choose the optimal strategy, allocate funds, execute the trade, and even monitor performance afterwards.

To use a metaphor:

A traditional AI Agent is like a talented writer stuck within a fixed outline.
Agentic AI is like a writer who has broken free from the outline and can fully unleash their talent.

Additionally, Agentic AI typically possesses three core abilities:

Perception: Understand what you want to do and your current status;
Reasoning & Planning: Think about how to achieve your goal and lay out a plan;
Tool Use: Proactively call various Web3 tools, APIs, wallets, and protocols to complete tasks.

So, this is no longer just a “smarter AI”, but a “more proactive AI”, which will have a fundamentally different impact in the crypto space.

Why Agentic AI Could Be the Tipping Point for Crypto Adoption

Conceptually speaking, in the crypto space, Agentic AI has the potential to significantly lower the user operation threshold. It can automatically complete on-chain interactions, manage wallets, participate in DeFi or governance — essentially acting as a “smart assistant” and “execution engine” that drives Web3 adoption.

We all know that the crypto market has a massive barrier to entry: it’s just too difficult to use.

For the average person, setting up a wallet, memorizing seed phrases, switching chains, authorizing transactions — these steps are already overwhelming. Let alone more advanced tasks like participating in DeFi, minting NFTs, using cross-chain bridges, or staking nodes. Many Web3 projects, despite their advanced tech and design, suffer from the same core issue: users don’t know how to use them, are afraid to try, or simply don’t have the time to learn.

Agentic AI solves precisely this pain point.

1. Reducing the Learning Curve

It can guide users step by step through complex operations, even automatically deciding what should be done. For example, based on your past on-chain behavior, it can identify NFTs you might be interested in, set up purchase alerts, or even help you mint them directly.

2. Improving Execution Efficiency

It can handle everything from cross-chain bridging to wallet authorization to transaction submission — all with one click, sparing users from tedious confirmations. For instance, if you say “I want to earn some interest on stablecoins,” it can automatically scan pools across platforms like Curve, Aave, Uniswap, and select the best yield option, transferring, depositing, and authorizing on your behalf in minutes.

3. Easing Security Anxiety

It can perform background risk checks, such as verifying if the contract you’re interacting with is safe, whether the project is a potential rug, or if gas fees are too high — helping users avoid “blind participation” and enhancing trust in the crypto world.

Simply put, Agentic AI is the Web3 tour guide for retail users, the transaction nanny for beginners, and the user acquisition engine for project teams.

With such a “smart bot” helping to operate, judge, and guide, the need to understand code, wallets, and market trends can be drastically reduced. It’s easy to envision a future where the gateway to Web3 is not an app, not a wallet, but a conversational, goal-oriented Agentic AI.

This is what true mass adoption looks like.

Final Thoughts

Looking back at the current market, it’s actually quite clear: the market is rising, but users haven’t arrived.

Old users are back, projects are heating up again, and trading enthusiasm is returning. But those retail investors who left after the 2021 bull market haven’t returned, not to mention the general public who’s never entered the crypto space.

Why? Because the barriers remain. Users still don’t understand, aren’t confident, and don’t know how to use the tools.

And the emergence of Agentic AI just happens to solve this problem. It doesn’t require you to learn a bunch of new concepts, doesn’t require coding skills, and doesn’t require understanding complex protocols. All it needs is for you to say, “Here’s what I want to do” — and it takes care of the rest.

Of course, as Jensen Huang said, Agentic AI is what we are currently researching, developing, maturing, and deploying, and this will require time and progress.