AI agents will trade more on eToro than people, predicts CEO Yoni Assia
The idea that AI agents will trade more than humans on eToro might sound futuristic, but it is already front and center for the platform’s CEO, Yoni Assia. In a conversation with Scott Melker on The Daily Wolf show, aired by Yahoo Finance, he envisions a scenario where most trading activity will be handled by artificial intelligence agents trained to operate on behalf of investors.
In the original content, the spotlight is exactly on this vision: AI agents, configured and trained to trade, are likely to take over a large share of the flow of trades on eToro over time. The conversation is also framed within the crypto universe, since the interview is part of a daily crypto-focused show aired at noon, and is tied to Yahoo Finance’s new crypto hub.
From there, it is possible to dig deeper into what this outlook actually means in practice, how it might change the role of the investor on the platform, and what the challenges and opportunities are in this transition where humans, algorithms, and platforms start to share center stage.
AI agents trained to trade: what is at stake
When Yoni Assia says that AI agents will trade more than humans on eToro, he is not suggesting that people will vanish from the process, but that their role will change. Instead of manually clicking every buy and sell order, investors will configure, train, and fine-tune agents that trade on their behalf.
These agents use real-time market data, price history, volumes, and other indicators to make decisions autonomously. They can apply strategies defined by the user or based on pre-trained models, always within pre-established rules and limits.
The vision is of a future in which:
- The human investor defines goals, risk limits, and main criteria.
- The AI agent analyzes the market, spots opportunities, and executes orders.
- The platform, like eToro, provides the infrastructure, data, and controls so that everything runs smoothly and transparently.
This model is especially aligned with the crypto world, which is the context of the interview. The market runs 24/7, with high volatility and fast moves. Staring at the screen all the time is impossible for any normal person; for an AI agent, though, this is the ideal environment.
Why AI agents are likely to surpass human trading volume
The projection that AI agents will trade more than humans on eToro is not a random guess. It is based on some pretty clear behavioral and technological factors.
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Scale, speed, and no fatigue
A human trader:
- Needs to sleep, rest, work, and handle other tasks.
- Gets tired, stressed, and makes decisions under emotional pressure.
- Can only follow a limited number of assets at the same time.
A well-designed AI agent:
- Runs 24 hours a day, non-stop.
- Processes multiple assets, pairs, and markets in parallel.
- Follows defined rules, with no fear, greed, or impulsiveness.
Putting this together, the core point becomes clear: in pure trade volume, a set of automated agents tends to pull way ahead of manual traders. Not because they are magical, but because they can execute far more orders in less time, in more markets, with less friction.
Low marginal cost and multiplying strategies
Once an AI agent is configured, validated, and set to run, the marginal cost of keeping that agent active is usually low compared to the equivalent human effort. This makes it possible to:
- Have a single investor running several agents at the same time.
- Have each agent focused on a different approach: one more conservative, another more aggressive, another dedicated to a specific pair, and so on.
- Test, tweak, and replace strategies quickly, without having to redo everything manually from scratch.
Over time, the combined activity of these agents tends to generate a much larger trading volume than what humans can do by hand alone.
Yoni Assia’s prediction is clear: in the not-too-distant future, most trades on eToro will be opened, managed, and closed by AI agents, with humans shifting into the role of supervisors, configurators, and strategy reviewers.
eToro’s role in this new trading environment
The interview with Scott Melker also highlights eToro’s place in this scenario. It is not just about enabling automation, but about embedding the logic of AI agents naturally into the platform experience.
This role involves a few key points:
- Providing reliable infrastructure to handle high volumes of automated orders.
- Offering consistent market data, with accessible history for strategy backtesting.
- Building user-friendly interfaces to configure, monitor, and adjust agents.
- Adding safety layers so that simple mistakes do not turn into massive losses.
Since the interview is part of a crypto-focused show and also references Yahoo Finance’s new crypto news hub, it is clear that the goal is to connect this vision to the current landscape: digital markets, high liquidity, real-time information, and a community that is used to trying new tools.
From copying traders to copying agents
One of eToro’s historic differentiators is social trading – the ability to automatically copy other users’ trades. In the context of AI agents, this logic can evolve to something like:
- Copying automated strategies instead of just people.
- Following AI-managed portfolios with clear rules for risk and allocation.
- Combining agents created by different developers, building a mix of algorithms in a single account.
This would make human-machine interaction even more social: instead of only following a popular trader, users could follow a successful agent, understand its basic trading logic (as far as possible), and adjust it to match their own profile.
How trader behavior changes in practice
The original content makes it clear that we are talking about agents trained to trade on behalf of the investor. That directly affects how people relate to the act of trading.
The classic image of the trader spending all day in front of charts tends to share space with a different profile:
- Someone who spends time defining rules, limits, and assumptions.
- Who tracks performance through reports, instead of pressing the button every trade.
- Who periodically reviews the strategy, instead of trying to nail the top and bottom in real time.
This does not mean less responsibility, quite the opposite. Responsibility shifts from deciding the exact timing of each click to designing the system that will click for you.
A matter of trust and psychology
Many people feel they are in control when making every decision manually, even though in reality that control is limited by emotion, fatigue, and lack of data. When they hand execution over to an AI agent, users need to:
- Trust the process they defined.
- Accept that not every decision will be perfect.
- See results as reflections of rules and probabilities, not of a single brilliant click.
This mindset shift is an important part of the transition. By placing the topic inside a daily crypto show and tying it to a specialized news hub, the interview also suggests that continuous education and information are key so users understand what they are using and how it affects their money.
Market impact and price dynamics
Over time, a market dominated by AI agents tends to behave differently from one dominated mainly by humans.
Some possible effects include:
- Faster exploitation of micro opportunities, since agents can react in milliseconds.
- Shorter arbitrage windows, because algorithms quickly detect and correct pricing distortions.
- Faster disappearance of simple patterns, since any predictable pattern tends to be captured by many agents at once.
For traders who continue to operate only manually, this may mean a more competitive environment, where isolated gut feeling and basic visual chart analysis offer less of an edge. For those who learn to use AI agents as allies, the game levels up, opening room for interesting combinations between human intuition and automated execution.
Risks and limitations in this transition
Yoni Assia’s outlook is optimistic, but not naive. A market crowded with automated agents also carries important risks:
- Error amplification: a poor configuration in an agent that runs 24/7 can cause fast losses.
- Algorithmic herd behavior: if many agents follow similar signals, they can push prices in the same direction at the same time.
- Understanding gaps: more complex models can become black boxes for average users, who may not grasp why the agent made a certain decision.
That is why platforms like eToro need to provide:
- Loss and exposure limit tools.
- Clear, visually accessible performance reports.
- Options for quick pause and shutdown in extreme scenarios.
Where this conversation fits in the crypto and news ecosystem
Yoni Assia’s comments do not appear in a vacuum. They come in a daily crypto show, The Daily Wolf with Scott Melker, aired by Yahoo Finance every day at noon, and are mentioned in a context where Yahoo itself is highlighting its new crypto news hub.
This reinforces two points:
- The topic of AI agents in trading is already on the radar of major news and investment platforms.
- The debate is not just technical, it is also educational: it is about helping the public understand what is coming in terms of automation and artificial intelligence in the markets.
In this context, eToro stands out as one of the key platforms where this transition can be closely observed, precisely because it combines an active community, social trading, and strong exposure to the crypto space.
The near future: humans as designers, AI agents as executors
Summing up the vision laid out by Yoni Assia and framed in the conversation with Scott Melker, the picture that emerges is a future where:
- Most trade orders on eToro will be triggered by AI agents.
- Humans will act as strategy architects, defining goals, limits, and rules.
- Platforms will be responsible for providing tools, data, and safety so that this relationship works well.
- Media coverage, such as that provided by Yahoo Finance and its crypto hub, helps bring visibility and understanding for those just entering this space.
In the end, the statement that AI agents will trade more than humans on eToro is not a verdict against the human trader, but an indication of a role shift. Instead of competing with algorithms click by click, investors move to a different level: designing systems, reading context, and intelligently supervising agents that, more and more, will handle the heavy lifting in real time.
