AI Trading: The Best Uses of AI Software, And The Limits

AI is quickly becoming part of the trader’s toolkit. Not because it can magically predict every market move, but because it can help traders work faster, screen more markets, test ideas, organise risk, and make better use of the tools they already have.

The key is knowing where AI is genuinely useful, and where it becomes dangerous. For most retail traders, the best use of AI is not to hand over the trading account and hope for the best. It is to use AI as a support tool for charts, screening markets for opportunities, building out your strategy, backtesting, and making sure your risk management is tight enough. So you use AI in trading to help you save time, and find opportunities, but it should not replace your thinking. The best AI trading platforms typically provide an assistant to work with you, or automate your own logic, not replace you.

Best Use Cases For AI in Trading

Chart Assistance

One of the most interesting tools in this space is TradingView Remix, also known as the TradingView AI Chart Copilot. It works as a browser extension and sits alongside your TradingView chart, bringing AI directly into the place you most likely already do your analysis.

So instead of switching between a chart, a chatbot, a news site and a screener, you can ask questions directly beside the chart you are looking at, and place a trade right there if you have an integrated broker. You might ask the AI what you might be analysing yourself initially such as:

“What are the key support and resistance levels on this chart?”

“Is this a possible breakout setup?”

“What indicators are confirming or contradicting the move?”

“Set alerts around the main levels you just identified.”

“Screen for stocks showing breakout behaviour.”

That is where a tool like TradingView Remix can be genuinely useful. It can save time, highlight things you may have missed, and help you move from raw chart-watching to a more structured trading process, but it still needs direction and is not a fully automated trading platform. With this type of use case, you need to ask good questions, know what sort of setup you are looking for, and be able to judge whether the answer makes sense.

So whilst AI can identify patterns on your charts, it can’t take away the uncertainty of what happens next.

AI as a Market Screener

Another strong use case is screening the market. Many of us have spent countless hours time flicking through charts, news, or forums, looking for something interesting. AI can reduce that workload by helping you search for specific conditions using data that you know is coming from the chart itself. As a data parsing machine, there is none better.

So you can ask TradingView Remix to search through the top ASX 200 shares, and give you some a few names that are approaching breakouts, or breakdowns, showing unusual volume, or making moving average crosses such as golden cross, or a death cross. You could also have it search for breakout attempts that have failed, potentially looking for reversals.

The key is with using AI as a screener is to to be specific about what you are looking for. If you simply ask it to “find good trades”, you are being too vague. A better suggestion would be to “screen the ASX 200 for shares breaking above the 200 day SMA, on above-average volume”, or “check for shares where the 50 day SMA is less than 1% below the 200 day SMA, and price is above the 30 day SMA”.

So if you know what you are looking for as a ‘good’ setup, then the AI works well with you to find more of what works for you.

AI as a Risk Assistant

One of the most important parts of trading that get’s overlooked by many is risk management. AI can cut through a lot of the work and calculation to help you with position sizing, and setting the right stop losses and take profit levels, but there is another interesting use case. What is often overlooked, is to use the AI to challenge trades you already have in mind.

You could ask the before entering a position, for the “opposing case”, or for “potential fail points” in the setup. You can check whether the risk to reward is attractive, or how many losses in a row a particular strategy might experience before a profitable one. These kind of insights could be very useful in just making you fully question your trading idea before you pull the trigger on it.

We see many traders using technology to find more trades, but the bigger improvement may come from filtering out the bad ones. A good AI tool, like a good trader should also no to weak setups.

How To Use AI Trading Tools

Fully automated AI trading sounds attractive, with the machine finding the trade, entering them, managing them and exiting. But the moment you hand over full control, you need to understand exactly what the system is doing.

Do you know exactly what trading strategy it is using, which market conditions it works best in, or how many losses in a row are normal? What about how it would behave during spikes in volatility, of if a data feed fails, or your broker connection breaks?

The dangers here is not just that an AI bot may lose money, that can happen. The danger is that you may not understand why it is losing money until the damage is already done. That is why a human-in-the-loop model is more sensible for most traders. Let AI research, screen, explain, draft and monitor, but keep the final decision with you.

This is similar to the old full-service stockbroker model. A broker might give you ideas, explain the reasoning and talk through the risks, but the final decision always sat with you. AI can play a similar role, but is faster, cheaper and available on demand.

A sensible AI trading workflow might look like more this:

• Use AI to scan for potential opportunities.
• Ask it to explain the setup and identify key levels.
• Check whether the idea fits your strategy rules.
• Have it backtest or review similar historical setups.
• Ask the AI to challenge the trade idea.
• Decide for yourself whether the trade is worth taking.
• Use AI to create you a journal, and add the outcome for review.

That is a much healthier process than simply asking AI to “make me money”.

Why TradingView Integration Matters

The advantage of a TradingView-based AI tool is that it lives where the trading decision is being formed. Claude, ChatGPT, Codex and other large AI models can all help with trading research, strategy ideas and code, and they can even be linked to certain brokers. But unless they are connected to your chart, data, broker or backtesting environment, they are operating one layer removed from the actual trading workflow.

That is why TradingView Remix can feel more practical for active traders. It can interact with the chart, help manage alerts, read the current setup and support your analysis in real time. And if you use a broker that supports TradingView trading, such as Pepperstone, or Blackbull; analysis, AI suggestions, alerts and the trade itself can all be that much closer together.

That does not mean the AI is your trading guru, but more of an assistant sitting beside the chart doing a lot of the leg work. You are still the trader.

Where Claude, ChatGPT and Codex Fit In

General-purpose AI tools are still extremely useful, but they are more suited to different parts of the process.

Claude, ChatGPT and Codex can help you turn a trading idea into a set of rules that could be applied to another automated trading system like an EA on MetaTrader. They can also review strategy logic, create a Pine Script, generate Python backtests, summarise trade journals, and help you think through risk.

But whilst AI has moved on leaps and bounds in recent months, AI-generated code can look right (to the uninitiated) while still being wrong. A strategy can backtest well because of bad assumptions, missing trading costs, unrealistic fills, repainting indicators, or overfitting to historical data.

What To Avoid

Traders should be very cautious with any platform claiming that its AI can guarantee profits, trade with no losses, or generate passive income with no skill required. Those claims are red flags.

Markets are uncertain, and losses are a part of trading. Any serious trading strategy has drawdowns, losing streaks and periods where it stops working. The trick to longevity is being able to size your positions properly, keep you risk management in tact, and keep a clear head.

If an AI tool cannot explain its logic, risk controls and expected losing periods, you should be careful, and the more control you give a system, the more you need to understand how it behaves under stress.

In Short

AI tools can you a lot as a trader. They can help you save time, scan markets, explain charts, write code, test ideas, organise alerts, review risk and even improve discipline. But AI should be treated as a trading assistant, not a money making machine. If it was that easy, every one would already be doing it.

You should still have a plan, proper risk management, an understanding the setup, and actually make the final call.

Used properly, AI can sharpen your process and provide more opportunities. But if it’s used blindly, it can simply help you make mistakes, and losses that much faster.