AI as Your Trading Mentor

By William Wang, Assistant Vice President, APAC Marketing, Ultima Markets

Picture this: you’re a novice trader. You’ve just entered the market with no real experience. You understand the concept of trading—but beyond that, you don’t really know what to do next. Now imagine having a personal mentor beside you. This mentor doesn’t just trade on their own, they are able to teach you as they go along. They are able to explain what a breakout is and many other concepts, show you how to manage your risk on each trade, and train you as you go by guiding your decisions and correcting your missteps in real time. Now imagine that mentor is able to follow you wherever you go. We call that mentor: Artificial Intelligence or AI.

Generative AI — powered by large language models and real-time analytics — is already helping traders interpret market behaviour. One example is BloombergGPT1, a finance-specific LLM trained on proprietary financial data and documents to serve professional traders and analysts.

No matter what question you might have on your mind, AI can take on the role of a mentor to answer, guide, and teach, at your own pace. For traders who’ve long been navigating complexity alone, it’s a dream come true.

Why? Because the real issue - both in the past and in the present - wasn’t a lack of tools, it was a lack of structure. Most traders fail not from poor execution, but from their inadequate education. Institutional traders benefit from peer review, experienced analysts, and internal checks. Retail traders? They rely on forums, hearsay, and broker-published articles that are rarely objective. It’s certainly not a level playing field and historical results have proved it.

This is where AI steps in.

AI can learn from millions of data points—far more than any human can. It’s consistent, available 24/7, and never emotional. It doesn’t just automate trades; it explains them. It grows with you, adapting as your understanding evolves.

The larger institutions are already paying attention.

A recent McKinsey2 report highlights how finance teams are already piloting generative AI to accelerate reporting, surface critical data, and assist decision-making in real time — improving speed, clarity, and collaboration across the finance function

Research from the CFA Institute3 indicated that investment professionals are steadily integrating AI and big data tools into their workflows to automate tasks and enhance strategic decision-making across research, compliance, and risk analysis.

PwC4 estimates that AI could contribute up to $15.7 trillion to the global economy by 2030, with financial services among the sectors expected to benefit most from productivity gains and personalised financial products.

The timing couldn’t be more perfect.

Millennials and Gen Z are growing and maturing in the age of AI. According to Accenture’s 2025 Global Banking Consumer Study5, 88% of Gen Z and Millennials are eager to expand their financial knowledge — more than any previous generation. They want financial platforms to offer tools that are not only smart, but intuitive, transparent, and genuinely helpful in improving their financial well.

They expect intelligent support systems embedded in everything from their search engines to customer service chats. Now they’re looking for that same intelligence in their financial platforms. With AI, we’re putting high-quality, real-time guidance into the hands of any trader, anywhere. But here’s the nuance. AI doesn’t just deliver answers because, let’s be honest, the best mentors never do. They sharpen your instincts. They help you notice patterns. They reduce emotional overreactions and guide you to act based on probability and not panic. AI, when deployed properly, doesn’t replace intuition, it shapes it.

That said, transparency and guardrails are absolutely critical. We need to acknowledge AI’s inherent risks: opaque decision-making, over-reliance, and bias in algorithms. The future of AI in finance lies in explainable systems. Those are the ones that earn your trust by showing you why they make the choices they do. Some platforms are already delivering this type of intelligent mentorship. Ultima Markets, for example, has integrated AI-driven tools into its MT5 platform, ranging from automated risk controls to data-backed trade analysis. It is one of several emerging examples of how brokers can combine education and accountability through AI. This is why we believe the next generation of trading mentorship won’t be human or machine. It will be both. Our traders will no longer rely solely on our static educational content, webinars, or Telegram chats. They will learn from both their peers and from AI: intuitively, interactively, and intelligently. AI will teach them as they trade, accelerating their development from novice to strategist. And in this new reality, mentorship will no longer be a privilege, it will be a given.

William Wang, Assistant Vice President, APAC Marketing, Ultima Markets

References

1.Bloomberg. (2023). BloombergGPT: A large language model built for finance.
https://www.bloomberg.com/company/press/bloomberg-announces-bloomberggpt-a-new-large-language-model-built-for-finance/
2.McKinsey & Company. (2024). Generative AI in finance: Finding the way to faster, deeper insights
https://www.mckinsey.com/capabilities/operations/our-insights/generative-ai-in-finance-finding-the-way-to-faster-deeper-insights#/
3.CFA Institute. (2025). AI in Investment Management: Enhancing decision-making through technology.
https://rpc.cfainstitute.org/research/reports/2025/creating-value-from-big-data-in-the-investment-management-process
4.PwC. (2017). Sizing the prize
https://www.pwc.com/gx/en/issues/artificial-intelligence/publications/artificial-intelligence-study.html
5.Accenture. (2025). Banking Consumer Study 2025 - Where is the love?
https://www.accenture.com/content/dam/accenture/final/industry/banking/document/Accenture-Global-Banking-Consumer-Study-2025-Report.pdf