Mark Govoni, CEO, Liquidnet
AI is everywhere. From voice assistants in the kitchen, to our social media feeds and predictive healthcare, it’s reshaping how we live and how we work. Trading desks are no exception. The integration of AI and GenAI into trading workflows has revolutionised incumbent processes, transforming the way we handle and process data in particular. But as machines take on more and more routine tasks, we have to ask ourselves the question: where does the agency broker fit in this evolving system?
The answer lies in partnership, not replacement.
AI’s strength lies in its ability to process vast amounts of data in the blink of an eye and with astonishing precision. Modern trading generates mountains and mountains of information – price movements, global news, spreads, etc. – and AI can synthesise these inputs instantly. This enables algorithms to identify patterns and predict market shifts in moments.
The proliferation of tools powered by AI showcases just how versatile it is and gives the industry a glimpse of the technology’s potential. Generative AI tools that automate complex workflows and analyse unstructured data can and will enhance trading efficiency. On the risk side, we’re starting to see AI further integrated to offer real-time insights to help managers mitigate potential losses.
But while AI handles the heavy lifting in terms of data and information processing, it does not operate in a vacuum. Trading decisions require context, strategy, and an understanding of nuanced client expectations – areas where machines still fall short.
The broker perspective
Humans and machines are not running the same race, nor should they. The unique strengths of each must be acknowledged and leveraged to create a truly effective trading ecosystem. AI excels in data processing, pattern recognition, and operational efficiency. However, it lacks the nuanced understanding, emotional intelligence, and strategic insight that human brokers bring to the table.
In the world of trading, client relationships remain a cornerstone of success. These relationships are built on trust, communication, and a deep understanding of client needs—factors that no algorithm can replicate. Clients often rely on brokers not just to execute trades. Whether it’s an illiquid market, a high-stakes block trade, or a sudden market event, the broker’s ability to assess the situation, provide insight, and make decisions under pressure is irreplaceable.
In this symbiotic relationship, AI empowers brokers to devote more time to what they do best: providing thoughtful, bespoke solutions. As trading grows more complex, the broker’s role is evolving into one that blends the precision of data-driven insights with the art of human judgment.
The partnership
AI should not be seen as a competitor but as a collaborator. The relationship between humans and AI is not one of replacement but of symbiosis, where the strengths of both are combined to achieve greater results than either could alone.
Think about a trading desk looking to identify patterns in market data. AI might flag an opportunity but it’s the broker who evaluates the context, applies a layer of human intuition, and determines the best course of action.
A successful partnership with AI requires more than passive acceptance. This symbiotic relationship, if embraced, will redefine efficiency and effectiveness on the trading floor. Brokers and traders must actively engage with this technology, learning how to interpret its outputs, identify its limitations, and optimise its integration into their workflows. Upskilling to work alongside AI is not a choice but a necessity for the next generation of trading professionals.
Ultimately, the future of trading will be defined by this interdependence. Those who thrive will be the brokers and institutions that adapt to this new dynamic, leveraging AI’s strengths while honing their own unique skills. AI may be the engine driving the trading desk forward, but it’s the human brokers in the driver’s seat, steering toward opportunities and navigating challenges with a balance of data-driven precision and strategic intuition.
This evolution is not a challenge – it’s an opportunity. It’s a paradigm shift in how we think about trading.