The Future of AI in Investment
Recorded live at the Buy and Build: Trading Tech Briefing 2025 in London, this episode of FinTech Focus TV, hosted by Toby, brings forward-thinking insights from David Marcos, Founder and Managing Partner at Quantoro Technologies. The conversation captures a pivotal moment in the evolution of investment technology, exploring how artificial intelligence is transforming trading, portfolio management, and the very nature of investment decision-making.
In this session, David delves into how AI agents are changing the rules of investing, not by replacing human expertise, but by enhancing it. With deep roots in both the buy-side and sell-side of finance, his perspective brings together the technological, behavioural, and strategic aspects of a financial ecosystem in flux.
Breaking Down Barriers in FinTech Investment
The discussion opens with the idea that the investment process is broken, a statement that immediately draws attention. For David, this conclusion came from a simple yet telling observation: many of his peers in the financial and quantitative world found personal investing unnecessarily complex. Despite being highly skilled, data-driven professionals, few of them actively invested their own money, and those who did found the experience cumbersome, risky, and inefficient.
This disconnect led him to question why the world of investing, which thrives on innovation and analytics, remains so fragmented and difficult for even the most knowledgeable individuals. His answer came through technology. Quantoro Technologies set out to make investing more linear, accessible, and intelligent, combining the power of algorithms with human intuition to reduce friction in the investment journey.
David explains that his team identified three critical needs for investors: generating new investment ideas, building and testing strategies, and finally executing those strategies in a cohesive and intuitive way. The goal was to bring these functions together into a single, streamlined environment where users could move from inspiration to action without the traditional layers of complexity.
AI Agents: The Future of FinTech Investment Tools
The conversation naturally moves towards artificial intelligence, and more specifically, AI agents, which David believes represent the next great leap forward in financial technology.
In traditional investment processes, even sophisticated investors must jump between multiple systems for research, analysis, backtesting, and execution. AI agents offer a more unified, conversational experience: a way to communicate directly with an intelligent system capable of designing, testing, and managing entire investment strategies.
At Quantoro Technologies, AI agents are not merely performing data analysis; they are building strategies, backtesting performance, and managing portfolios autonomously within a single platform. David draws a comparison with recommendation systems used by streaming services like Netflix. Just as Netflix learns individual preferences to suggest films, AI algorithms can learn an investor’s risk appetite and style to recommend relevant assets or stocks.
For the first time, quantitative investment is being made accessible to everyone, not just hedge funds or institutions with deep data-science expertise.
Reinforcement Learning and Trading Innovation
With extensive experience on both sides of the financial market, David has seen first-hand the inefficiencies in execution and timing that traders face. Even seasoned professionals struggle with delays in decision-making and reaction time as markets move faster than humans can process.
To solve this, Quantoro Technologies integrates reinforcement learning, a branch of AI that learns through trial, error, and feedback, into trading and portfolio construction. David describes reinforcement learning as a natural fit for financial markets, where an agent must continuously observe its environment (the market), make decisions (trades), and learn from outcomes (returns or losses).
This technology allows systems to adapt dynamically to market behaviour. Instead of being programmed with static rules, the AI learns from market data and optimises its actions in real time. Quantoro Technologies applies this approach to execution trading, market making, and alpha capture, using AI to discover and refine profitable strategies.
The result is an intelligent framework that mirrors how a human trader might act, but with far greater speed, precision, and consistency.
Balancing Human Intuition and Artificial Intelligence
While AI brings immense computational power, David makes a key point: AI is not a replacement for human intelligence. Instead, it should be seen as a complement.
AI agents excel in processing massive amounts of data, identifying correlations, and executing tasks that would take humans hours or days. However, they lack the intuition, empathy, and emotional understanding that underpin human decision-making. Trading often involves judgement, perception, and awareness, elements that machines are still far from mastering.
David refers to the ideas of physicist and mathematician Sir Roger Penrose, who argued that AI cannot become truly conscious because there are truths humans intuitively know to be real but cannot mathematically prove. This insight highlights the boundaries of AI in its current form.
For David, this balance between automation and human oversight is not a limitation, it is an opportunity. By using AI to handle computation and pattern recognition, and allowing human professionals to focus on intuition-driven strategy, the industry can reach a new level of performance.
A Vision for the Future of AI in FinTech
Looking ahead, David envisions a future where AI agents become trusted partners in daily financial decision-making. He imagines investors interacting with their AI systems as they would with a colleague or advisor, asking how their portfolio is performing, which areas could be rebalanced, or what market trends are emerging.
This conversational interface would allow users to request complex analyses in plain language. For instance, an investor could ask for assets that achieved a Sharpe ratio above a certain threshold last year, filtered by specific CEO nationalities, and have the AI instantly design and backtest a trend-following strategy.
The beauty of this vision lies in accessibility. What once required an entire team of analysts and developers could be achieved in seconds by speaking to an AI. Quantoro Technologies’ mission is to make this level of sophistication available to all investors, not just institutional giants.
For the FinTech sector, this represents a shift towards personalised, intelligent automation that empowers individuals while democratising the investment landscape.
Simplifying Complex Investment Workflows
In its current form, the investment ecosystem is fragmented. Research, optimisation, trading, and portfolio management often occur on separate platforms, requiring manual coordination and technical expertise. This inefficiency creates barriers not just for individual investors, but also for firms trying to innovate quickly.
Through reinforcement learning and AI integration, Quantoro Technologies is developing tools to linearise the entire investment process. The company’s vision is to create a single system capable of idea generation, backtesting, execution, and performance tracking, all within a unified environment.
The potential impact is transformative. Portfolio managers could seamlessly test new models without switching tools. Retail investors could explore complex strategies without coding knowledge. Data scientists could focus on creativity and insight rather than infrastructure.
By bridging these gaps, the company is advancing what many see as the next logical step in FinTech evolution: the convergence of machine learning, human expertise, and accessibility.
The Role of AI in Financial Trading Talent and Recruitment
For FinTech professionals and recruiters alike, David’s insights hold wider implications. As AI reshapes the financial landscape, demand for specialised technology talent continues to rise. The integration of deep learning, reinforcement learning, and AI agent technology means that traders, data scientists, and engineers must increasingly collaborate in hybrid roles.
From a recruitment standpoint, this evolution highlights the growing importance of cross-disciplinary FinTech skills, combining quantitative finance knowledge with machine learning and data engineering expertise. As firms like Quantoro Technologies push innovation forward, the industry will need professionals capable of building, deploying, and managing AI systems that interact intelligently with both markets and people.
This ongoing transformation also underscores why FinTech recruitment plays a central role in the ecosystem. The success of companies exploring AI-driven trading solutions depends on sourcing exceptional talent that understands not just the algorithms, but the financial purpose behind them.
Why AI Will Not Replace Traders, Yet
A recurring theme throughout the conversation is reassurance: despite the pace of automation, AI is not about to replace human traders entirely. Instead, it offers a toolkit to enhance performance and simplify decision-making.
David highlights two reasons for optimism. Firstly, humans maintain a unique advantage in tasks requiring awareness, emotional intelligence, and creative problem-solving, qualities that remain out of reach for current AI systems. Secondly, reinforcement learning and similar techniques are designed to work best when combined with human oversight.
While AI agents can backtest thousands of strategies and detect patterns invisible to human eyes, they still depend on human direction and ethical frameworks. This partnership between human insight and machine intelligence could define the next generation of financial trading, one where intuition meets automation in perfect balance.
The Year of the AI Agent in FinTech
As Toby notes during the conversation, 2025 has often been referred to as “the year of the agent.” At the time of recording, the industry had already seen dramatic advances in the development of AI agents, intelligent systems capable of reasoning, decision-making, and independent learning.
For David, this prediction is already coming true. The progress achieved in less than a year has surpassed expectations, and the technology continues to accelerate. As these agents become more capable, they promise to revolutionise not only investment management but also how financial institutions approach product design, risk management, and customer engagement.
FinTech firms are now racing to implement these innovations in ways that enhance efficiency without sacrificing trust or transparency. The message from the Buy and Build 2025 conference is clear: those who can adapt fastest to AI-driven systems will lead the next chapter of trading technology.
Collaboration and Optimism for the FinTech Industry
Throughout the episode, David’s tone remains one of optimism. He acknowledges that disruption often brings uncertainty, yet he sees the rise of AI as an opportunity to enhance human potential rather than diminish it. His call to action for the FinTech community is to embrace this transformation with curiosity and collaboration.
As AI simplifies the investment process, the barriers to participation in financial markets will continue to fall. This democratisation of access can foster a more inclusive and innovative ecosystem, one that values both technological advancement and human expertise.
At Quantoro Technologies, this philosophy underpins everything from platform design to research methodology. The aim is not just to build smarter tools, but to create an environment where investors, regardless of experience level, can interact intelligently with technology.
Advancing FinTech Recruitment for a Smarter Tomorrow
At Harrington Starr, conversations like this one exemplify why FinTech recruitment is more critical than ever. As AI, data science, and quantitative trading continue to converge, the need for adaptable, forward-thinking talent will define which firms thrive in the years ahead.
Episodes like this remind us that the world of trading technology is not only about systems and algorithms, it is about people with the vision to apply them responsibly and creatively. Whether it’s developers building reinforcement learning frameworks or investors learning to collaborate with AI agents, the future of FinTech depends on talent that bridges innovation and insight.
To discover more discussions shaping the global FinTech landscape, explore the latest episodes of FinTech Focus TV, where leaders like David Marcos share their perspectives on technology, investment, and the power of human-AI collaboration.
