AI is changing the investment process – but the fundamentals remain

Artificial intelligence is changing the way investment managers work, bringing a new level of speed, scale and insights to a process that has traditionally relied heavily on human research and analysis. 

For Dan Mead, Head of Investment at MAS, the biggest change is not that AI is replacing investment expertise. It is that investment teams can now process and interrogate information at a pace that was previously impossible. 

“AI is being used across the investment process,” says Mead. “It can be used to identify trends and undertake research at a much faster pace than an analyst.” 

That can mean analysing company financials, market data, economic indicators and other information from a wide range of sources, identifying patterns and then testing what those patterns could mean for an investment strategy. 

That doesn't mean the fundamentals of investing have changed. 

MAS still believes that diversification remains one of the most important ways of managing investment risk. Understanding an asset's underlying value, the quality of a business, the economic environment and the risks associated with an investment remains critical. 

AI's potential goes beyond analysing more information, more quickly. It can also help investment teams identify patterns, connections and shifts in sentiment that traditional research tools might miss, drawing together insights from a much wider range of sources. 

In practice, this can provide an additional perspective on what is happening in markets, what might be driving it and where further investigation could be worthwhile. The value lies not simply in the volume of information processed, but in what that information reveals.  

“It's the speed and scale that’s really interesting,” Mead says. “You can bring together huge amounts of information and start to understand what it might mean much more quickly. Investment implementations can then be automated or provide Portfolio Managers more time to make a decision.” 

Machine learning is also becoming increasingly useful for scenario analysis. Rather than simply looking at what has happened in the past, models can analyse patterns in data and model potential outcomes under different conditions. 

For an investment manager, that could mean testing how an investment or portfolio might respond to changes in interest rates, inflation, economic growth or individual company factors – and then assessing whether a change is warranted. 

The result is not necessarily more decisions. It can be better-informed decisions, made faster. 

A July 2026 report from CFA Institute, Artificial Intelligence and the Future of Finance, describes AI as a structural force that is changing how investors process information, allocate capital and manage risk. It notes that AI is making analysis faster, cheaper and more widely available, while also highlighting the continuing importance of professional judgement and oversight.  

 That balance matters because AI-generated insights are not infallible. Models can misinterpret information, reflect biases in their data or identify patterns that don't hold when market conditions change. An apparent signal is not necessarily an investment opportunity. 

For investment managers, the task is to test those insights, understand the reasoning behind them and decide whether they stand up to scrutiny. AI can help identify where to look, but professional judgement remains essential in deciding what the findings mean and whether they warrant action. 

For Mead, the future is not about AI replacing investment expertise, but about artificial intelligence and human intelligence (HI) working together. 

“The real opportunity is where AI and HI come together,” he says. “AI can do the heavy lifting – pulling together huge amounts of information, analysing it and running different scenarios – but you still need people to ask the right questions, challenge the outputs and apply oversight.” 

He believes that combination could ultimately evolve the role of investment managers rather than replace them. 

“As the technology gets better, we should be able to spend less time gathering and processing information and more time thinking about what it actually means. That’s where the value of investment expertise comes in.” 

The next phase of AI in investment management, then, may be less about humans versus machines and more about what happens when the two work together. 

The machines can process more information, more quickly. The investment manager still has to decide what matters.