The shift from back office to front office when it comes to deploying AI in buyside firms is well underway. In fact, according to a new survey from SimCorp of 200 buy-side operations leaders across APAC, EMEA, and North America, front office AI adoption has accelerated dramatically, with 70% of firms now actively using AI, 53% scaling implementations, and 17% operating mature deployments.

But while more than 50% of firms mostly automate such processes as investment decision-to-execution, only 18% are taking advantage of automated predictive insights and more than one-third still rely on non-AI augmented analysis. This could mean a lost opportunity for many firms as competitors forge ahead in the application of AI, achieving substantial value and efficiencies.

One size doesn’t fit all

For most buyside firms, the goal of AI is to improve processes. In the past this mostly applied to the back office—focusing, like many businesses, on operations and HR to achieve efficiencies. However, applying AI to the front office is a very different animal. That’s because the processes the front office engages in are significantly more complex, and the role AI can play within them is far less straightforward.

But the leading firms are pursuing AI value in the front office, nonetheless. And to find that value, they are re-evaluating the entirety of the investment process—from the early stages of idea generation through research and issue selection, all the way to choosing what securities to actually buy. They are asking such key questions as where do we redraw our processes to apply AI effectively?

The answers are not simple, though and the application of AI may be different at each step. What is clear is that overhauling processes simply for the sake of change isn’t the solution.

The need for speed

One obvious advantage that AI can bring is speed, especially in straight-through processing (the time from investment decision to execution). The manual workflows often involved in straight-through processing—that is, people swiveling in chairs, flicking among multiple screens, doing data entry—is where AI tools can have significant impact. In fact, many in the industry see the potential to shift straight-through processing from a front-office function into a more operational and/or administrative task.

And yet, according to the SimCorp survey, only 17% of firms have fully automated straight-through processing with no manual intervention — and with 63% still lacking a unified data layer across front, middle, and back office, it's easy to see why. Without it, the execution latency that manual processes create is unlikely to disappear. With the speed at which markets move, latency can be a major competitive advantage, especially in areas that are more commoditized.

Quicker processing of research volumes can help the front office determine what investments to make in a more timely manner and get those decisions into the system and into portfolios. Using AI to gather data into a single workstation can also free up a portfolio manager to focus on those decisions. And for those 18% referenced above that use predictive analytics, they are the ones truly beating the clock, anticipating market moves and swiftly identifying opportunities while competitors merely react after the fact.

Human in the loop

Despite the advantages of automation, for many firms AI is at its most effective when combined with human input and aligned with their competitive differentiators. For them, AI’s advantage is in its ability to enhance the delivery of their distinct methodologies and strategies. AI can give their established investment teams “bionic arms,” allowing them to do more with less and garner new and better insights.

One way AI can do this is by improving a team’s ability to proactively monitor the portfolio or the market. It can help them manage, buy, sell, trade, time, decide, and size, their portfolios—all of which can influence investment outcomes. In fact, at many firms AI agents are already being trained to serve different purposes, for different approaches, with different skills to make better, data-driven investment decisions.

But these agents still need to interact with humans. And humans will need to learn how to interact with them, developing interactive processes that ultimately drive strategic goals and build investment expertise. To get there, though, may require a firm to strengthen its transformational DNA—that is, its ability to change habits and see new opportunities for value. Not only will teams need to rethink how they operate, but they will also need to build out such new capabilities as data validation and risk management, because in an AI-augmented environment, the quality of the output is only as good as the oversight behind it.

Leveling up

Clearly use of AI in the front office has moved from an exploratory mindset to deployment. But only a little over half of firms surveyed are expanding their use with successful implementations, with only 17% having deployed AI across multiple functions with measurable ROI. That means almost 50% of firms may be leaving value on the table. And it also means that those 17% are most likely boldly drawing on AI: rethinking how decisions are made and the time it takes to make them, figuring out how to balance AI with human interaction, and, ultimately, how to embed AI into their long-term strategies to create competitive advantage.