ROI FOR AI: GOING BEYOND THE HYPERBOLE FOR TRUE BUSINESS IMPACT

of professional investors agree that GenAI will create efficiencies that lead to more value-add investment management activities.*

*Source: Reuters/Aladdin Brand Image Survey 2024

Generative AI has come up in every conversation for the past 2+ years. And it’s not just pervasive in the tech industry—every sector, every leader, every individual is thinking about the impact of its transformative capabilities. What will it revolutionize? And how will it reshape the way we live and work?

Looking beyond lofty prognostications, the value of AI is there for the taking, but for now lies beyond the hype of drastic technological change. Today, the value is really in an organization’s ability to harness GenAI as a tool for true, pragmatic business transformation—to fundamentally reimagine how we operate down to the smallest details.

As with any new transformative technology, these changes will be incremental, evolving as the tech itself evolves—following a similar paradigm to the “digital transformation” era from which we are now exiting.

Today, many organizations are looking at a project or workflow that has 10 steps across myriad teams. They are evaluating how AI can condense that process into five steps for instance, boosting productivity, reducing points of friction, and increasing shared knowledge. In investment management terms, this could mean rethinking how a portfolio manager makes allocations—arming them with the right information, such as liquidity data, earlier in the process to streamline trading and reduce friction.

In financial services, we are seeing a shift in focus from technical success with AI to commercial, operational, and strategic success. This goes beyond using LLMs and lands in the realm of the ROI behind AI-driven business applications.

Institutions like BlackRock are leveraging those applications with partners like Snowflake to fundamentally change how they interact with both their data estate and their customers.

Jonathan Regenstein, AI Industry Principal, Financial Services, Snowflake

Imagine: various teams across an organization have adopted this approach, simplifying and speeding up how they manage core tasks across functions such as portfolio construction, analytics, and compliance.

GenAI capabilities can be impactful for a range of functions across the company, reshaping not only how each team operates, but how those teams work together. Instead of going from 10 steps to five steps, we’re able to fundamentally reimagine the order of operations and the role that one team can play. Think obliquely: moving step seven after step three, eliminating step five. If teams can weave the tech into their every day in a way that makes their work more productive, allows them to reduce pain points in the process, and focus more time on higher-value work—that is meaningful change.

INNOVATIONS

AI agents at every level
Aladdin is building agents across knowledge, experience, and workflows—with the goal of enabling more customization across the platform. Our AI agents will surface knowledge from user guides and release notes, but also client-specific information and access to data.

Workflows will transform with AI.

Our compliance copilot will streamline analysis of investment management agreements (IMAs) and facilitate the creation of compliance rules, saving time and reducing risk of manual role creation. The investment research agent streamlines the process of gathering and synthesizing research data, allowing users to interact with research notes, search through large amounts of data, and get answers for support queries through natural language.

Driving value
The experience of the future will be individualized and connected, bringing together the right information in the context of the user—ensuring data privacy and risk controls are in place to protect your data and information. Each step we take in transforming Aladdin with AI is to drive value for our clients through delivering a better experience and enhancing productivity through reimagined operational processes.

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Ultimately though, this must all add up to an end-to-end business transformation. That means these changes aren’t one and done. The bottom-up connectivity gives us an opportunity to make an immediate impact, but a business of the future must simply operate with an AI-focused mindset. Having a clear long-term vision of how to shift to these target operating models will be an important catalyst for the necessary business transformation. A top-down vision, paired with these incremental changes, can then amalgamate into meaningful and impactful change.

That’s where the concept of “composability” comes in. The AI space is moving quickly. Building agents for the smallest task allows us to snap together these modular components to create AI solutions—and then reconfigure those solutions to create different outcomes. Think about it as building blocks.

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And as building blocks, agents need to be able to reason together—“talk,” “debate,” and “collaborate” with one another to get to the best solution. In this way, they are more than the sum of their parts, able to tackle more complex solutions, and generate greater ROI.

This concept is not new to development; it’s how we approached building our APIs in the Aladdin platform and user experience. And applying this concept to agents facilitates adaptability and allows us to build for the consolidated workflows of today, while we reimagine the business transformations of the future.

So, in a paradigm where agents are composable and able to collaborate, the value streams and workflows of the organization can be completely remodeled in a way that has never been previously possible—far beyond simply moving step seven to after step three. Instead of solving a task, or a series of tasks in a process, with composable agentic capabilities we can redesign the entire process with AI as the collaborator.

Now, think about what this means at the industry level.

There’s even more value that comes from this type of collaboration across the industry. Financial services firms have traditionally operated in silos, each developing their own solutions. But many of these firms are facing common challenges, and taking an approach of openness (as we discussed with investment infrastructure) can help us innovate new solutions together. This includes sharing best practices and developing industry-wide standards and frameworks that can facilitate the integration of AI across different firms.

Cutting through the hype, there is real value in harnessing AI capabilities to strategically transform not only operations and technology, but also how we deliver investment solutions to clients and the scale at which this is done. And as the tech continues to advance, so will the industry.