Redefining the Investment Edge in the Age of AI

• Artificial intelligence (AI) is transforming the way investment managers work, but gaining a durable edge still depends on differentiated information, thoughtful analysis, and trusted expertise.

• We view AI as the connective layer that helps investors bring together differentiated data, research, and analytical capabilities to make more informed decisions, faster.

• Instant Query (iQ), our AI-powered system within our Insights research platform, enables clients to seamlessly explore, access, and curate State Street Markets’ research, indicators, and analytical methods in a trusted environment.

• Drawing on longstanding partnerships with leading academics, including the recent addition of AI-focused researchers at the Massachusetts Institute of Technology (MIT), State Street Associates helps clients navigate the opportunities and risks of using AI in investment decision-making.

Ambitious investors have always faced a daunting challenge for at least two key reasons. First, markets evolve in genuinely new and unpredictable ways. Second, competition is fierce. Gaining an investment edge requires continually making better decisions.

In recent decades, differentiated data and analytics have proven to be powerful tools for informing those investment decisions when applied well. The latest chapter in the evolution of data and analytics is the unprecedented volume of information that technology has made available. While this has expanded opportunities for investors, it has also introduced new challenges — information overload and an increasingly rapid pace that demands staying ahead of the competition. Every day generates a steady stream of market data, economic releases, research publications, alternative data, risk indicators, and policy developments. With the advent of AI, the industry has now entered a new chapter. AI promises to boost and accelerate the data and analytics advantage, but its true value depends on how effectively it is used, in that, practitioners must separate meaningful innovation from passing fads. In our view, the most pressing question is not how AI can create more information or content, but rather, how it can help investors connect the right information at the right moment to make informed data-driven decisions before an opportunity disappears.

Helping investors convert information into actionable insights has always been at the core of what State Street Associates does. While AI can and should increase speed and scale, it should not do so at the expense of trust and confidence.

For more than 25 years, State Street Associates has helped investors uncover differentiated insights from unique data sources and innovative academic research — ranging from State Street PriceStats daily inflation and investor sentiment to novel methods of portfolio construction and statistical prediction. Additionally, our long-standing partnerships with more than 10 leading academic researchers, including MIT professors Roberto Rigobon and Hui Chen, provide in-depth perspectives on pressing questions in AI. For example, we are helping clients enhance machine-based prediction models with sound economic logic to improve reliability and better understand how confidence in large language models’ (LLMs) outputs can be assessed. Together, these data sources and viewpoints are the types of ingredients that help our clients develop their own investing edge. While AI does not change that mission, it fundamentally changes the speed at which information can be gathered, connected, and acted upon.

Our goal is not to argue for a single best answer, nor to provide an exhaustive view of AI’s potential in investing. Rather, we aim to share our perspectives on some of the most compelling opportunities, the key risks investors should consider, and how these views are shaping the tools and capabilities we are building to support our clients’ evolving investment processes.

Investing is fundamentally about making the best decisions possible, while balancing risk and return. Information fuels these decisions: What information you have and how you use it. Investors have different goals, hypotheses, and world views, and it is precisely that diversity which makes markets work. If everyone relied on the same data, used the same AI tools for analysis, scanned the same earnings report, or ran the same quantitative back tests, investing would be a far less rewarding endeavor.

It is important to note that AI alone does not create an investment edge. While rapid adoption of new tools and technology can initially give an edge to early adopters, those methods eventually become ubiquitous and turn into table stakes. The true source of investment edge has always been the information that is used, how it is combined, and the expertise applied to interpreting it. We believe AI will follow a similar path.

AI can play a powerful role in strengthening that edge and offers a distinct perspective. Data is messy and fragmented, and investors often devote considerable time to finding the right information, much like the proverbial needle in the haystack. It is often said that 80 percent of research is spent sourcing, cleaning, and organizing data, and only 20 percent is dedicated to analysis. Yet, it is in that final stage where the greatest value is often created. AI has the potential to compress much of this preparatory work, giving investors more time to focus on interpretation, insight, and better decision-making.

We see exciting potential for AI to act as the “glue” that connects trusted information and tools, helping researchers explore and expand upon available insights. The investment industry has spent decades building a rich ecosystem of data, research and analytics. What portfolio managers need now is faster, and more effective ways to synthesize it.

Perhaps this all sounds obvious. Yet, putting it into practice is far from straightforward. Two factors are important to consider: The role of the person and the role of trust.

Setting aside the deeper philosophical debate about what AI can or cannot do in principle, the reality is that investors cannot hold an AI system accountable for investment outcomes, or any outcomes, for that matter. People remain accountable. They also bring the creativity, judgement, and diversity of thought that we described earlier.

Thus, an exciting role for AI is to serve as the connective layer between trusted data, trusted tools, and human expertise — and to do so quickly. The objective is not to remove human judgment from the investment process. Quite the opposite. By reducing the time spent gathering, organizing, and cleaning information, AI enables decision-makers to devote more time applying experience, intuition, and healthy skepticism where they matter the most.

People hold deep, nuanced expertise, but scaling that expertise can be difficult. Traditional code-based programs and models are relatively transparent and verifiable, but often rigid and slow to adapt. General-purpose AI is fast and flexible, but not always reliable. We believe the most promising approach sits between these extremes: Combining trusted tools and institutional knowledge with AI systems that can rapidly identify, access, and orchestrate them transparently.

Those who have worked extensively with AI know it can address problems with remarkable tenacity, reasoning through challenges, writing code, iterating solutions, and in some unfortunate cases, even transgressing the rules to solve a problem. Still, there are real limits to how well this approach scales. First, reinventing solutions on-the-fly can be more costly than relying on established ones. Second, the logic behind a given task’s output can be difficult or impossible to validate. Third, answers may subtly gravitate towards a generic average, diluting the differentiated insights that give investors a refined advantage.

In our experience, it is crucial to crystallize trusted tools and institutional knowledge when the goal is to move quickly while keeping people in control. This fosters trust in the end result because there is a shared understanding of what these tools do, and confidence that they will perform as expected every time. With this approach, the risk is no longer that a person acts on information that is inaccurate or fundamentally wrong. Instead, the downside is limited to receiving an answer a user did not want, but one that can be questioned and, if necessary, disregarded.

Over time, these accumulated decisions do more than make a person or organization more efficient. They become expertise, a source of differentiation, and, ultimately, the edge itself.

These principles are not merely theoretical. They are shaping how we are building the next generation of research tools at State Street Associates, beginning with Instant Query.

Instant Query (iQ) is the first step on our journey to accelerate a distinctive research process. Embedded within our Insights research platform, iQ connects our curated collection of thousands of indicators, interactive charts, strategist views, award-winning academic research, rigorous methodologies, and a growing suite of on-demand analytic tools such as our Signal Studio.

iQ does exactly what its name suggests: Ask a question (query) and get an instant answer sourced from State Street’s unique information set. You bring the critical thinking; iQ does the gathering. Historically, understanding what State Street's research and data were signaling about the Euro might have required reviewing multiple charts, datasets, and strategy reports. Now, you can simply ask iQ to summarize the research team’s perspective on the Euro and the indicators most relevant to that view. Within seconds, it delivers a curated summary, complete with links to underlying research and supporting charts.

Investors can also use iQ to analyze proprietary indicators, explore historical market relationships of State Street’s indicators, and understand how an indicator is built. For example, users might ask, “What do aggregate investor positioning indicators say about sentiment in the technology sector?", "How has the Japanese Yen performed against the United States dollar in the month after spikes in currency turbulence?", or "How is the Foreign Exchange (FX) Turbulence indicator constructed, and how should I interpret it?" In seconds, iQ can retrieve and visualize proprietary indicators, synthesize written research perspectives, and surface the underlying evidence supporting the result.

The future belongs to investors who can combine trusted information, powerful tools, and human expertise to create an edge. The best time to begin is now. Let’s get started.