Insights from the KX Capital Markets Data Report 2026

Across capital markets, AI is redefining what’s possible in research, trading, and client outcomes — and firms are responding decisively. Investment is set to rocket by 20% year-on-year as firms up the ante on what’s seen as an increasingly indispensable driver of speed, insight, and alpha.

To take the pulse of AI progress, KX surveyed more than 2,000 capital markets professionals ( 1000 quantitative analysts and 1000 C-suite IT and data leaders) in firms across North America, Europe, and Asia. We probed all aspects of their AI journey, examining how they’re managing competing priorities to drive competitive advantage in a world where signal is scarce, noise is abundant, and time is short.

If your organization is busy integrating intelligence, you won’t want to miss the full report. In the meantime, here are our top five insights from quants and IT leaders.

1. AI boosts quant productivity by 62% — with much more to come

92% of quants credit AI with boosting productivity, with the majority citing faster, better decision-making as the leading benefit, alongside automating time-consuming tasks, optimizing strategies, and gaining new insights. The impact is dramatic, with an average productivity improvement of 62%.

Better still, the benefits from AI investments are likely to accelerate as firms remove obstacles to adoption, improve integration with existing tools, and leverage higher-performing technologies. Already capital markets firms are achieving a higher success rate with AI investment than the broader economy, with only around 33% of annual spending going towards projects that failed to meet requirements. That compares very favorably to McKinsey’s finding that 80% of global AI initiatives fail to achieve their intended bottom line impact.

In particular there’s a clear opportunity to harness agentic AI; less than a quarter of firms currently use it across research, backtesting, analytics, and real-time trading advice. This shift from AI as advisor to AI as actor is game changing, enabling systems that not only understand the market but autonomously adapt to new regimes.

2. 61% of IT leaders agree there is “clear tension” with quants

Given the potential benefits, it’s not surprising quants are pushing the limits of what AI can do. 70% of analysts aren’t fully satisfied with the tools available for real-time data analysis and decision making, while 48% say that current GenAI tools “still feel limited”. However, this hunger for innovation is creating tension with IT leaders.

Where quants prioritize the freedom to experiment, IT must also consider resilience, governance, and budgets. 61% of IT leaders agree there is “clear tension” with quants, 66% feel “overwhelmed” by the demands analysts place on them, and 75% report analysts demanding access to new AI technology and tools faster than they can be delivered. Conversely, 58% of quants believe their ability to innovate is being constrained by IT or data teams, while 81% say they should have more influence over technology decisions.

How are firms balancing these competing priorities? Interestingly, the majority of IT leaders fall on the side of prioritizing innovation, reflecting the importance of data-driven predictions and decision-making to capital markets success. 65% of IT leaders say they prioritize innovation over reducing risk, with 83% championing in-house development to create the specialist applications that quants need.

3. 87% of IT leaders worry about the risk from shadow AI

Whether firms are deploying AI or ensuring the performance and scalability of the data architectures that power it, IT leaders cite security, privacy, and compliance concerns as the greatest obstacles. However, ironically, this focus on security can itself create risks.

When unable to harness the technologies they need to maintain competitive advantage, quants may turn to shadow AI — that is, unsanctioned tools. Using these tools doesn’t just elevate business risk, firms may not even have a clear picture of what tools have been used, where, or how.

Nonetheless, shadow AI is startlingly commonplace: 58% of IT leaders believe their quant teams have used unsanctioned AI tools, while 87% worry that this puts the business at risk. To reduce shadow AI, firms must focus on two areas: first, giving quants the tools they need and, second, implementing governance that prevents and identifies shadow AI use before it causes harm.

4. Quant and IT alignment drives a 6.6 month competitive advantage

While quants and IT leaders have different priorities as firms operationalize AI at scale, they remain on the same side. In most cases, analysts see IT and data leadership as supportive: helping them access and use new technology quickly and effectively. At worst, quants recognize that IT and data leadership is constrained in how much they can enable analysts.

The challenge is understanding the tensions on each side and creating an orchestration framework that reduces friction. Quant and IT priorities often seem at odds, but when orchestrated, they become a force multiplier. Analysts need to be allowed to find new approaches and applications that will extend their advantage. Likewise, IT teams must be able to ensure resilient infrastructure that can meet the demands of real-time analytics and let the business make full use of new technologies.

Firms which effectively align these roles expect to gain a decisive edge: an average of 6.6 months’ market advantage over peers. That’s extremely significant in today’s competitive landscape; it’s time in which analysts can create multiple AI applications, pioneer new investment approaches, investigate fresh opportunities, or refine data models.

5. “Firms that don’t continuously improve how they use data will fall behind the competition.”

For quants and IT leaders alike, AI success depends on trust, security, and consistency. A successful data platform builds on this foundation while delivering the scale and speed required for advanced analytics. Without it, end users can’t rely on real-time, explainable insights, undermining confidence in AI applications.

For analysts, the right data platform means rapid, flexible access to real-time and historical data, enriched with AI-driven analysis to detect patterns, forecast trends, and power high-frequency trading. For IT leaders, it means integrity, governance, and security; ensuring access is compliant, auditable, and controlled.

Both sides benefit when data delays, silos, and bottlenecks are eliminated. The result is a sharper competitive edge: 84% of quants see acting on data faster than others as a core advantage, while 78% believe firms that don’t continuously improve data use will fall behind.

Turning friction into edge

The push and pull between analysts and IT can be challenging, but it’s not an insoluble conflict — it’s an opportunity. The firms that outpace the competition in AI won’t be those that simply experiment the most. The real winners will be the organizations where CIOs, CDAOs, and quants operate as one team to industrialize AI, united by high-performance data platforms that transform insight into action and unlock the ability to predict, decide, and act before markets move.

That’s when your AI investment truly pays off.

Is your firm ready to work together for AI success? Read the KX Capital Markets Data Report 2026 to understand the potential, the pitfalls, and the paths forward. Alternatively, discover why the world’s leading firms, including the titans of Wall Street, trust KX to maximize AI’s value with continuous, high-performance analytics that power faster consensus, anticipatory decisions, and superior business outcomes