Key Takeaways
- AI assistants are helping capital markets firms move beyond chatbots to unlock real productivity, insight, and scale.
- Leaders like Citadel and Jane Street are using AI to drive billions in revenue by embedding it into research, trading, and advisory workflows.
- AI assistants streamline everyday tasks like data gathering, portfolio rebalancing, and client prep, without sacrificing accuracy or control.
- With explainable outputs, real-time performance, and secure infrastructure, KX makes AI assistants ready for production in regulated environments.
- Firms that start with focused AI use cases, like research and relationship management, are seeing fast wins and scalable results.
Capital markets are at a turning point. AI adoption is accelerating but many firms remain stuck in low-impact use cases like chatbots and FAQ automation. Useful, but not enough to stay competitive and drive revenue.
While some banks have focused on automating help desks, others are automating alpha. AI-natives like Citadel and Jane Street have been driving revenue, using AI at scale to transform research, wealth management, and trading strategies. In just the first half of 2024, Jane Street doubled its earnings to $6.1 billion.
This divergence is reshaping the industry. AI-native firms are rewriting the rules: scaling faster, capturing market share, and eroding traditional profit pools with new models built on intelligence and speed. Meanwhile, almost half of hedge funds already use generative AI (GenAI) in day-to-day operations. IDC projects the financial sector will double its AI spend to over $400 billion by 2027.
Today’s markets are driven by volatility. Between mid-2024 and mid-2025, markets were battered by everything from tariff wars to geopolitical flashpoints. In April alone, a single U.S. policy shock triggered a 13% drop in equities, a 47-basis-point swing in Treasury yields, and one of the largest VIX spikes on record.
Volatility at this scale is exposing the limitations of traditional research and risk workflows, putting AI’s real-time decision-making strengths in the spotlight.
Across the industry, five common barriers are slowing progress:
- Explosive growth in the volume of structured and unstructured data
- Fragmented data landscapes, with information siloed across disparate systems
- Severe analyst capacity constraints and other mounting time pressures
- Rising client expectations for faster, deeper insights
- Difficulty scaling infrastructure to support enterprise-grade use cases
- Lack of verifiable, audit-ready outputs undermine trust in AI results
To move beyond low-impact deployments and pilot purgatory, you could turn to domain-specific, agentic AI assistants. Built on a high-performance data layer and accelerated with GPU-powered AI pipelines, these solutions are helping firms utilize GenAI where it counts: in everyday workflows that impact revenue, performance, and client outcomes.
Let’s explore three key use cases that illustrate the potential of AI assistants in capital markets, and the broader operational and strategic benefits they can unlock for your business.
Agentic AI use cases: What they are and who they are for
AI assistants deliver timely, performant, scalable, conversational access to historical and live data, tailored to the specific needs of capital markets. Here are three powerful use cases:
Rethinking research workflows
Research teams are under constant pressure to cover more names, generate differentiated insight, and respond quickly to new events. But manual research remains time-consuming, and data is often scattered across filings, reports, models, and internal sources.
An AI research assistant can enhance the output of sell-side research analysts in investment banking and asset management. This assistant enables the use of natural language querying to streamline research across all relevant datasets: structured and unstructured, live and historical. With explainable answers and audit trails, you can generate summaries, calculations, peer comparisons, and market commentary in minutes rather than hours.
The result? You spend less time wrangling data and more time interpreting insight, identifying market shifts, and engaging clients.
Deepening insight at the client edge and refocusing on value
Client-facing teams are under constant pressure to deliver actionable, high-quality guidance, often across a growing book of business. But preparation is slow, manual, and fragmented. Compiling market analysis, CRM notes, portfolio context, and firmwide research can take hours.
An AI relationship manager addresses this by automating much of the prep work. This assistant retrieves relevant updates, assesses market impacts in real time, and generates tailored talking points in seconds. Rather than relying on fragmented research and static templates, you can gain dynamic, context-aware insights aligned to each client conversation.
The result? Faster, better-informed responses. More time engaging clients. And greater capacity to deliver differentiated advice and uncover new opportunities, all without expanding the team.
Scaling proactive portfolio management
Markets are moving faster and client needs are growing more complex. For portfolio managers and wealth advisors, keeping strategies aligned to both real-time conditions and client-specific mandates is no longer a periodic task, it’s a continuous challenge.
AI portfolio construction helps you align strategies with client goals and constraints. By integrating real-time market data, risk signals, and evolving client goals, these assistants proactively flag opportunities and risks, generate strategy recommendations, and automate constraint-aware rebalancing.
The result? More resilient portfolios, delivered faster and more consistently. You can respond to client needs and market shifts in minutes, enabling a higher standard of service, better performance alignment, and more efficient growth across their book of business.
Under the hood: What makes these assistants work
For use cases like these to be effective in capital markets, they need to operate across structured and unstructured data, deliver real-time performance, and offer traceable, explainable outputs.
This requires a robust architecture that:
- Supports natural language and agentic workflows at scale
- Handles time series, relational, and semantic data in a single environment
- Enables rapid querying, vector search, and dynamic computation
- Integrates easily with models, policies, and downstream tools
- Delivers accurate, auditable outputs grounded in real-time and historical data
Firms are pairing performant data engines with GPU-accelerated infrastructure to achieve the necessary speed, scale, and efficiency. This combination is helping teams embed AI into production workflows without compromising latency, accuracy, or governance.
Transformative benefits: Why KX and NVIDIA AI assistants stand out
We’ve partnered with NVIDIA to help bring these agentic AI capabilities to capital markets firms, embedding intelligence directly into the workflows where it drives real performance gains. At the core of these capabilities is our high-performance data layer, purpose-built for speed, scalability, and the ability to query structured, unstructured, and time series data in a single environment.
This foundation is supercharged by NVIDIA’s GPU-accelerated infrastructure and AI factory stack, enabling rapid ingestion, reasoning, and response, even at petabyte scale.
This combination creates seamless connections between data and decision-makers, enabling your team to more easily deploy AI and focus on outcomes. Choose your models. Set regulatory or liquidity guardrails. Ingest data from multiple sources. And then quickly get accurate answers to those who need them.
Instant, context-rich insights at scale
KX supports massive-scale vector storage, handling tens of petabytes of data with no impact on performance. And we harness NVIDIA’s hardware and software stack with such speed and efficiency that it radically outperforms other solutions. Whatever your use case, that means context-aware, client-ready analysis, insights, and recommendations at scale and at lightning speed.
Unified data for deeper intelligence
With our tech, you can query structured and unstructured data, including proprietary data and real-time feeds, in one unified system. This means richer, time-aware, verifiable insights that encompass filings, tick data, charts, live sentiment, and macro trends, with no tool switching, and yet with the kind of high performance and low latency that capital markets demand.
Productivity through automation and accessibility
AI assistants automate repetitive tasks, freeing experts from time-consuming manual data pulling to focus on delivering value, differentiated insights, and client impact. And our conversational interfaces also enable access to data previously locked behind ‘q gods.’ This helps teams better deliver transformational value across use cases, covering four times more stocks and clients while maintaining the same high quality of research.
Prioritizing accuracy, explainability, and compliance
For AI assistants to be production-grade, they must go beyond retrieval. That means grounding every answer in real data, applying timestamp-aware logic, and embedding compliance context from the start. Our assistants are built on a high-performance time-series engine with full traceability, enabling audit-ready outputs and minimizing hallucination risk. By integrating NVIDIA’s NeMo guardrails and re-ranker, we ensure each response is contextually relevant, regulation-aligned, and enterprise-trusted.
Built specifically for capital markets
KX AI assistants are tuned to the needs of capital markets. So they offer, amongst other things, ultra-low latency, robust audit trails, assured security and privacy, seamless connection to CRM records to tailor insights to specific clients and contexts, and the means to proactively manage risk and rebalance portfolios before exposure becomes critical.
A practical path to transformation
You know that speed of insight and action is now a key competitive edge. The trick is ensuring your time and investment are focused on use cases with real business impact.
For many firms, AI assistants are proving to be a practical starting point. By targeting roles like analysts, advisors, and relationship managers, you can unlock measurable productivity, deepen client engagement, and extend the reach of your teams.
The most effective strategies start small, deliver quick wins, and scale iteratively, driving real results across research, advisory, and relationship workflows. Our AI Assistants, powered by NVIDIA, help embed intelligence, turning AI ambition into measurable, revenue driving, performance gains.
Discover how we can help you unlock the following AI assistant use cases: AI Research Assistant, AI Relationship Manager, and AI Portfolio Construction.
Learn more about our partnership with NVIDIA to deliver a unified analytics platform built for the velocity and scale demanded by capital markets.
