The financial industry is at an inflection point. AI has shifted from pilot programs to production systems, and institutions are now scaling data-driven initiatives across fraud analytics, trading optimization, regulatory compliance, and customer engagement.
Yet while use cases continue to grow more sophisticated, most institutions are still held back by the same issue: fragmented, inflexible infrastructure. In today’s AI-powered economy, data silos aren’t just inefficient, they’re competitive liabilities.
According to the 2025 NVIDIA State of AI in Financial Services Report, 76% of financial institutions using AI reported revenue growth, and over 60% saw reduced operational costs. But behind those gains lies a shared realization: unlocking AI’s potential at scale requires rethinking how data is accessed, processed, and governed.
The Rise of Data Intelligence in Finance
What’s emerging is a new category of infrastructure: the data intelligence platform. Unlike traditional storage or siloed analytics tools, these platforms unify data across environments (cloud, edge, and core) and deliver real-time insight through metadata-rich architectures, automation, and native integration with AI workflows. In financial services, where milliseconds matter and compliance is non-negotiable, this unified, intelligent foundation is quickly becoming the new standard.
As firms adopt more advanced models, from retrieval-augmented generation (RAG) to agentic systems capable of autonomous decision-making, they need infrastructure that not only performs but understands AI demands. DDN’s Data Intelligence Platform has emerged as a key enabler of this transformation, powering some of the most advanced AI environments in the world, including NVIDIA’s internal clusters.
Industry-Wide Alignment Around AI Infrastructure
The financial sector is not evolving in isolation. As the NVIDIA report shows, there is now widespread alignment around the strategic importance of infrastructure:
- 98% of financial executives plan to increase AI infrastructure investment in 2025
- The majority are prioritizing unified platforms that support both performance and governance
- Top ROI-generating use cases include trading optimization, customer engagement, and document processing
These insights reflect what we see in the field every day: AI is no longer an experimental edge case; it’s becoming the foundation of modern financial operations. But scaling it requires more than just GPUs and models. It requires a data intelligence platform that reduces latency, ensures compliance, and unlocks actionable insight, without duplicating or moving data unnecessarily.
Why Speed Alone Isn’t Enough
Today’s financial AI workloads don’t just require fast storage, they demand real-time awareness. Traditional infrastructure falls short under the pressure of concurrency, metadata intensity, and policy requirements. What’s needed are systems that can:
- Trigger workflows the moment new data arrives
- Index and govern multi-modal data, text, video and transactions
- Seamlessly integrate with modern pipelines like NeMo Retriever, Trino, and real-time RAG
This is the essence of data intelligence. It’s why DDN’s platform is helping financial institutions collapse the gap between data ingestion, insight, and action—whether they’re running fraud detection in production, optimizing portfolios, or enabling 24/7 autonomous client advisory.
From Generative AI to Agentic AI and ESG
Looking forward, the next leap in financial AI will be agentic systems: models capable of reasoning, adapting, and acting across complex tasks. Already, use cases like dynamic portfolio rebalancing, real-time KYC (Know Your Customer), and autonomous risk modeling are taking shape.
Simultaneously, AI for ESG (Environmental, Social, and Governance) and sustainable finance is rapidly maturing. According to the NVIDIA report, production-ready ESG AI use cases have doubled year-over-year. These require infrastructure that is not only fast and intelligent, but also energy-efficient, traceable, and scalable across environments. Data intelligence platforms purpose-built for these dual imperatives, autonomy and sustainability, will define the next decade of financial innovation.
Infrastructure is the Differentiator
AI success in financial services is no longer about model accuracy alone. It’s about infrastructure readiness. To build trust, scale outcomes, and stay competitive, financial institutions must unify and operationalize their data with speed, security, and intelligence.
DDN’s Data Intelligence Platform is purpose-built for this moment, enabling real-time, AI-driven decision-making across the most performance-sensitive and regulated environments in the world. Read the whitepaper to discover how leaders in finance are using DDN’s platform to scale AI, reduce risk, and unlock new revenue streams. To learn more, visit our website.
