AI-ready data foundations for wealth and asset management

Wealth and asset managers are under pressure to do two things at once: deliver more relevant, personalized advice and operate with greater transparency, control and speed. That pressure is intensifying as firms explore contextual search, advisor copilots, enterprise AI and agentic workflows. But in practice, most firms discover the same truth: AI does not scale on top of fragmented data, unclear lineage and inconsistent controls.

Before a firm can deploy trusted AI across advisory, investment, operations and client service, it needs the right foundation. That means governed lineage, clean reference data, secure access controls and cloud-native data products that make information usable across the enterprise. Without that groundwork, even promising AI pilots struggle to move beyond experimentation.

At Publicis Sapient, we help wealth and asset management firms move from siloed data and stalled pilots to modern platforms built for production. By combining deep financial services expertise with Snowflake-based data modernization, we help organizations create the data foundations needed for faster decisions, auditable workflows and better advisor and client experiences.

Why AI in wealth and asset management starts with data modernization

In wealth and asset management, high-value decisions depend on trusted data flowing across portfolios, client records, market sources, research, operations and compliance processes. Yet many firms still rely on disconnected platforms, legacy warehouses, manual workarounds and brittle data pipelines. That environment makes it difficult to scale personalization, deliver timely insights or give advisors the confidence to act on AI-supported recommendations.

The challenge is not just access to more data. It is creating a governed operating foundation where definitions are consistent, ownership is clear and controls are built in from day one. Publicis Sapient’s broader Data & AI approach is designed around exactly that requirement: fixing the plumbing first, then embedding AI into real workflows with lineage, monitoring, auditability and measurable business impact.

For wealth and asset managers, this is the difference between an interesting demo and an enterprise capability. Trusted AI depends on:

These capabilities do more than reduce risk. They make AI usable in the real world by improving the quality, timeliness and traceability of the information behind every recommendation, search result, workflow and decision.

Building the cloud-native data core with Snowflake

Publicis Sapient and Snowflake work together to help organizations unlock, unscramble and unleash their data. For financial services firms, that means moving from rigid and siloed environments to flexible, scalable cloud-native ecosystems that support advanced analytics, enterprise-wide decision-making and AI.

Our work spans the core functions of a modern data center of excellence, from ingestion and processing to governance, lineage, quality and consumption. In wealth and asset management, that foundation matters because advisor enablement and intelligent automation both depend on the ability to share trusted data across domains without losing control.

Snowflake’s architecture supports this shift by enabling faster integration, scalable processing and more flexible data sharing. Publicis Sapient brings the transformation model around it: strategy, architecture, engineering rigor, product thinking and embedded governance that align technology decisions to measurable business outcomes.

Proven patterns from investment and advisory platforms

For a major investment company operating across North America, Europe and Asia, Publicis Sapient partnered with enterprise architecture and business technology teams to design a data mesh architecture and introduce Snowflake as an information delivery platform. The result included stronger integration with the data platform, onboarding for data product teams, data product design and a robust data consumption layer. This kind of architecture helps create the reusable, domain-based data products that future AI use cases depend on.

For a global investment management firm, we helped establish a Snowflake governance program focused on monitoring, access control, cost management, security and compliance. The solution included role-based access control, automated governance tooling, account monitoring, data transformation models and resource monitoring. Publicis Sapient also helped create a governance dashboard that gave the firm real-time visibility into usage, cost and security compliance while supporting onboarding across projects and user groups.

In another investment management engagement, we supported the build of a next-generation market reference data platform. The client wanted to improve data quality, expand coverage, simplify consumption and strengthen auditing. Publicis Sapient helped modernize the platform using Snowflake and AWS services, with capabilities for real-time ingestion, transformation, quality checks and consumer access. We also helped create a configurable vendor data onboarding tool, a metadata-based processing application and a new security setup service that significantly accelerated instrument setup across the firm.

These are not isolated technical wins. They represent the underlying business capabilities firms need if they want to scale AI with confidence: better lineage, cleaner vendor and market data, more transparent validation, stronger controls and faster onboarding of new data products.

From advisor productivity to trusted AI

In one large investment bank engagement, Publicis Sapient supported the design of a next-generation advisor platform and the big data engine behind it. The goal was to migrate multiple data sources, including hundreds of legacy systems, so advisors could view and recommend insights to clients based on the latest asset trends and reports. Publicis Sapient helped drive data and technical requirements, architecture, engineering and governance while building capabilities with technologies including Snowflake, DBT, Airflow and Power BI.

This is the next wave for wealth and asset management: data platforms that do not just centralize information, but actively power better advisory work. When firms modernize the data core, they create the conditions for contextual search, more relevant insights, faster reporting and AI-assisted decision support. They also make it easier to keep humans in the loop, preserve explainability and maintain the audit trails that regulated businesses require.

That matters because agentic workflows and advisor copilots are only as trustworthy as the enterprise context behind them. Publicis Sapient’s enterprise AI approach emphasizes clear ownership, traceable lineage, role-based access and auditability before deployment. In a wealth management setting, those principles help firms move toward AI-enabled advice augmentation without sacrificing compliance, control or client trust.

The path from pilots to production

Publicis Sapient helps wealth and asset managers move from pilots to production by connecting Snowflake-based modernization with a broader transformation model across Strategy, Product, Experience, Engineering and Data & AI. We do not treat AI as a layer added at the end. We help build the data, governance and delivery foundations that make it sustainable.

The opportunity is clear. Firms with modern, governed data platforms can make faster decisions, improve advisor productivity, accelerate onboarding of new data products, strengthen compliance visibility and create more personalized client experiences. More importantly, they are better prepared for the future of enterprise AI.

In wealth and asset management, trusted AI starts long before the first model or agent is deployed. It starts with the data foundation underneath it. Publicis Sapient and Snowflake help firms build that foundation so AI can move from ambition to auditable, scalable business value.