The bar for AI in financial services is rising faster than any technology adoption in the history of the industry. Today, execution at scale is the defining challenge, and leaders will be those who effectively embed AI across the business to help drive revenue, manage risk, and shape client outcomes. Competitive advantage in the AI era comes less from access to models and more from a company’s ability to continuously learn from its own data, orchestrate human-agent collaboration, and operate a secure and managed AI platform.
The shift has already begun. Leading financial institutions are rapidly moving beyond narrow use cases to agent AI solutions designed to drive impact at scale. Frontier companies—organizations that reimagine business processes around human-agent collaboration—are integrating intelligence into the workflows, data environments, and managed systems where decisions are made and work is completed.
The challenge is that within the highly regulated constraints of financial services, access to data is tightly controlled, critical data is often fragmented across traditional platforms, and workflows span multiple systems, teams, and jurisdictions. Internal data must be integrated with external data such as market data, research, and third-party insights. Businesses need to ensure that the right people have access to the right data, in the right way, while keeping it all safe.
Our partnership with Microsoft is shaping the next era of AI-enabled data and intelligence-driven workflows. We respond to our clients where they work by embedding S&P Global’s trusted, high-quality data directly into their workflows, unlocking agent capabilities that turn insights into actions and enabling accurate, faster, and more informed decision-making. Together, we accelerate the way our clients drive growth, manage risk and seize opportunity in an increasingly complex and rapidly changing market.
Sally Moore, S&P Global Chief Customer Officer
Trust is paramount, and the best way to scale AI is by leveraging the unique strengths and characteristics of trusted cloud environments and the applications that professionals use to do their jobs. In this way, the data used by the agent solution can be configured to inherit existing permissions, license constraints, and governance controls without the need for enterprises to rebuild trust around the new layer.
To do this, you need to think of AI as an operational capability that unifies data, governance, tools, and workflows to bring intelligence to the place where the work is done. Success is best achieved through approaches that simplify access to critical data and embed AI into everyday decisions and actions.
Bringing AI to the workplace where data, decisions, and actions work together
Financial operations are rarely conducted in a single system. Professionals move across data, spreadsheets, meetings, messages, and business applications in scenarios that span all aspects of financial services. Just to name a few:
- A banker preparing for a meeting with a client needs more than an overview of the market. You need relevant signals, previous context, comparable activity, potential risks, and a path to next-best action.
- Risk professionals need intelligence that can be applied within existing controls, not outside of them.
- Investment analysts need current financial data in spreadsheets to test their assumptions, rather than individual answers that must be copied and adjusted later.
When embedded in workflows across the value chain, AI can help create more value, reduce handoffs, preserve context, and bridge the gap between analysis and action. AI apart from the workflow can generate useful responses, but data still needs to be copied, reconciled, and validated between systems.
The next stage of AI in financial services is about connected intelligence, bringing the right data into the right context at the right time. Our connector places Morningstar’s independent research and trusted data alongside a firm’s own data in the workflow, allowing investment professionals to generate deeper insights, act faster, and make more confident decisions with clarity and control throughout the investment process.
Adam Wheat, Chief Technology Officer, Direct Platform, Morningstar
Our focus is on narrowing the distance between trusted information, expert judgment, and subsequent action – enabling managed AI execution in context and enabling people to move from insight to action within the tools they are familiar with. That’s why we and our partners are bringing financial data and AI capabilities directly into the everyday applications and tools that many professionals use to do their jobs, including Microsoft Excel, Teams, Outlook, and Microsoft 365 Copilot. This enables intelligence that can be accessed in spreadsheets where analyzes are built, meetings where client discussions are prepared, or collaborative spaces where teams coordinate next steps.
A platform for advanced AI experiences
For financial institutions, the next model for AI starts with the data that powers the business, including market intelligence, risk signals, research, customer information, trading context, policies, and operational knowledge.
Microsoft’s approach brings together trusted data, enterprise context, and intelligence into one unified platform. It spans a rich ecosystem of financial services data providers, helps you tune your models, and builds on Microsoft Cloud’s core strengths of enterprise-grade security, compliance, and governance.
In this approach, the following key capabilities work together to connect trusted data, enterprise context, and AI-powered capabilities.
- federated connector Access information without moving or copying, providing live data.
- sync connector Provides enterprise data by indexing content from business and partner systems.
- Microsoft IQ Provide context by understanding how people work, how businesses operate, what organizations know, and how the broader business and market environment is changing.
- skill Provides expertise by defining how to perform specific business tasks.
- plugin Combine connectors and skills to package data access and task expertise into reusable functionality.
- Co-pilot cowork We help coordinate and support tasks across systems, people, and workflows, bringing agent functionality to Microsoft 365 Copilot and, by extension, Excel, Word, PowerPoint, and Outlook.
Together, these capabilities enable financial services professionals to ask more accurate questions, receive more relevant answers, and take actions directly within their workflows, all while supporting compliance efforts and maintaining context.
Expanding the financial data provider ecosystem
In recent months, we have announced this strategy through milestones that reveal the expansion of our ecosystem of financial data providers and capabilities.
The Federated Copilot connector extends the reach of Copilot by securely integrating external real-time data directly into Copilot for Excel, Copilot Chat, and Researcher agents. We recently announced federated Copilot connectors for LSEG and Moody’s, and the momentum continues today with new federated Copilot connectors for CB Insights, Daloopa, FactSet (in preview), Morningstar, PitchBook, and S&P Global. These integrations provide access to the latest market data, corporate intelligence, research, portfolio analysis, investment data, and more within supported workflows, subject to provider availability, licensing, and system integration.
As financial institutions scale AI, the combination of trusted data and enterprise platforms will be critical. Our collaboration with Microsoft allows clients to incorporate LSEG’s data into AI-powered workflows to support more consistent and informed decision-making across their businesses.
Emily Prince, Head of Enterprise AI Group, LSEG
The Copilot Cowork plugin embeds expert partner expertise directly into task-oriented workflows, enabling Copilot to support role-specific financial analysis and decision-making. Building on the recent release of the Copilot Cowork plugin from LSEG and S&P Global Energy, we have expanded the list of partners for the Copilot Cowork plugin from CB Insights, Moody’s, Morningstar, and PitchBook. Depending on partner capabilities and implementation, these plugins package unique data, models, and domain knowledge within defined workflows, enabling financial services professionals to more easily move from insight to action.
The critical question for financial institutions today is not whether to use AI, but whether they can trust the intelligence that powers it. From Microsoft 365 Copilot to Excel to Copilot Cowork, Moody’s embeds decision-grade, connected intelligence directly into the Microsoft workflows where critical decisions are made every day, so you can act faster and with more confidence without sacrificing the rigor, transparency, and accountability required for high-stakes decisions.
Cristina Pieretti, Head of Digital Content and Innovation, Moody’s
We also announced new skills and features in Copilot for Excel, one of the most widely used tools in financial services. Additionally, we introduced a starter library of pre-built finance skills and the ability for organizations to create and integrate their own skills. These enhancements, combined with new customization and control capabilities, enable financial services professionals to customize workflows, apply consistent logic, and scale analytics more efficiently.
This integrated platform supports the transition from information retrieval to managed execution. For businesses and institutions, this means more efficient preparation, more consistent use of trusted information, less manual piecing across applications, and a stronger connection between insight and execution.
Based on trust
For financial institutions, this transition will only be successful if trust is built into the architecture. Organizations must be able to innovate without separating intelligence from the controls that enable enterprise adoption.
Here, Agent 365 embodies the trust model. This enables organizations to see which agents are running, understand what data they are using, monitor the actions agents take, and apply policies that govern how agents operate. It also supports the traceability and citations that institutions need to understand how data was used, what sources influenced the output, and how agent-driven work was produced.
As agent workflows become the new standard for how analytics are performed, the underlying data must be reliable and verifiable. Through Kensho’s AI innovation and S&P Global’s expertise, we’ve done that work and built a trusted data retrieval foundation designed for how AI systems reason and operate. Our partnership with Microsoft builds on the AI-native experience the industry is already well on its way to.
Bhavesh Dayalji, S&P Global Chief AI Officer and S&P Kensho CEO
The same environment that brings data and AI closer to work must inherently provide the capabilities needed to use agents responsibly at scale. In a regulated industry, this combination is a great advantage. Businesses no longer have to choose between moving faster with AI and maintaining control over how their data and actions are managed.
For financial services leaders, the next stage of AI will not be defined by isolated experiments, disconnected tools, or AI architectures that require companies to add another layer of trust, authority, and context on top of the systems they already use. As enterprises move from experimentation to large-scale deployments, the Microsoft advantage is our ability to unify trusted data, context, workflow integration, and governance into one consistent operating model for AI, allowing enterprises to leverage the platforms they already rely on.
