People.ai, a San Francisco‑based leader in AI‑powered revenue intelligence platforms, has announced a major enhancement to its SalesAI platform by integrating the Model Context Protocol (MCP). The new integration enables revenue teams to access comprehensive revenue intelligence — including both structured and unstructured activity data — within their existing AI workflows, such as AI agents from Claude, Microsoft Copilot, ChatGPT and other custom models. This release is designed to eliminate one of the biggest challenges for AI‑driven revenue operations: incomplete or inaccurate data.
Through People.ai’s Answer Platform, revenue organisations can now connect directly to a comprehensive data layer that combines structured customer relationship management (CRM) records with the “real‑world” unstructured business context captured from emails, meetings, chats, call transcripts and buyer interactions. Patented technology associates unstructured data with traditional CRM fields — enriching insights with persona data, engagement patterns and historical win rates that AI can reason over.
According to People.ai, legacy CRM systems often paint an incomplete picture of customer activity — contributing to findings that as much as 80 % of CRM data is inaccurate. By contrast, the MCP integration aims to ensure that AI agents work from complete and accurate activity intelligence, meaning forecasts, deal assessments and opportunity prioritisation are grounded in reality rather than limited metadata or manually logged entries.
Why the MCP Integration Matters for Revenue Teams
The Model Context Protocol (MCP) is an open standard that enables AI systems to access external data sources and tools in real time. Rather than relying solely on a siloed CRM, an AI agent connected via MCP can reason across multiple underlying systems, bringing far richer context to revenue operations.
For revenue leaders and sales operations professionals, this has several important implications:
More reliable forecasting and pipeline insights: Traditional AI tools may generate seemingly confident answers based on partial or outdated CRM entries. With MCP, AI models can factor in all the relevant activity data, be it conversation activity or meeting engagement, to make predictions about deal health.
Enhanced trustworthiness of AI: Since AI is only as good as the data it processes, the use of MCP to bring in structured and unstructured activity data can help avoid making decisions based on misleading or inaccurate insights.
Incorporating modernization in workflow: Revenue teams can ask questions in natural language within AI applications without having to leave the platform, such as “Which high-value deals are experiencing engagement decline?” and get answers right away.
According to People.ai’s CEO, integrating MCP into the Answer Platform reduces friction by bringing accurate activity intelligence to where teams already work, rather than requiring separate analytics or dashboards. This design facilitates faster action and closer alignment between AI recommendations and real‑time business needs.
Also Read: Seismic Boosts Go-to-Market Execution with Winter 2026 Product Release
Broader Impact on the Revenue Industry
The People.ai MCP integration is part of a wider shift toward agentic AI in revenue technology, where AI agents don’t just analyse data but act intelligently within business processes. As organisations increasingly incorporate generative and agent‑based AI into forecasting, coaching, opportunity inspection and prioritisation workflows, the demand for complete, trustworthy data has never been greater.
Industry predictions suggest that by 2028, around a third of enterprise software will embed agent‑style AI — making interoperability and data access standards like MCP essential for scaling intelligent workflows.
For businesses, the integration could lead to:
Faster revenue cycles, as teams can trust AI to highlight risks and recommend actions sooner.
Higher win rates, by enabling more nuanced opportunity analysis grounded in real engagement signals.
Operational efficiency gains, reducing time spent reconciling disparate tools and manual data entry.
In an era where data quality directly influences strategic outcomes, People.ai’s MCP integration positions revenue teams to make more informed choices, act faster on insights, and improve the predictability of their revenue engines — a competitive advantage in increasingly complex and AI‑driven markets.
