Usercentrics is making a decisive move to connect privacy compliance with the fast-expanding world of AI agents. The Privacy-Led Marketing company has acquired MCP Manager, a next-generation governance platform for the Model Context Protocol (MCP), marking what it says is the first time a global data privacy leader has extended consent and data guardrails directly into AI-driven workflows.

The deal positions Usercentrics at the intersection of privacy, marketing, and AI governance—an increasingly crowded but still loosely defined space as enterprises rush to deploy AI while regulators catch up.

Why AI Consent Is Becoming a Board-Level Issue

As AI agents take on a more active role in personalization, customer engagement, and internal decision-making, they’re also gaining deeper access to sensitive systems like CRMs, analytics platforms, and customer data stores. That shift creates a problem: traditional consent frameworks were built for data collection, not real-time, model-driven interactions.

Usercentrics argues that this gap is quickly becoming untenable—especially in Europe. With the EU AI Act moving from phased rollout to enforcement this year, organizations can no longer afford to treat AI governance as a future concern.

By acquiring MCP Manager, Usercentrics is aiming to apply the same rigor used in consent management to how AI systems access, process, and act on data. The company frames this not just as compliance, but as a competitive advantage in an era where trust increasingly influences brand choice.

What MCP Manager Adds to the Stack

MCP, or Model Context Protocol, has rapidly emerged as a standard for connecting AI models to enterprise systems. What it doesn’t provide on its own is governance—specifically, visibility and control over whether AI agents are accessing data in ways that align with user consent and regulatory requirements.

MCP Manager fills that gap by acting as a policy-enforcement layer. It gives organizations a centralized control plane to monitor, explain, and enforce how AI systems use data across workflows. That includes scenarios where AI agents might otherwise pull CRM data without consent checks or produce decisions that are difficult to justify to regulators.

In practical terms, the technology enables companies to answer uncomfortable but increasingly common questions: Why did the AI access this data? Was consent in place? Can we prove it?

Toward a Unified Privacy-Led Marketing Suite

Post-acquisition, Usercentrics plans to integrate MCP Manager into a unified Privacy-Led Marketing Suite. The goal is a single platform that manages consent, preferences, and data governance across websites, apps, internal systems, and consumer-facing AI agents.

This matters because AI is no longer confined to the back office. Chatbots, recommendation engines, and AI-driven personalization tools now sit directly in front of customers, shaping experiences in real time. Extending consent into these interactions brings AI closer to the same compliance standards already expected for cookies, tracking, and data collection.

According to Usercentrics CEO Donna Dror, this shift reflects a broader reality: AI governance is no longer optional. Companies that delay risk not only regulatory exposure, but erosion of customer trust at a time when transparency is becoming a differentiator.

Governance Where AI Meets Data

One of the more strategic aspects of the acquisition is its focus on enforcement at the moment AI interacts with data—not after the fact. By governing access at the MCP layer, Usercentrics aims to prevent violations before they happen, rather than relying on audits or post-hoc explanations.

Michael Yaroshefsky, founder of MCP Manager, who joins Usercentrics as VP of Artificial Intelligence within its Chief AI Office, describes MCP as the natural enforcement point for consent and compliance. As regulations take effect, he argues, governed AI infrastructure will shift from being a differentiator to a baseline expectation.

This reflects a growing consensus in the market: explainability, consent, and auditability will become core requirements for enterprise AI, not optional features.

Market Implications

The acquisition underscores how quickly privacy vendors are repositioning themselves for the AI era. While many AI governance tools focus on model risk or bias, Usercentrics is betting that consent-aware AI will be the next frontier—particularly for marketing, personalization, and customer-facing use cases.

It also raises the bar for competitors in privacy tech, many of whom still treat AI as an adjacent concern rather than a first-class citizen in consent frameworks. As AI agents proliferate, platforms that can bridge marketing performance, compliance, and AI governance may find themselves with a durable advantage.

For now, Usercentrics is signaling that privacy doesn’t stop at data collection—and that in the age of AI, consent must travel with the data wherever models go.

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