Organizations that treat consent as an ongoing data relationship—not a one-time transaction—are better positioned to build trust, improve data quality, and scale AI responsibly

CAMBRIDGE, Mass., April 15, 2026 -- A new report by MIT Technology Review Insights finds that organizations must rethink how they approach data consent, shifting from one-time compliance interactions to ongoing, trust-based relationships with users to succeed in the AI era.

Insights

The report, "Building trust in the AI era with privacy-led UX", is produced in partnership with Usercentrics, a global leader in data privacy technology, and is based on in-depth interviews with industry experts and practitioners whose work sits at the intersection of privacy technology, digital marketing, consumer analytics, and trust. Interviewees included experts from organizations such as Forrester, DWC Consult, MeasureU, and Usercentrics.

Adelina Peltea, the chief marketing officer at Usercentrics explains, "The opportunity is significant. Privacy-led UX doesn't just reduce risk, it builds the kind of trust that compounds. Organizations that get consent right unlock higher opt-in rates, better quality first-party data, and the signal fidelity that makes personalization and AI outputs actually work. In the AI era, trust is not a soft metric. It is the foundation everything else is built on."

The key findings from the report are as follows:

  • Privacy is evolving from a one-time consent transaction into an ongoing data relationship. Rather than asking users for broad permissions up front, leading organizations are introducing data-sharing decisions gradually, matching the depth of the ask to the stage of the customer relationship.
  • Privacy-led UX is a prerequisite for AI growth. The consumer data that organizations gather is rapidly becoming a core foundation upon which AI-powered personalization is built. Organizations that establish clear, enforceable privacy and data transparency policies now are better positioned to deploy AI responsibly and at scale in the future.
  • Agentic AI introduces new levels of both complexity and opportunity. As AI systems begin acting on users' behalf, the traditional consent moment may never occur. Governing agent-generated data flows requires privacy infrastructure that goes well beyond the cookie banner.
  • Realizing the advantages of privacy-led UX requires cross-functional collaboration and clear leadership. Privacy-led UX touches marketing, product, legal, and data teams, but someone must own the strategy and weave the threads together.
  • A practical framework, called the TRUST framework, can support businesses in getting it right. Organizations must define their data collection and usage strategies and ensure their UX incorporates data consent, including a focus on banner design.

"Organizations can no longer treat privacy as a compliance checkpoint at the edge of the user experience," says Laurel Ruma, global director of custom content for MIT Technology Review Insights. "Our research shows that privacy-led UX is becoming foundational to how companies build trust, collect meaningful data, and ultimately scale AI systems responsibly."

To download the report, click here.

For more information please contact:

Natasha Conteh

Head of Communications

MIT Technology Review Insights

natasha.conteh@technologyreview.com

About MIT Technology Review Insights

MIT Technology Review Insights is the custom publishing division of MIT Technology Review, the world's longest-running technology magazine, backed by the world's foremost technology institution—producing live events and research on the leading technology and business challenges of the day. Insights conducts qualitative and quantitative research and analysis in the U.S. and abroad and publishes a wide variety of content, including articles, reports, infographics, videos, and podcasts.

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