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AI Platform Strategy · OneTrust

Transforming OneTrust into
an AI-first platform.

Leading UX strategy for OneTrust's transition from a monolithic governance suite into a connected, AI-first enterprise platform — making AI visible, understandable, governable, and extensible across the product ecosystem.

Company
OneTrust
Role
Principal UX Designer
Scope
Platform strategy · AI UX · MCP
Status
Currently shipping
AI/ML UXPlatform DesignDesign SystemsEnterprise0→1MCPDeveloper Experience
AI in your workflow
Risk summarization
Active
Vendor AI scoring
Review required
Consent analysis
Not enabled
MCP agent access
Agent credential
risk-copilot-prod
Scope
read:assessments
Audit
Enabled
Least-privilege · User-context bound

Overview

OneTrust is a large enterprise governance platform with a broad legacy product ecosystem spanning privacy, risk, compliance, third-party management, and AI governance. I led the UX strategy for transforming that experience from a monolithic product suite into a more connected, AI-first platform.

The work centered on two distinct customer paths — those who expect AI to appear naturally inside the product through guided, trustworthy workflows, and those who are building their own copilots, agents, and automation layers requiring governed platform access.

🎯

The goal was to make AI visible, understandable, governable, and extensible across the platform — not to ship a set of features, but to define how AI should show up across an entire product ecosystem.

The problem

OneTrust had powerful AI capabilities, but they were often hidden behind settings, packaging, feature toggles, and disconnected enablement paths. Customers did not always know what AI was available, whether they were eligible to use it, or how to activate it.

At the same time, advanced enterprise customers were beginning to build their own AI agents and needed a secure way to connect those agents to OneTrust data and workflows. The challenge was bigger than designing a set of AI features — it required defining how AI should show up across the entire product ecosystem.

My role

As OneTrust's senior-most UX designer, I led the experience strategy across AI platform transformation — including in-product AI discovery, guided enablement, MCP credentialing, developer experience, and governance patterns.

I worked across design, product, engineering, GTM, and leadership to translate a complex technical vision into a clear customer experience strategy.

Strategy

I framed the experience around two connected modes of AI adoption.

Path 1 — Guided AI experiences

For AI-expectant customers, the experience needed to surface AI capabilities directly inside existing workflows. The shift was from hiding AI until it was purchased and enabled, to making AI visible, explainable, and actionable.

Path 2 — MCP platform access

For AI-advanced customers building their own copilots and agents, OneTrust needed to support external agents through a governed MCP platform — letting customers safely connect their own AI ecosystems without bespoke integrations or overly broad API credentials.

💡

The two paths were not separate products. They were two points on the same adoption curve — and the experience strategy needed to connect them into one coherent platform narrative.

Design principles

Make AI visible before activation
Customers should be able to see where AI can help, even if it is not yet enabled.
Explain the current state
Clearly distinguish between disabled, unavailable, gated, permission-limited, and governance-required states.
Treat enablement as a governance journey
Enterprise AI activation often requires legal, privacy, security, and risk review. The experience supports that reality.
Make advanced access governable by design
MCP experiences balance developer flexibility with security, permissioning, and auditability.

Key outcomes

This work helped define a platform strategy for how OneTrust can position itself as a credible AI-first governance platform.

🔒

Screens and full case study artifacts are in progress — including the AI-first platform model, customer maturity framework, AI discovery patterns, MCP credential flows, and governance-led enablement journey. Available on request.

Case study artifacts

When complete, the full case study will include:

Screens from Figma will be added here. Reach out if you'd like to discuss this work directly.

More work