Across hundreds of enterprise deployments, we see the same pattern: IAM programs optimized for what they prevent, not what they cost…in trust, in customers, and in revenue quietly lost to friction, opacity, and AI interactions users don't yet believe in.

This session combines that implementation pattern recognition with three years and 30,000 consumer responses from the Thales Digital Trust Index to show where the gap between assumption and reality is widest and most expensive. The data confirms what we see repeatedly in the field: unexplained friction drives abandonment, unnecessary data collection erodes sharing behavior, and AI-mediated identity flows are outpacing the consumer confidence required to sustain them.

We'll show you what the organizations closing these gaps are doing differently: which onboarding moments they've redesigned first to avoid drop-offs, what adaptive passwordless journeys they’ve implemented to elevate trust and where they've surfaced privacy controls to move retention numbers.

Attendees leave with a prioritized action list, implementation patterns from peers already making these changes, and the consumer evidence to defend every decision internally.

Key Takeaways

• Across enterprise deployments, broken onboarding and unexplained authentication friction is the most recoverable retention leak. Learn which moments to redesign first and how risk-based approaches that make security rationale visible measurably reduce abandonment.
• Organizations that surface consent and preference controls inside the experience, not buried in policy, consistently outperform peers on data-sharing rates and customer lifetime value; learn where in the journey the intervention has the most impact.
• Consumer confidence in AI-mediated identity is lagging deployment speed across the board. Leave with transparency and control benchmarks that separate programs that scale safely from those accumulating trust debt.

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