An independent global study finds that organizations meeting verified trust criteria achieve 51% higher transaction conversion and 43% lower fraud losses.

Ping Identity, a leader in securing digital identities for the world’s largest enterprises, released independent research showing that organizations that have operationalized continuous, contextual identity verification materially outperform peers across revenue growth, fraud reduction, compliance readiness, and workforce productivity as AI-driven interactions scale.

The white paper, conducted by International Data Corporation (IDC) and sponsored by Ping Identity, highlights a clear maturity gap between perception and execution, while more than half of organizations believe they lead in digital trust, only a small fraction has operationalized continuous, contextual identity verification at scale.

Based on a global survey of 794 organizations, IDC found that enterprises meeting verified trust criteria delivered statistically significant performance advantages across core enterprise metrics:

• Customer registration conversion: 51% higher
• Compliance readiness: 44% stronger
• Fraud losses: 43% lower
• Workforce onboarding time: 47% faster

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What is verified trust, and why is it important? 
IDC defines verified trust as “a continuous assurance that every digital interaction, whether human or machine/AI agent, is tied to an independently verified identity and remains trusted over time.” It enforces continuous, contextual verification for every identity-sensitive event using signals such as zero-knowledge biometrics with liveness detection, device posture, behavioral intelligence, and AI-aware risk analysis.

According to the white paper, this model “transforms identity from a static gate into a dynamic trust fabric.” This shift moves identity from a perimeter authentication event to a runtime control plane governing every authorization decision.

“In today’s threat landscape, identity can no longer be treated as a single authentication event. In an AI-mediated enterprise, every authorization decision must be continuously verified, contextualized, and governed,” said Peter Barker, Chief Product Officer at Ping Identity. “This research confirms that organizations embracing continuous, contextual verification reduce risk while unlocking measurable business value. Verified trust is how enterprises close the gap between confidence and control in an AI-driven world.”

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Closing the Verified Trust Gap
Despite the measurable gains, IDC found a significant maturity gap between perception and reality. The study highlights several critical divides between leaders and early-stage adopters:

• Perception vs. reality: 51% of organizations believe they are ahead of peers in establishing trusted digital identity, yet only 9% meet IDC’s criteria for verified trust leaders.
• Verification coverage: 69% of leaders verify 75-100% of trust flows, compared to 16-19% of early-stage adopters.
• Adoption at scale: 94% of leaders operate at enterprise scale across trust flows, while early-stage organizations remain confined to pilot deployments.
• Passwordless maturity: Leaders embrace biometrics, passkeys, and digital wallets at 80–83%, while starters hover below 30%.

“Verified trust is no longer a design choice – it’s the prerequisite for operating at scale in AI driven environments,” said Emanuel Figueroa, Senior Research Analyst at IDC. “As AI increases autonomy and complexity, identity becomes the mechanism for control, accountability, and confidence. Organizations that establish this foundation early will move faster with less risk; those that don’t will accumulate cost, friction, and regulatory exposure over time.”

As enterprises accelerate AI adoption, verified trust across human and AI identities is foundational to maintaining control and accountability across every interaction. Ping Identity enables enterprises to operationalize verified trust across workforce, customer, partner, and AI identities—establishing a unified trust control plane that adapts in real time as risk, behavior, and machine interactions evolve.