Imposter AI is more than 14 percentage points higher than the tenth-ranked procedure by weighted ASR.

In Europe, 59% of data policy violations across AI and personal cloud applications involve regulated data.

In Europe, 13% of data policy violations across AI and personal cloud applications involved intellectual property.

The share of users who switch between personal and enterprise accounts grew from 7% to 15% in Europe.

64% of users are using AI applications directly, while an even larger share (95%) are using applications that incorporate AI-powered features indirectly in Europe.

83.2% of critical vulnerabilities either lacked scanner coverage entirely or had exploits appear before detection ships.

There is a 51-point gap between organizations' intent to secure AI in the cloud and their capability to enforce that security

78% of organizations have either experienced an AI-related security incident or cannot determine whether they have

Anthropic Claude-family single-turn ASR ranges from 2.19% to 3.64%, and multi-turn ASR ranges from 11.16% to 16.20%.

Grok 4.1 Fast in its non-reasoning configuration records a multi-turn ASR of 88.30%.

In an earlier open-weight evaluation, multi-turn ASR reached 92.78% against Mistral Large-2.

Imposter AI procedures produce a 37.50% weighted single-turn ASR, Soft Paraphrase produces 29.21%, and System Prompts produce 27.69%.

About 99% of organizations in Europe use AI.

In Europe, 15% of data policy violations across AI and personal cloud applications involved source code.

In Europe, 12% of data policy violations across AI and personal cloud applications involved passwords and API keys.

In Europe, Individual user AI adoption increased from 35% to 65%.

26% of organizations report having the architecture to enforce their AI-related cloud security strategy

24% of organizations can fully inspect AI traffic without impacting performance

16% of organizations enforce AI access controls consistently across the environment

86% of leaders rate unified security management across cloud, datacenter, and edge as critical for AI workloads