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The current enterprise AI conversation is, frankly, unscientific. Leadership demands acceleration, while security mandates control. The decisions being made across the organization are based on conjecture, vendor-supplied narratives, and industry reports with an immediate expiration date.
This is not a strategy; it is a profound operational risk.
At Netskope, our vantage point is unique and empirically grounded. Our platform provides deep, continuous inspection of traffic across thousands of global enterprises—capturing every single prompt, every shadow AI application access, and every upload of sensitive data into a generative AI service. We do not rely on anecdotal evidence or self-reported surveys to understand AI adoption. We observe it directly. And this real-time, behavioral data has the power to fundamentally reshape how security leaders must approach and mitigate the risks of enterprise AI. That’s why we built the Netskope AI Index.
What is the Netskope AI Index?
The Netskope AI Index provides organizations with a clear snapshot of how enterprises around the world are actually adopting and using AI. It is designed to help security and IT leaders understand the trends their peers are experiencing, and signpost the risks they may need to account for in their own AI strategies. The AI Index is built from aggregated and anonymized telemetry across the Netskope platform, creating a dynamic, regularly updated benchmark of real-world AI usage. It reflects observed enterprise activity across industries, regions, and company sizes, offering a grounded view of how AI adoption and risk are evolving in practice.
Think of it as your AI reality check; a clear window into what enterprise AI adoption actually looks like right now, not six months ago when some quarterly report was being written.
The number of enterprise AI users more than doubled year-over-year, with 44% of employees now engaging with at least one AI application each week compared to 19% one year ago.*
The shadow AI problem is bigger than you think
So what does the Index tell us? Here’s the finding that tends to surprise people: when we look at the AI tools employees are actively using, the officially managed ones are almost never the majority. How many AI apps do you think your employees are accessing per week? The average enterprise sees users accessing 60—already up from 35 a year ago and still growing.
Yes, Microsoft Copilot is widely deployed. Yes, Google Gemini is gaining enterprise share. But right alongside those approved tools, employees are actively routing work (and using sensitive data) through ChatGPT personal accounts, unmanaged Claude instances, experimental AI coding tools, and dozens of purpose-built AI apps that most security teams have never audited (if they have even heard of them).
The Netskope AI Index tracks all of this data with regularly updated snapshots. And the numbers are stark.
12% of enterprise users are bypassing approved tools, opting instead to use personal AI apps and instances weekly*
It’s worth considering that shadow AI isn’t a sign that employees are simply being reckless. It’s a sign that they’re trying to get their jobs done, and the official stack isn’t moving fast enough to support them. It is true, however, that from a security posture standpoint, every unmanaged AI interaction is a potential data exposure event: a moment where intellectual property, customer data, or regulated information can exit the organization with.
That’s not a hypothetical risk. Our telemetry shows it happening, at scale, every day.
Weekly and monthly trends: the signal in the noise
One of the most powerful features of the AI Index is temporal intelligence: the ability to see how AI adoption is moving right now, not just where it sits today.
And we’re seeing a consistent pattern. Enterprise AI usage is not plateauing. The curve is still climbing, but the shape of that curve is already changing. Early adoption was dominated by productivity and writing tools (for example, employees experimenting with ChatGPT when drafting emails and summaries). The current wave of tools is different. They are functional, specialized, and far more integrated into core workflows.
We’re tracking the rise of AI coding assistants, AI-powered data analysis tools, and vertical-specific AI applications that touch regulated data far more directly than the general-purpose tools that preceded them. This is the shift that security teams need to get ahead of because the compliance and data governance stakes have fundamentally changed.
The question is no longer “Are our employees using AI?” It’s “Which AI tools are accessing our most sensitive systems?”*
Know where you stand: benchmarking against your peers
The capability that resonates with most security leaders we talk to is the ability to compare their organization’s AI posture against their industry peers.
Are you ahead of the curve in AI adoption, or falling behind your sector? Are your approved AI tools aligned with what comparable organizations are standardizing on? Is your rate of shadow AI usage above or below the industry average and what does that gap tell you about your employee enablement strategy?
These aren’t abstract questions. The Netskope AI Index gives you a direct line to the answers, segmented by vertical, by region, and by company size. A financial services CISO can see exactly how their organization’s AI traffic compares to other firms in the sector. A healthcare security team can benchmark their managed vs. unmanaged AI ratio against health sector peers. A global enterprise can cross-check their regional adoption patterns to determine whether the differences between their European usage compared to their US headquarters usage are to be expected, aligning with trends.
This kind of contextual benchmarking is what separates informed, proactive security strategy from reactive firefighting.
Why this matters now
The window for getting AI governance right is narrowing.
Regulatory frameworks around AI data handling are advancing in the EU, in several US states, and across APAC. Boards are asking harder questions about AI risk. Cyber insurance underwriters are beginning to factor AI usage patterns into policy assessments. And internally, the longer shadow AI operates unchecked, the harder it becomes to govern. Habits harden into workflows. Workflows harden into dependencies. Dependencies become very difficult to unwind without disrupting the business.
Research by Cybersecurity Insiders this year found that 38% of organizations wish their governance had preceded adoption of AI at scale, and 25% wish they had invested in visibility controls sooner. The security leaders who are winning this moment are not the ones saying no to AI. They’re the ones who got visibility first, established governance frameworks second, and are now enabling the business to move fast on a foundation they can actually defend.
The Netskope AI Index exists to give every security leader that same starting point: accurate, current, peer-contextualized intelligence about what’s actually happening in the enterprise AI landscape. We built the Netskope AI Index because the conversation about enterprise AI deserves accurate data. Not estimates. Not vendor narratives. Observed reality, continually updated, and sourced via the largest security cloud in the world.
Whether you’re trying to build a board presentation, construct a defensible AI governance policy, or simply answer the question your CEO is going to ask you next week, the AI Index is where that conversation should start.
See where your organization stands. Explore the Netskope AI Index and get real-time intelligence on the trends shaping enterprise AI adoption.
* Netskope AI Index, Feb 23, 2026
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