C-Suite Outranks Junior Staff on Shadow AI Use, Survey Finds

A TrustedTech survey of 2,001 UK and US employees, published July 1, 2026, found 67% of senior decision-makers use unauthorized AI tools, compared with 31% of the staff they manage. Among C-level executives, the share admitting to shadow AI use climbs to nearly 73%; among entry-level staff, it sits at 36%. The exposure concentrates at the top of the org chart.

“The first thing CIOs need to accept is that this isn’t primarily a rank-and-file problem,” said Andy Nolan, vice president for technology at TrustedTech. “It’s a leadership problem.” His warning was direct: if governance concentrates on monitoring junior staff, the larger exposure at the top goes unaddressed.

The C-Suite Outranks the Junior Desk

The default shadow AI story points at the rank-and-file employee pasting company data into a personal ChatGPT account. The TrustedTech data says otherwise. 67% of senior decision-makers admitted to using AI tools their organization had not sanctioned, against 31% of the staff they manage. Among C-level executives, the share climbs to nearly 73%; among entry-level staff, it sits at 36%.

That inversion lands hard on existing enterprise governance. Most CIO programs monitor traffic, browser logs, and DLP signals from the bottom up: junior laptops first, exec laptops last. TrustedTech’s March 2026 polling puts the heaviest exposure one layer up, on the desks of the people approving the very policies meant to manage it. “If a CIO’s governance strategy is built around monitoring junior staff,” Nolan said, “they’re pointing the telescope in the wrong direction.”

The senior decision-maker row and the staff-they-manage row are the central finding of the survey. The same gap, drawn between the C-suite at nearly 73% and the entry-level row at 36%, is the operational problem governance must now solve. The figure with the cleanest reading is the gap itself: the heaviest shadow AI population sits one layer up from where most enterprise tooling looks.

Why Senior Leaders Bypass Approved AI Tools

Tool inadequacy was not the main driver. Only 28% of senior decision-makers said they found unapproved tools more efficient than the approved ones. 29% said limitations in access were a problem. The bigger driver was fear of being watched: 56% of decisionmakers said they were concerned about shadow AI use in their organization, and 42% said they believed their employers were monitoring their AI use. Among the staff those executives manage, concern about shadow AI sat at 31% and concern about monitoring at 23%.

The worries the executives named when asked why they used unapproved tools anyway fell along three lines:

• 24% were worried that AI monitoring could hurt their careers.
• 23% were worried AI monitoring would raise doubts about their abilities.
• 23% were worried about being monitored by their manager.

The gap, on this reading, is not hypocrisy. It is a symptom of executives routing around governance when the approved tooling does not yet do what they need. The pay-off argument (faster work) and the policy argument (rules exist for a reason) collapse into one when a senior leader believes every prompt is being logged and counted against them. The default shadow AI story pointed at rogue junior staff typing in personal ChatGPT accounts at lunch; the new figure lives one row up in the org chart, on the people approving the very policies meant to manage the rest of the firm.

Confidence Concentrates at the Top

The leadership-heavy use of shadow AI also exposes a confidence gap. Nearly 80% of senior decision-makers said they feel confident using AI, while 43% of their employees said the same. Among C-suite executives, 92% reported feeling confident; among entry-level staff, only 41% did.

That mismatch means the people setting AI policy and deploying AI tooling are not the people using the tools day to day. Only 23% of employees said their AI skills came from employer training. Almost 55% of those below decision-maker level said they were self-taught or had learned from online resources such as blogs or YouTube. The result is an enterprise-wide skill and tooling shortfall on the staff side, set by a leadership side that feels ready. A similar C-suite-versus-worker gap on AI readiness shows up in the Accenture Pulse of Change 2026 take on AI management, with executives reporting readiness levels well above the workers they cover.

Where Awareness Is Highest, Trust Is Lowest

The data shows that concern about shadow AI use does not track with who is doing it most. 56% of senior decision-makers said they were worried about shadow AI in their organization, against 31% of the staff they manage. 42% of decision-makers believed their employers were monitoring their AI use, versus 23% of employees.

That is the trust problem the data names. The executives most likely to use unauthorized AI tools are also the most likely to know the company frowns on them, and the most likely to assume the company can already see what they do. The belief that every prompt is being logged and graded undermines the policy backdrop. Surveillance meant to deter shadow AI use at the top ends up driving it further underground, into tools with no governance at all.

Nolan framed the dynamic as governance racing against executive pressure to move fast. The result, in his reading, is that approved tools get treated as optional, while senior leaders route to whatever AI does the actual job. The trust gap and the routing-around gap are the same gap, measured from two angles.

Who Was Polled, and What 2025 Showed

The figures came out of a Censuswide poll conducted in March 2026 across 2,001 UK and US employees in junior and senior roles. Andy Nolan, vice president for technology at TrustedTech, was the lead commentator on the data in the July 1, 2026 write-up of the survey.

Shadow AI is the use of AI tools and applications by employees without formal approval or governance from the organization’s IT or compliance function. Generative AI assistants, copilots, and AI agents used outside a company’s vetted stack all count. The risk runs past productivity losses; corporate data shared with outside systems can end up exposed, as detailed in how shadow AI exposes sensitive data to outside systems.

A year earlier, Varonis’s 2025 State of Data Security Report had put unsanctioned-app use at 98% across shadow AI and shadow IT combined. That figure folded AI and conventional unsanctioned software into one number and pointed at employees as the population. The March 2026 read breaks that aggregate apart. It separates shadow AI from shadow IT and surfaces a different heavy-user group.

On the cost side, organizations funding AI rollouts are under pressure to track hidden workforce costs that can erode ROI. Gartner’s three hidden AI workforce costs for HR flags what CHROs can take now; the figure from the survey sits next to it. Only 23% of employees said their AI skills came from employer training, the lowest figure among the categories the survey asked about.

What a Telescope Turned the Other Way Looks Like

The practical effect of the data is to shift shadow AI governance upward. CIOs who only monitor traffic, browser logs, and DLP signals from the bottom up keep missing the heaviest exposure, on the laptops and credentials of the executives who approve the policies. The fix is not to monitor executives more; it is to give executives an approved tool stack that does the job and a governance frame that does not treat them as the adversary.

Executives are under pressure to move fast, and when the approved tools don’t exist yet or don’t do what they need, they route around governance. That’s a completely human response, but it’s also exactly how you end up with sensitive data sitting in tools IT has no visibility into.

Nolan framed that as the central governance challenge. The TrustedTech data does not say executives are wrong to use the tools they want. It says the chain of accountability is shortest at the top. A board that funds an AI rollout also owns the governance around it, by the same rules that govern every other risk in the organization. Read against Varonis’s earlier 98% figure, the senior-decision-maker tier now looks like the layer of the enterprise where shadow AI is most concentrated, and least supervised.

Frequently Asked Questions

What is shadow AI?

Shadow AI is the use of artificial intelligence tools and applications by employees without formal approval or governance from their organization’s IT or compliance function. It typically covers generative AI assistants, copilots, and AI agents used outside a company’s vetted stack.

Who uses unauthorized AI tools most?

According to TrustedTech’s March 2026 survey, senior decision-makers were the heaviest reported users of unauthorized AI. 67% admitted to using shadow AI tools, and the share rose to nearly 73% among C-level executives, against 31% of the staff they manage.

Why do executives use unapproved AI tools?

Worries about surveillance ran deeper than tool-quality concerns. Only 28% said unapproved tools were more efficient than approved tools, while 24% were worried about career impact from monitoring and 23% worried it would raise doubts about their abilities.

How was the TrustedTech shadow AI survey conducted?

TrustedTech ran the survey in March 2026 through Censuswide, polling 2,001 UK and US employees in junior and senior roles across organizations. Andy Nolan, vice president for technology at TrustedTech, was the lead commentator on the data.