Are you adopting AI faster than you can secure it?
While the benefits of AI adoption are undeniable, business security leaders everywhere are also raising a timely flag of caution.
The core problem isn’t AI itself. It’s the speed of AI relative to the speed of governance. What’s worrying security leaders is that AI is being deployed at production pace on a security and compliance foundation that barely exists.
The concern isn’t theoretical. The research points to a growing gap between AI adoption and governance.
The data that should raise your eyebrows
In its 2026 Data Trust and Resilience Report, Veeam says that 43% of security leaders say AI adoption is outpacing their ability to secure data and models. A further 42% report limited visibility into which AI tools and models are used across their organisation. And 40% say their policies haven’t been updated for AI-specific risks at all.
AI-generated threats are now emerging as a top concern for security leaders. According to Veeam’s 2026 IT Leaders Survey, 66% of IT leaders now see AI-generated attacks as their most significant data threat, ranking it above ransomware.
Veeam observed: “Digital transformation, cloud adoption, and AI have increased the value of enterprise data and expanded the attack surface around it. Data moves across clouds, applications, APIs, models, and automated systems faster than most organizations can track.”
AI has already rewritten the speed of vulnerability discovery. Security teams still operating at human speed are being outpaced. Not just by attackers, but by their own organisation’s rate of AI deployment.
The over-confidence gap
Many organisations believe they’re prepared, but the evidence suggests otherwise.
One of the more striking findings is the disconnect between confidence and capability: organisations are deeply, measurably overconfident. And that false confidence is a security risk in itself.
According to Veeam, 90% of organisations say they are confident they can recover quickly after a cyber incident, yet only 69% say their recovery targets are actually aligned with what the business needs to keep operating.
Veeam says nearly 3 in 10 organisations experienced a cyber incident in the last 12 months that resulted in data loss, downtime, or business disruption. Those affected reported 42% customer/constituent disruption, 41% financial loss or revenue impact, and 38% extended downtime of critical systems.
But ransomware exposes the real resilience gap, says Veeam. Of those respondents who experienced ransomware, 56% faced encryption or exfiltration, yet only 28% fully recovered all affected data, while 44% recovered less than 75%.
All of which goes to prove that confidence without proof is a liability.
A high confidence score isn’t the same as proven resilience. Organisations that mistake belief for capability aren’t just unprepared. They’re unprepared and don’t know it. That creates risk because weaknesses often remain unaddressed until they’re tested.
Who actually owns AI governance in your organisation?
If ownership is unclear, governance becomes difficult to enforce. Fragmented ownership isn’t just an administrative inconvenience. It’s a measurable predictor of worse security outcomes.
Veeam reports that in organisations that experienced a cybersecurity incident, responsibility for AI governance was spread across multiple leaders. 38% identified the CISO, 27% the CIO, and 17% a cross-functional committee.
This fragmentation creates real resilience risks because AI-related decisions span security, IT operations, data/platform teams, legal/compliance, and the business.
So, who should it belong to?
According to Veeam, detection confidence is 24% higher when CISOs own AI agent risk. That confidence drops 47% when responsibility is shared. In short: shared ownership doesn’t just slow progress. It actively makes outcomes worse.
For example, 65% of CEOs believe they have a complete AI inventory, compared to just 52% of CIOs and 44% of CISOs. And 52% of CEOs believe they actively lead on data, but only 41% of CISOs and 38% of CIOs agree.
Rapid AI adoption, incomplete visibility, and unclear accountability create conditions for failures that are difficult to detect, explain, and contain. And AI governance ownership is more than a title. It’s a set of decisions, controls, escalation paths, and enforcement mechanisms.
Without a named owner with actual authority, governance is theatre.
Time to get tough: policy isn’t enough
For most organisations, there’s a very real gap between policy and controls. And it’s not enough to simply hope that the gap is effectively bridged. The reality is that enforcement is the only way to stop your organisation being exposed.
Many organisations recognise AI-related risks, but the data shows that policies alone aren’t enough. They need to work hand in hand with technical controls that reduce data exposure and enforce how your data can be used.
The policy gap is significant. Veeam reports that 40% of organisations have not updated their policies for AI-specific risks at all.
In its Data Trust and Resilience Report 2026, Veeam found 25% of its respondents cited unauthorised shadow AI tools as a primary concern. Its Data & AI Trust Gap Report 2026 puts this into even sharper relief: 95% of organisations know employees are using unapproved AI tools, and 93% recognise shadow AI as a problem, however, only 25% provide all employees with access to approved alternatives. So, most organisations are trying to suppress demand rather than govern it effectively.
From the same research, Veeam says that 47% of organisations identify maintaining audit trails for AI decisions as their top compliance concern, yet only 28% of those surveyed are confident they could detect agents operating outside approved parameters. Having a compliance requirement and having the controls to meet it are two very different things.
In practice, policies describe what should happen, while controls enforce what can happen. And monitoring confirms what did happen. Most organisations only have the first. The other two are where real protection lives.
Some organisations are getting it right. What are they doing differently?
The top-performing 7% of organisations, says Veeam, do something specific that separates them from the rest: They build strong foundations.
Veeam’s research identifies four capabilities linked to better outcomes:
- Visibility into data and AI risk
- Enforced controls not policy-only governance
- Proven recovery (tested and validated)
- Executive alignment on ownership and reporting
Stronger recovery organisations, says Veeam, share all four capabilities, and the data shows that measurement and reporting correlate directly with better outcomes.
Those making the most AI progress aren’t necessarily the ones moving fastest, though. Instead, those seeing the biggest results are the ones building the right foundations first. They’re auditing their data, closing visibility gaps, assigning ownership, and building governance that can withstand operational and regulatory pressure.
According to Veeam’s Data & AI Trust Gap Report 2026, among organisations classified as fully AI-ready (representing just 7% of those surveyed), 97% report measurable, formally quantified business benefits from data and AI investments, compared with just 48% overall.
The top performers aren’t necessarily the biggest or the best-funded. They’re the ones who treated trust as a prerequisite for scale, not an afterthought. Visibility, enforcement, tested recovery, and clear ownership appear consistently among higher-performing organisations.
What all this means for your business
The research makes clear that the organisations closing the AI-security gap are generating better outcomes. As for the ones ignoring it? They are absorbing real, measurable costs.
In Veeam’s Data & AI Trust Gap Report 2026, 48% of executives say trusted, secure, and compliant data could unlock more than 25% revenue growth. Yet most organisations are not positioned to capture it. Why not? Because they’re still missing the foundation of trusted data, enforced governance, and precision recovery.
So, what next?
Veeam says 54% of respondents plan a moderate or significant increase in their data protection and resilience budget in 2026. 45% chose strengthening cybersecurity as the single “must-win” IT initiative, ahead of every other operational priority. Leaders are clearly directing budget where the risk is most acute.
As AI becomes more embedded in business processes, governance and resilience become business issues rather than solely technical concerns. The question for every business leader isn’t whether to secure your AI.
It’s whether you can afford not to.
