AI/ML
AI agents will make data access transactions at rates that overwhelm manual compliance checking systems.
The regulatory environment is getting more stringent as GDPR, the EU AI Act, ePrivacy, DORA, and emerging national and state AI regulations all create obligations that cover data, AI models, consent signals, and cross-border data transfers. Failure to comply can bring fines. Manually managing compliance is getting more difficult and AI agents could bring a whole new level of data access transactions to monitor. Veeam’s answer is to use dedicated AI agents to monitor the other AI agents’ (and users and applications) data access activities and enforce compliance
The data protector and cyber-resilience supplier says its three new AI agents continuously prove, with evidence, that governance policies are actually working across complex data and AI ecosystems; something it asserts that traditional privacy programs have struggled to achieve at enterprise scale.
Cassandra Maldini, Head of Product Strategy for Privacy and AI Governance at Veeam, says this: "For ten years, privacy professionals have been quietly admitting they cannot fully prove compliance with their own policies. Now they're being asked to do the same for AI, at a pace no manual program can keep up with. Compliance is no longer a point-in-time exercise. It has to be continuous, evidence-based, and built directly into how organizations operate.”
Veeam has produced a Data and AI Trust Gap report report which shows, it says, that AI agent use is growing faster than the governance structures need to manage it. For example, the report states:
88 percent of the 600 senior execs in various organizations polled say they are already using or piloting AI agents.
Only 28 percent are confident they can detect AI systems operating outside approved parameters.
95 percent say data challenges have already slowed AI progress.
Veeam CEO Aand Eswaren said: “Most organizations don’t have an AI adoption problem; they have an AI trust problem.”
The report reveals a perception gap between the boardroom and the operational teams responsible for delivering AI outcomes. Progress frequently stalls between intent and execution: governance exists inconsistently, data is managed reactively, and ownership is assigned but fragmented. AI failures will not be like traditional system outages. Risk is moving away from traditional system outages toward data-level failures that are harder to detect, explain, and contain. The research warns that machine-speed mistakes can outpace detection, forcing resilience to evolve from broad recovery to precision – restoring only what is impacted, rather than rewinding entire environments.
Only 40 percent of the execs polled are very confident they can isolate and precisely reverse an agentic AI failure. Inside organizations, unauthorized AI use is now mainstream:
95 percent report unauthorized AI use within their organization and 93 percent view it as a significant risk.
25 percent offer approved alternatives, meaning most are trying to suppress demand rather than govern it effectively.
44 percent say increased cyber risk is the top “Shadow AI” risk.
Eswaren said: “The findings here leave no room for doubt. When 95 percent of executives say data challenges are already slowing their AI progress, the bottleneck isn’t the model – it’s trusted, governed, recoverable data. Veeam is building the Data and AI Trust layer to give enterprises the visibility, control and precision recovery needed to scale AI safely and deliver real business value.”
In his view: “The first phase of AI was defined by infrastructure investment, experimentation, and acceleration. The next phase will be defined by trust. With the widespread adoption of autonomous AI agents operating at machine speed, the question transitions from whether you can use AI, to whether you can ensure all your data is secure, governed, compliant and resilient. And should something go wrong, can you recover with precision? That’s how you accelerate safe AI at scale without accelerating reputational and operational risk.”
There are three new compliance-checking agents provided as part of Veeam's DataAI Command Platform:
The Consent Agent is a compliance detection and auto-remediation agent that gives privacy practitioners, legal professionals, and marketing operations like real-time visibility and reduced regulatory risk under GDPR, CCPA, and global laws. It helps ensure that, when a person makes privacy choices, such as opting out of tracking technologies or restricting how their data feeds an AI model, those preferences are respected by every system the data touches, not just the ones where the person clicks an on-screen button.
This is a full-stack consent compliance and remediation agent that manages the end-to-end consent lifecycle, from banner creation and automated testing to continuous monitoring and auto-remediation. It captures user consent signals, including cookie preferences, marketing opt-outs, revoked permissions for AI personalization, and downstream processing restrictions from customers' domains. Then it provides jurisdiction-aware risk scoring, centralized dashboards, and audit-ready evidence. Using Veeam's regulatory database, it helps propagate and enforce them across every system that must honor them, including analytics platforms, AI pipelines, advertising technologies, SaaS applications, and third-party ecosystems.
The Data Subject Request Agent generates and maintains data subject request intake forms configured to your operational and regulatory footprint. Teams can stand up compliant forms in minutes and keep them current as regulations evolve, all without queuing legal review and developer time for every legislative change. This will reduce time to launch a Data Subject Rights (DSR) form by roughly half.
The Assessment Agent analyzes supporting evidence to generate high-quality, tailored assessment responses with a single click, covering Data Protection Impact Assessments (DPIA), EU AI Act conformity assessments, and vendor risk questionnaires.
Veeam’s DataAI Command Platform is a data and AI trust infrastructure that unifies DataAI Security, DataAI Governance, DataAI Compliance, DataAI Privacy, and DataAI Resilience domains, based on a DataAI Command Graph. This has hundreds of connectors across every cloud, SaaS application, and on-premises environment. As part of this, DataAI Privacy is based on a People Data Graph, an identity intelligence graph, to unify structured and unstructured personal data across hybrid multi-cloud environments. This enables real-time, jurisdiction-aware compliance policy enforcement and produces audit-ready evidence of how intent and policy are applied.
The Consent Agent is generally available today as part of the Veeam DataAI Command Platform. The Data Subject Request Agent and Assessment Agent are planned for Q3 2026.
Read more about these new agentic agents on the Veeam blog website and view the full Data and AI Trust Gap report survey results here.