AI Security Audit

We examine exactly what data is being shared with AI systems across your organisation—whether through sanctioned enterprise deployments or informal staff usage of public AI tools. This covers personal data, customer records, financial information, intellectual property, and commercially sensitive material. We map data flows into and out of every AI system, assess data residency and storage locations, evaluate whether data is being used for third-party model training, and identify any processing activities that fall outside your existing GDPR lawful basis. The result is a clear picture of your data exposure and specific recommendations to close every gap.

One of the most significant risks businesses face is AI tools being adopted by staff without IT knowledge or approval—commonly known as shadow AI. We conduct a thorough discovery exercise to identify every AI tool, plugin, browser extension, and third-party service being used across your organisation, whether sanctioned or not. This includes free-tier AI assistants, AI-powered browser extensions, AI features embedded in existing SaaS applications, and any integrations staff have configured independently. The resulting inventory gives your leadership team complete visibility of your actual AI footprint, enabling informed decisions about which tools to approve, restrict, or replace with governed alternatives.

We review who has access to your AI systems, what permissions they hold, and whether the principle of least privilege is applied consistently. This covers authentication mechanisms, role-based access controls, API key management, service account configurations, and administrative access to AI platforms and their underlying data sources. We assess whether access is appropriately segmented between development, testing, and production environments, and whether adequate logging and monitoring exists to detect unauthorised or anomalous usage. Weak access controls around AI systems are one of the most common and exploitable vulnerabilities we encounter.

We assess your AI usage against the regulatory frameworks that apply to your organisation—including UK GDPR requirements for automated decision-making and data processing, the emerging EU AI Act obligations around transparency, risk classification, and human oversight, ISO 27001 information security management controls, and Cyber Essentials certification standards. For regulated industries such as healthcare, financial services, and social care, we also evaluate alignment with sector-specific requirements including CQC standards, FCA guidance, and NHS Data Security and Protection Toolkit obligations. Every compliance gap is documented with a clear remediation recommendation and priority rating.

Most organisations consume AI through third-party platforms and SaaS vendors rather than building models in-house. We evaluate the security posture and data practices of every AI vendor in your supply chain—reviewing their terms of service, data processing agreements, data residency commitments, training data usage policies, security certifications, and incident response track record. We identify vendors that present unacceptable risk to your organisation and recommend governed alternatives where necessary. This assessment is critical for understanding your true exposure, as a single poorly vetted AI vendor can undermine your entire data protection framework.

We review your existing AI governance framework—or identify the absence of one—assessing whether you have adequate acceptable use policies, AI procurement procedures, output validation processes, bias monitoring, escalation procedures, and incident response plans specifically covering AI-related events. We evaluate whether governance responsibilities are clearly assigned, whether your board has appropriate oversight of AI risk, and whether your existing information security and data protection policies adequately address AI-specific scenarios. Where gaps exist, we provide ready-to-adopt policy templates and governance framework recommendations aligned to industry best practice.

AI systems can produce inaccurate, biased, or misleading outputs—and if these are published externally, used for business decisions, or shared with customers without human validation, the consequences can be severe. We assess whether appropriate output review processes exist, whether staff understand the limitations of AI-generated content, whether automated outputs are clearly labelled, and whether adequate quality controls are in place for customer-facing AI interactions. We also evaluate prompt engineering practices and system configurations to ensure AI models are producing reliable, consistent results appropriate for their intended use cases.

Your people are the frontline of AI security. We assess the level of AI awareness across your workforce—whether staff understand what constitutes safe and unsafe AI usage, whether they know which tools are approved, whether they recognise the risks of entering sensitive data into public AI platforms, and whether they can identify AI-generated content that requires human validation before use. We evaluate existing training provision, identify knowledge gaps by department and role, and recommend a structured AI awareness and training programme that equips your team to use AI tools productively within clearly defined, secure boundaries.