Governance emerges as a bottleneck as UAE firms scale AI for security
Organisations across the UAE and the wider Middle East are increasing their use of artificial intelligence in cybersecurity, but a new report from KPMG warns that many AI projects fail to generate measurable value because governance, oversight and operational discipline are lagging behind deployment.
Published in May 2026, KPMG’s report, The New Cyber Battleground, draws on recent regional activity to argue that while AI is becoming a frontline tool for threat detection, response and automation, the business case for many initiatives remains unproven. The consultancy highlights a striking global figure: more than 95% of AI use cases do not deliver measurable business or security outcomes, a gap it links to weak problem definition, immature operating models and insufficient validation.
For UAE organisations, the report underscores a transition from experimentation to scaled deployment, but warns that scale without governance can increase risk rather than reduce it. Cyber threats in the region are increasingly identity-driven, the report notes, with social engineering and account compromise often acting as the initial vector. In this context, AI can both help and complicate detection: while machine learning models can identify subtle patterns that human analysts miss, they can also amplify mistakes if outputs are accepted without verification.
Operational gaps: validation, accountability and lifecycle security
KPMG highlights three recurring weaknesses that limit AI’s effectiveness in security programmes. First, organisations often lack clear problem statements that map AI capabilities to measurable outcomes. Second, operating models and processes have not evolved to embed AI into day-to-day security workflows. Third, governance and validation practices do not consistently cover the AI lifecycle, from data curation and model training to ongoing monitoring and incident response.
The report also cites survey data showing that more than half of professionals have experienced mistakes linked to AI in their work, while two-thirds sometimes rely on AI outputs without validating accuracy. These behaviours, the authors warn, create operational blind spots at a time when adversaries are improving their own use of automation and generative tools.
Trevor Niblock, Partner, Digital Trust, KPMG Middle East, summarised the challenge for UAE organisations: “The UAE has demonstrated strong leadership in digital transformation and AI integration. In a more complex and fast-moving threat environment, organisations need to shift focus from speed of deployment to quality of implementation. Embedding accountability, validation, and lifecycle security into AI systems will be critical to strengthening resilience and maintaining trust as these technologies scale.”
Why this matters to boards, CISOs and regulators
The findings carry practical implications for several stakeholder groups. For boards, they elevate AI governance from an IT or security topic to a strategic risk issue: oversight structures, risk appetite frameworks and reporting on model performance will be needed to ensure investments translate into measurable resilience.
For CISOs and security teams, the report points to the need for stronger validation processes and tighter integration between AI tools and human analysts. That includes formal testing regimes, adversarial testing, continuous monitoring of model drift, and playbooks that specify when analysts should override automated decisions. Organisations should also pay attention to data quality and lineage, as biased or poorly curated training data can erode detection accuracy.
Regulators and sectoral authorities are likely to take interest as well. As AI-based security controls proliferate across critical infrastructure and financial services, expectations for auditability, explainability and incident reporting will increase. Firms that can demonstrate structured governance and robust validation will be better positioned to satisfy both regulators and customers.
Market implications and next steps
The KPMG analysis suggests several near-term industry trends. Demand for managed security services that combine AI tooling with human expertise is likely to grow, especially among organisations that lack in-house data science or security operations capabilities. Vendors will face pressure to improve transparency around model performance and to provide tooling for validation and lifecycle management.
Investment priorities are also likely to shift. Rather than allocating budgets purely to experimentation or tool acquisition, many organisations will need to invest in governance frameworks, change management, talent and processes that operationalise AI safely. Training for security teams on validating model outputs and responding to AI-driven alerts will be a practical focus.
Finally, given the identity-driven nature of many regional attacks, firms should prioritise controls that harden identity and access management alongside AI-based detection. AI can augment identity analytics, but these systems require continuous tuning to distinguish between legitimate and malicious behaviour at scale.
Bottom line: AI is becoming integral to cybersecurity in the UAE, but KPMG’s report warns that the technology’s benefits will remain limited unless organisations invest in governance, validation and lifecycle security. The shift from rapid deployment to disciplined implementation will determine which organisations convert AI projects into durable improvements in resilience.
