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New IDC study identifies governance gap as AI adoption accelerates across UAE enterprises. In line with Cyber Security Awareness Month, Microsoft, CPX and IDC today released the findings of 'Securing AI in the UAE Enterprise', a new study examining how organizations across the UAE are adapting their cybersecurity models and governance structures as AI adoption accelerates. The study comes as the cyber environment grows increasingly complex and AI reshapes both attack and defense. Recent coordinated cyberattacks targeting numerous sectors have reinforced the importance of continuous preparedness, while AI is giving both attackers and defenders new capabilities. Against this backdrop, Microsoft and CPX worked with IDC to examine whether enterprise security, governance and operating models are evolving quickly enough to keep pace with AI adoption. Based on a survey of 175 senior security and technology executives across UAE enterprises, the research finds that organizations are moving quickly to capture the value of AI, but the governance and security models surrounding its use are not always developing at the same pace. While 80% of CIOs are confident their AI investments will deliver results within two years, 98% of security teams report having encountered at least one real AI security risk in their production environment. The findings point to a broader shift in the enterprise risk environment as AI becomes embedded across more systems, data and workflows. 92% of security leaders report AI systems processing sensitive data, while 54% have encountered a situation in which an AI system's decision could not be explained or audited in a compliance context. One of the clearest challenges is the growing use of AI outside established organizational controls. 43% of CIOs acknowledge that employees regularly use AI tools that have not been approved or issued by their organization. More than half of security teams have already identified data leakage through these tools. Agentic AI is creating a further governance consideration. More than half of organizations surveyed have AI agents deployed or in active development, yet only one in 10 consider themselves fully prepared to deploy agentic AI safely. In addition, 52% of security teams have already identified real data leakage through unsanctioned tools, reinforcing the importance of clear permissions, oversight and accountability as agent use expands. The report identifies a fundamental governance challenge behind this disconnect. Only 15% of CISOs have mandatory approval authority over AI deployments, while just 10% of organizations define security requirements before evaluating an AI solution. In most cases, security is brought into the process after key strategic or deployment decisions have already been made. The research also reveals a gap between awareness and action. Only 30% of organizations use a structured methodology to assess their AI security posture, while 40% rely mainly on reactive assessments, vendor reviews or third-party audits. With 87% of surveyed security teams not fully comfortable with AI security topics and just 13% having fully defined approaches and operating models, the study advises organizations with limited expertise to engage a trusted managed security partner for initial asset inventories and assessments. This way, providers with dedicated AI security capabilities can help make accountability operational without transferring responsibility. Commenting on the findings, Hadi Anwar, CEO of CPX, said: "The research makes clear that readiness cannot be measured by adoption alone. UAE organizations are moving quickly to capture the opportunities presented by AI, but the pace of technological change must be matched by clear accountability, stronger governance and security models designed for increasingly autonomous systems. The organizations that succeed will be those that embed security and governance into their AI programs from the outset." Rima Semaan, Data & AI lead at Microsoft UAE, said: "The pace of AI adoption is not going to slow down. But as AI becomes part of more day-to-day decisions and workflows, organizations need to be just as deliberate about how they govern it. They need visibility into where AI is being used, clear accountability, and the right controls around data and access. This matters even more with AI agents. The opportunity for the UAE is to build these controls in early, so organizations can move quickly with AI without compromising trust." Shilpi Handa, Associate Research Director, Security & Trust, IDC, said: "AI adoption across UAE enterprises is accelerating rapidly, driven by strong national ambitions and government-led innovation agendas. However, while organizations are moving quickly to deploy AI, security governance has not kept pace. Our research has found security teams are already encountering AI-related risks, yet many CISOs still lack formal authority over deployment decisions. The challenge is not the technology itself. The real gap lies in governance, and it can be addressed with the right frameworks, accountability, and oversight in place." The study recommends giving security a formal role in AI decision-making, supported by clear approval processes, accountability and structured security assessments. Organizations should also audit existing AI systems and the data they process, develop policies for unapproved AI use, define permission boundaries for AI agents, and strengthen resilience and compliance planning for AI-specific risks. At the same time, AI is becoming an increasingly important part of cyber defense. Two-thirds of UAE security teams already use AI for cybersecurity, with the remainder planning to do so within the next 12 months. This creates a dual imperative for security leaders: govern and secure the AI being introduced across the organization, while using AI to improve threat detection, investigation and response. The study concludes that the next phase of enterprise AI in the UAE will require AI-ready security. Governance, visibility and security must be built into AI adoption from the outset as organizations deploy increasingly autonomous systems. Securing AI in the UAE Enterprise is available here.

Precisely named a Leader in the 2026 IDC MarketScape for Worldwide Data Intelligence Platform Software. * September 15, 2026 Guest authors: Marlanna Harringon, Senior Research Analyst, Data Platforms, IDC Stewart Bond, Vice President, Data Intelligence and Integration Software, IDC From governance tooling to AI infrastructure. For most of the last decade, data catalogs and governance tools sat at the edge of the enterprise architecture: useful for compliance and documentation, but rarely central to strategy. AI has pulled them to the center. When a model or an agent is only as trustworthy as the data behind it, the platform that catalogs, governs, and delivers that data stops being an operational afterthought and becomes a decision leadership has to get right. In IDC's 2025 Office of the CDO Survey, 86% of organizations reported increasing their focus on data management specifically to support generative AI and agentic AI. The budget and the executive attention are following the same path, because the layer that assembles and delivers trusted data is increasingly where AI programs either succeed or stall. This is no longer a governance-only conversation. It is an AI readiness conversation, and it is against this backdrop that IDC positioned Precisely in the Leaders category of the 2026 IDC MarketScape: Worldwide Data Intelligence Platform Software Vendor Assessment. The trends reshaping Data Intelligence. The 2026 IDC MarketScape evaluates 15 vendors and, across a diverse field, finds a notable degree of strategic alignment. Every vendor described a plan to embed generative AI and, increasingly, agentic AI into cataloging, quality, and governance workflows, and nearly all now expose governed metadata to AI agents through the Model Context Protocol or an equivalent open interface. The clearest signal in the market is the rise of the digital data steward: agents that take on the slow, manual work of documenting assets, drafting quality rules, and proposing remediation, with their reasoning surfaced for human approval. The real constraint most organizations face isn't a shortage of tools but a shortage of people and hours. Automation capable of executing stewardship work at scale is fast becoming table stakes. A parallel shift is happening around openness, as data products and contracts are increasingly built on open specifications, and lineage and storage interoperate through standards such as OpenLineage and Apache Iceberg. This leaves buyers materially less exposed to lock-in than they were even two years ago, and moves the real separation between platforms to architecture and native depth. Looking ahead, two directions are pulling the market forward: * AI and model governance, which is growing out of established data governance practices as model inventories, risk tiering, and drift monitoring move from road map into native functions. * Unstructured content, as vendors extend data intelligence to bring documents, images, and other dark data into the same governed catalog that already holds structured data. Together, they mark the shift from governing the data organizations already understand to governing everything AI now reaches. Underneath every one of these shifts is a single job to be done: supplying context. IDC treats context not as a separate market but as a new use case that data intelligence exists to serve. An agent that does not know what a dataset means, where it came from, or whether it can be trusted, will produce confident but ungoverned, and quite possibly incorrect, answers. Data intelligence is, ultimately, what turns raw metadata into context and reliably delivers it to both people and machines. Why the decision now drives AI ROI. The stakes are measurable, and the link runs directly from intelligence about your data to the data products built on top of it. Cataloging, lineage, quality, and governance enable a team to turn a raw dataset into a data product with accountable ownership, discoverable access, and a defined purpose. IDC research directly links data product maturity to AI outcomes. Organizations with high data product maturity are 5.5 times more likely to have generative AI in production and 4.6 times more likely to have agentic AI in production than their low-maturity peers, and they report roughly three times the financial and operational improvement. That is why selecting a data intelligence platform is now a material driver of AI return on investment, not a strategic afterthought. Precisely was named a Leader in the IDC MarketScape assessment for both its current capabilities and forward-looking strategy against the criteria that matter most as the market shifts toward AI-ready data and trusted context. Read an excerpt of the 2026 IDC MarketScape: Worldwide Data Intelligence Platform Software Vendor Assessment for IDC's full view of the market and methodology. Virtual event. AI doesn't question your data. Your board will question you. Join Precisely October 8 as Precisely unveil a new era at Precisely and a new path to AI-ready data you can trust. Featuring Precisely CEO Walid Abu-Hadba, CPO Matt Waxman, IDC analyst Stewart Bond, and Precisely customers achieving AI-ready data today.