A notable shift is underway in the governance of artificial intelligence, with the United Arab Emirates leading a growing global trend as organisations increasingly appoint chief AI officers (CAIOs). A new global study conducted by the IBM Institute for Business Value (IBV) in collaboration with the Dubai Future Foundation (DFF) surveyed more than 600 CAIOs across 22 countries and 21 industries. The findings position the UAE at the forefront of AI leadership, underscoring how CAIOs are becoming central to shaping strategy, execution, and measurable value from AI investments across public, private, and cross-sector contexts. The research reveals that one in three organisations in the UAE have appointed a CAIO, compared with a global average of about one in four, highlighting a pronounced UAE-centric emphasis on organized AI governance. As organisations running CAIO-led models report stronger returns on AI spending, the UAE’s approach is framed not merely as a trend but as a strategic governance shift with tangible ROI implications. This rapid adoption aligns with broader national ambitions to position the UAE as a global hub for responsible and scalable AI across key sectors.
UAE CAIO leadership as a global trend and the UAE’s pioneering position
Across the global landscape surveyed, CAIO roles are increasingly becoming a standard feature of corporate and public sector governance. In the UAE, the prevalence of CAIO appointments stands out, reflecting a deliberate national strategy to embed AI leadership at the core of enterprise and governance. The study shows that organisations in the UAE report a 33 percent CAIO adoption rate, surpassing the global average of 26 percent. That differential is not merely symbolic; it translates into measurable differences in how AI investments are governed, funded, and implemented. When CAIO-led structures lean into centralized or hub-and-spoke operating models, the return on AI investment tends to rise significantly, by as much as 36 percent. This finding points to how the configuration of AI leadership—centralized authority, clear accountability, and coordinated resource allocation—can amplify impact and speed of value realization. The UAE’s case demonstrates that the leadership architecture around AI is a decisive variable in translating technical capability into enterprise value.
Within this framework, the UAE’s CAIOs are not treated as technicians alone, but as strategic orchestrators who bridge vision to execution across multiple domains. The foreword of the IBV-DFF report is written by His Excellency Omar Sultan Al Olama, UAE Minister of State for Artificial Intelligence, Digital Economy and Remote Work Applications, who emphasizes the cultural and operational importance of AI leadership. He describes AI not as a single breakthrough but as a continuum of ten thousand smaller shifts that are cultural, institutional, and habitual in nature. In this view, the CAIO becomes the agent responsible for nurturing that habit and pushing it forward across diverse functions—from public administration and healthcare to education and logistics. The role is framed as more than a technologist; it is a translator between strategic intent and operational reality, a bridge linking strategy to science, and a steward of enterprise value across the entire organization. This articulation frames CAIOs as essential drivers of transformation rather than mere guardians of AI budgets.
The report also features a cross-sectoral perspective from important UAE entities, including the Roads and Transport Authority (RTA) and Dubai Customs. Their participation demonstrates a broad, cross-sectoral commitment to AI strategy in the country. The emphasis on cross-sectoral collaboration signals that AI governance in the UAE is designed to cut across public and semi-public institutions, integrating AI priorities with service delivery, infrastructure, and public safety. Commenting on the UAE’s approach, Saeed Al Falasi, the director of the Dubai Center for Artificial Intelligence, highlights that Dubai’s early adoption of the CAIO role reflects a national commitment to a responsible, future-ready government. He notes that the study reinforces CAIOs as strategic enablers and catalysts who drive the city’s vision for the future. By equipping these leaders with the right tools and authorities, he argues, the framework paves the way for scalable, measurable AI impact across essential sectors in Dubai. The leadership voice emphasizes that enabling CAIOs with budgetary visibility and decision rights is foundational to moving from pilots to broader deployment.
Shukri Eid, vice president and general manager for IBM Gulf, Levant and Pakistan, adds that the UAE is setting a global benchmark by embedding CAIOs within organizations so AI becomes a strategic enabler across sectors. He frames this as evidence of a forward-looking national strategy and notes IBM’s continuing collaboration with the Dubai Future Foundation to help organizations scale their AI capabilities to achieve measurable, long-term impact. Lula Mohanty, IBM Consulting’s managing partner for the Middle East and Africa, underscores that early CAIO appointments and the allocation of visibility and budget authority have laid a robust foundation for enterprise AI in the UAE. The next phase, she argues, is execution: moving beyond pilots, embedding AI into core business functions, and delivering tangible ROI. IBM’s partnership with UAE clients is positioned as a critical element of enabling this next phase and ensuring that AI capabilities translate into sustained business and public-sector value. Collectively, these voices illuminate a shared conviction that CAIOs are strategic leaders essential to realising a future-ready AI economy in the UAE.
Benchmarking UAE’s CAIO leadership against global averages and ROI implications
A key insight from the IBV-DFF study is that UAE CAIOs enjoy notably stronger support from senior leadership compared with their global peers. The data show that 90 percent of UAE CAIOs report receiving adequate CEO support, contrasted with 80 percent globally. This is a significant leadership endorsement, since CEO backing is a critical driver of resource allocation, prioritization, and cross-functional collaboration. Beyond CEO sponsorship, 86 percent of UAE CAIOs report broader backing from the C-suite, versus 79 percent globally. This expanded executive sponsorship translates into more stable governance, faster decision cycles, and better alignment of AI initiatives with overarching strategic objectives. Another indicator of robust internal legitimacy is internal appointment: 69 percent of UAE CAIOs were appointed from within their own organisations, compared with 57 percent globally. Internal appointments tend to reflect deeper organizational trust and better alignment with existing capabilities and culture, aiding in smoother execution and continuity.
The roles themselves are broader and more strategic in the UAE context. A striking 79 percent of UAE CAIOs exercise control over the AI budget, compared with 61 percent globally. This indicates a higher degree of financial autonomy, enabling CAIOs to prioritise initiatives, allocate resources, and drive outcomes with fewer fiscal gatekeepers. Additionally, 62 percent of UAE CAIOs prioritise building business cases for AI investments, versus 45 percent globally, suggesting a more deliberate emphasis on ROI justification and value storytelling to secure organisational buy-in. While 50 percent oversee direct implementation of AI, in line with global peers, the UAE demonstrates a more pronounced expectation that CAIOs are involved in hands-on delivery and operational integration. These shifts collectively illustrate a governance model in the UAE that empowers CAIOs with budgetary control, strategic influence, and direct execution authority—factors that are strongly correlated with more rapid progression from pilot projects to scalable deployments.
Despite these strengths, UAE CAIOs report notable implementation challenges. About 38 percent characterize implementation as “very difficult,” a share higher than the global average of 30 percent. This signals that while CAIOs are empowered and resourced, the complexity of operationalizing AI within diverse contexts still presents meaningful hurdles. The data also reveals that UAE CAIOs bring deep operational expertise, with 69 percent having a background in data and 48 percent coming from operations, compared with 38 percent globally from operations. This concentration on execution-oriented backgrounds reflects a governance philosophy that values practical capability for turning AI propositions into action and measurable results. The emphasis on operational grounding may also imply a preference for immediate, impact-focused outcomes and a readiness to integrate AI into daily workflows and processes.
As organisations navigate the balance between experimentation and accountability, the UAE demonstrates distinctive patterns. Seventy-six percent of UAE CAIOs say their organisation risks falling behind without measuring AI impact, compared with 72 percent globally. This indicates a strong emphasis on accountability and the need for metrics to demonstrate value, even as progress continues. Meanwhile, 74 percent of UAE CAIOs initiate AI projects even if results cannot yet be fully measured, compared with 68 percent globally. This showcases a pragmatic willingness to pursue experimentation in the absence of perfect metrics, while still maintaining a focus on accountability and eventual measurement. Taken together, these attitudes reflect a mature risk posture: organisations value both agile experimentation and governance discipline, recognizing that early action can create longer-term advantage even as measurement frameworks are being refined.
UAE CAIOs’ operational maturity and the state of AI deployment
The study reveals a nuanced maturity landscape for AI adoption in the UAE. While leadership momentum is strong and CAIOs wield significant strategic influence, the broader enterprise AI maturity shows room for scale. A notable 76 percent of UAE organisations remain in pilot stages for their AI initiatives, compared with 60 percent globally. This divergence signals substantial headroom for expanding from experimental pilots to enterprise-wide, scalable AI deployments. The UAE’s growth trajectory thus rests not only on appointing CAIOs but also on accelerating capability-building, process redesign, data governance, and cross-functional collaboration to operationalize AI at scale. The report’s cross-sectoral insights emphasize that the UAE’s AI governance framework is designed to support scalable impact across critical domains, including healthcare, education, energy, smart cities, and transport.
The UAE’s broader national ambitions are reflected in its AI Strategy 2031, which aims to secure a leadership position for the country as a global AI hub across multiple sectors. The IBV-DFF study is positioned within this national agenda as a translatable, evidence-based reference that highlights the central role CAIOs play in turning strategy into practice. By foregrounding CAIOs as key enablers of a future-ready government and economy, the study contributes to the ongoing dialogue about governance models, investment strategies, and cross-sector collaboration necessary to achieve ambitious AI outcomes. The alignment with Strategy 2031 also underscores how the UAE is approaching AI governance as a national, long-term mandate rather than a collection of isolated initiatives. The cross-pollination of insights from public agencies like the RTA and Dubai Customs demonstrates the practical application of CAIO-led governance in real-world service delivery and operational optimization.
In practical terms, UAE CAIOs are seen as strategic enablers who promote a holistic view of AI that integrates data strategy, budgeting, and governance with execution. The leadership narrative positions CAIOs as stewards of value, responsible for delivering measurable ROI while maintaining responsible AI practices, transparency, and alignment with public-interest goals. The study’s findings suggest that UAE organisations are building a governance culture where AI is embedded in core business functions, rather than existing as a siloed technology initiative. As organisations continue to scale, CAIOs will likely play a pivotal role in coordinating data infrastructure, ethical considerations, risk management, and performance measurement across domains to ensure sustained impact.
The UAE’s cross-sector AI initiatives: from Dubai to national scale
Dubai’s early adoption of the CAIO role is framed as part of a broader national strategy to foster responsible AI leadership and to accelerate digital transformation across public services and the economy. The leadership remarks acknowledge this cross-city, cross-sector momentum as a catalyst for scalable AI impact. By empowering CAIOs with the authority to direct AI strategy and with access to essential resources, the UAE aims to create a cohesive landscape in which AI innovations can proliferate beyond pilot projects into core business and public service functions. The result is a more integrated approach to AI implementation, enabling organisations to align AI outcomes with strategic priorities such as efficiency, customer experience, digital citizenship, and sustainable growth. In Dubai, this approach is being connected to measurable outcomes across sectors, underscoring a shared objective: to translate AI capabilities into tangible value for residents, businesses, and government agencies.
The cross-sectoral contributions of entities such as the RTA and Dubai Customs illustrate how CAIO-led governance can translate into improved operations and services. Those involved emphasise that the CAIO framework helps unite data-driven decision-making with policy and service delivery. The cross-pollination of insights across sectors allows best practices to proliferate, enabling organisations to adapt AI governance models to their unique contexts while maintaining alignment with a national AI strategy. The cross-pertilization also strengthens the UAE’s position as a testbed for scalable AI governance, with experiences from transport and customs informing broader public-sector practice and private-sector adoption. This holistic approach demonstrates how CAIOs serve as both strategists and operators, ensuring that AI decisions are practical, scalable, and aligned with public-interest outcomes.
In this context, the UAE’s ambition to be a leader in AI across health, education, energy, and smart cities is presented as both a national aim and a practical program. The IBV-DFF study emphasizes that CAIOs are central to achieving that ambition by providing a coherent governance mechanism that bridges diverse domains, accelerates policy-to-execution cycles, and aligns AI investments with measurable outcomes. The collaboration between IBM and the Dubai Future Foundation is positioned as a capability-building partnership aimed at helping organisations scale their AI capacities to drive measurable, long-term impact. Importantly, the study reinforces that CAIO-led governance is not merely about technology adoption; it is about cultivating a culture of data-informed decision-making, ethical AI practices, and accountable performance across the enterprise.
Building capabilities: data, budgets, and governance under CAIO leadership
An essential takeaway from the UAE CAIO experience is the emphasis on developing the underlying capabilities that make AI governance effective. The data background of CAIOs—69 percent with a data-oriented foundation—points to a governance model that prioritises data readiness, quality, and stewardship. This focus on data readiness correlates with the ability to budget intelligently for AI initiatives, scale up pilots, and measure impact with reliable metrics. The 48 percent who come from operations underline an appreciation for execution readiness, process integration, and the pragmatics of embedding AI into day-to-day activities. The combined emphasis on data and operations suggests a governance philosophy that values both technical sophistication and hands-on implementation experience. This dual emphasis helps ensure that AI projects move beyond theoretical potential to practical transformations that affect service delivery and business performance.
Budget control is a central feature of the UAE CAIO model. With 79 percent of CAIOs controlling the AI budget, organisations can prioritise initiatives, allocate funds to high-impact opportunities, and avoid fragmentation across departments. This financial autonomy enables faster decision-making and reduces friction that might slow deployment. Alongside budget control, the ability to build a compelling business case (62 percent of UAE CAIOs) reinforces prudent investment in AI with clear justification and anticipated ROI. The combination of budget authority and rigorous business case development creates a strong governance substrate for AI initiatives to scale and deliver measurable outcomes.
Governance structures in the UAE also reflect a balance between experimentation and accountability. The willingness to initiate AI projects even when results are not fully measurable (74 percent) sits beside a robust focus on metrics and impact (76 percent). This balance supports a culture of informed risk-taking where experimentation is conducted with a clear plan for measurement, learning, and iteration. The governance framework therefore emphasises both the speed of experimentation and the discipline of accountability, enabling organisations to learn quickly while maintaining scrutiny of results and alignment with strategic objectives. Such governance can foster continuous improvement, iterative refinement of AI models, and the expansion of successful pilots into mainstream operations.
Across sectors, the study highlights a strong preference for embedding AI into core functions and business processes. UAE organisations are increasingly prioritising the integration of AI into operational workflows and decision-making routines rather than treating AI as a stand-alone, isolated capability. This approach recognises that AI’s true value emerges when it is embedded into the governance, planning, and execution cycles of the organization. The UAE’s strategy thus encourages not only the creation of CAIO roles but also organizational redesign to support AI-enabled value creation. The ultimate objective is to ensure that AI becomes a mainstream capability—an everyday tool that informs strategy, enhances efficiency, improves outcomes, and supports a resilient, future-ready economy.
The strategic narrative: CAIOs as catalysts for measurable, long-term impact
The CAIO role in the UAE is increasingly framed as a strategic enabler capable of driving measurable ROI and long-term impact across sectors. The leadership insights from UAE officials emphasize that CAIOs are catalysts who help translate visionary goals into executable programs, ensuring that AI investments yield tangible benefits. The emphasis on ROI, both in relative terms and through centralized operating models, reflects a disciplined approach to governance in which the value of AI is tracked through concrete metrics, business cases, and performance indicators. The study’s findings reinforce the view that CAIOs must balance strategic foresight with operational rigor, enabling organisations to pursue ambitious AI agendas while maintaining a clear perspective on cost, risk, and impact.
In Dubai and the broader UAE, the role of CAIOs is increasingly seen as a bridge between public policy and enterprise execution. CAIOs must align AI activities with national priorities and sector-specific needs, ensuring that AI innovations improve public services, enterprise productivity, and the readiness of the workforce for AI-enabled work. The cross-sector collaboration highlighted in the study underscores the importance of sharing insights, standardising data practices, and coordinating governance across ministries, agencies, and private sector partners. By integrating CAIO-led governance into a national AI strategy, the UAE aims to accelerate learning, adoption, and scaling of AI across domains, while maintaining a shared commitment to responsible AI, transparency, and value creation for society at large.
The broader market implications of the UAE’s CAIO-driven governance approach extend beyond national borders. As more organisations around the world adopt CAIO roles, the UAE’s model offers a blueprint for how leadership, budgeting, and execution can coalesce to accelerate AI value. The emphasis on strong executive sponsorship, operational experience, and the ability to fund and govern AI initiatives provides a replicable framework for organisations seeking to mainstream AI governance. The UAE’s experience demonstrates that CAIOs can play a pivotal role in moving AI from pilot projects into scalable, measurable, and ethically aligned implementations that contribute to sustained performance improvements.
Practical implications for organisations adopting CAIO-led AI governance
For organisations considering CAIO-led governance, the UAE case highlights several practical implications. First, securing strong CEO and C-suite support is essential for enabling the cross-functional collaboration and resource allocation required to scale AI initiatives. The UAE experience shows that executive sponsorship is not optional but a foundational driver of success. Second, enabling CAIOs with budgetary authority and clear decision rights is a critical accelerator of implementation, allowing rapid alignment of investments with strategic priorities. Third, cultivating a CAIO with a deep operational or data background can enhance the translation of AI concepts into real-world improvements, ensuring that data assets, process improvements, and analytics capabilities converge to deliver concrete value. Fourth, organisations should embrace a governance approach that balances experimentation with accountability, enabling rapid iteration while maintaining a clear framework for measurement and consequences. Fifth, embedding AI into core business processes and public services—not treating AI as a separate initiative—helps ensure that AI capabilities are integrated into the daily work of teams, enhancing both efficiency and outcomes. Finally, organisations should anticipate a maturation path that includes moving beyond pilots toward scale, with targeted roadmaps, data governance improvements, and capability-building that supports iterative deployment and continuous learning.
Implications for policy, governance, and the global AI landscape
The UAE’s CAIO-led governance experience has broader implications for policy and global AI governance. The study’s findings underscore the importance of creating leadership roles that are not purely technical but are integrated with strategy, budgeting, and execution functions. This governance model supports the idea that AI initiatives should be treated as enterprise-wide programs with governance structures that enable cross-functional collaboration, accountability, and measurable outcomes. In the global context, CAIOs emerge as a critical element in harmonising AI strategy across public and private sectors, enabling organisations to align AI investments with broader societal objectives and long-term value creation. The UAE’s experience suggests that when CAIOs have access to resources, authority, and an ecosystem that fosters data readiness and operational excellence, AI initiatives can transition from experimental pilots to scalable deployments that deliver real ROI and public value.
Moreover, the UAE’s AI Strategy 2031 provides a reference point for other nations seeking to embed AI governance within their strategic plans. The approach demonstrated in Dubai and across UAE institutions reflects a blended model that combines strong executive sponsorship, cross-sector collaboration, practical execution capabilities, and a national mandate to become a global AI leader. As organisations around the world observe the UAE’s progress, they may consider adopting similar governance elements—clear CAIO roles, budgetary control, structured business-case development, and targeted data and operational competencies—to accelerate AI maturity and ensure that AI investments yield lasting impact. The study thus contributes to a broader global discussion about how best to govern AI in ways that are recursive, adaptive, and aligned with long-term economic and social objectives.
Conclusion
The UAE’s ascent as a global leader in AI governance is anchored in a deliberate strategy to embed CAIOs at the heart of organisational and national AI initiatives. The IBV-DFF study demonstrates that UAE CAIOs benefit from strong leadership support, broader strategic responsibilities, and direct influence over budgets and execution. The data show that UAE organisations place a premium on building robust business cases, prioritising ROI, and balancing experimentation with accountable governance. While there is evidence of ongoing challenges in scaling implementation, the UAE’s approach—grounded in data readiness, operational expertise, and cross-sector collaboration—positions CAIOs as central to realising the ambitious goals of Strategy 2031. The country’s model offers a concrete blueprint for turning AI ambitions into scalable, measurable outcomes that advance public administration, healthcare, education, logistics, energy, and smart city initiatives. As AI governance continues to evolve globally, the UAE’s CAIO-led framework represents a meaningful benchmark for how leadership, governance, and execution can coalesce to deliver lasting value in a rapidly changing technological landscape.
