新兴的‘混合专业人士’：生成式AI对阿联酋技能需求变化的影响

Ahmed Dawoud and Ahmed Habashy Abstract Global models of Generative AI’s impact are insufficient for the United Arab Emirates,where national strategies collide with unique demographic pressures. This studyaddresses this gap through a novel, task-level analysis of 23,739 job postings,constructing a “Job Automatability Index” for the UAE. We find that AI exposureis invariant to geography, confirming its nature as a structural force. The results reveal sharpoccupational polarisation: Clerical Support Workers face high substitution risks (53.8 percentautomatability), while manual roles remain insulated. Critically, for the dominant professionalclass, AI’s primary mechanism is not substitution but the fundamentalredefinitionof coretasks. By identifying the emergence of the “hybrid professional,” this study provides a preciseframework for policymakers to align Emiratisation, migration, and upskilling strategies with themechanics of an AI-driven economy. Introduction The global economy is grappling with a profound paradox. While Generative ArtificialIntelligence (GenAI) is being adopted at unprecedented speeds, its promise ofa productivity revolution remains largely unfulfilled. This disconnect betweenindividual efficiency gains and lagging organisational performance highlights acritical uncertainty: firms and nations are investing billions in a technology whose impact theydo not yet fully understand. Global models offer broad predictions, but they are insufficientfor navigating the high-stakes reality of a nation like the United Arab Emirates (UAE), whereimmense, state-driven AI ambition collides with unique economic and demographic pressures.The UAE’s national strategies for economic diversification and workforce nationalisation (whatthe UAE government refers to as “Emiratisation”) are being forged at the very moment AI is setto redefine the nature of work itself. This challenge is particularly acute in a labour market where expatriate workers havehistorically dominated most sectors, particularly in low- and semi-skilled roles. The rationaleof this analysis, therefore, stems from the urgent need to understand how AI can be leveragedtocreate high-value jobs for the national workforce of the UAE,aligning technologicaltransformation with the strategic goals of Emiratisation. This report confronts this uncertainty by moving beyond speculation to provide a high-resolution map of AI’s real-world impact on the UAE’s labour market. The challenge forpolicymakers and business leaders is not the absence of ambition, but a lack of granular,empirical evidence. It is one thing to know that AI will transform skills; it is another to knowprecisely which skills, in which jobs, and through what mechanism. Answering these questionsis impossible with generic, top-down analyses that treat occupations as monolithic blocks. Thisreport introduces a novel,task-level methodology to analyse AI’s impact.Bydeconstructing over 23,000 online job postings into their constituent tasks, the authors’proprietary analytical pipeline creates the Job Automatability Index—a bottom-up, data-drivenmeasure of automation exposure. This approach allows one to pinpoint the true loci of change,revealing a sharp occupational polarisation hidden within broad sectoral trends. This reportnot only identifies the roles most exposed to substitution and those insulated from change,but, most importantly, it diagnoses the mechanics of augmentation and redefinition that willshape the future of high-skill professional work. It provides the first empirical baseline of AI’simpact on the UAE, offering actionable insights for navigating the complex interplay betweentechnological disruption and national ambition. Literature Review GenAI is transforming the nature of work at an unprecedented speed and scale,raising urgent questions about its economic impact.1While global models provide afoundational understanding of this disruption, they are structurally ill-equipped tonavigate the UAE’s distinct reality. Unlike the mature labour markets of the GlobalNorth, the UAE is defined by asevere demographic imbalance—where expatriates dominatethe workforce—and a state-mandated urgency to integrate nationals into the private sector(‘Emiratisation’). This creates a specific, high-stakes paradox: national strategies are pushing citizens towardadministrative and white-collar roles that are now the primary targets of AI automation. Globalmodels cannot account for this collision between workforce nationalisation and technologicalsubstitution. This review synthesises established research to pinpoint this critical gap, arguingthat the UAE requires a bespoke empirical framework to ensure that AI becomes a tool forstrategic economic leverage rather than a barrier to national ambition. A New Technological Paradigm: Disruption of Speed and Scope The current technological wave driven by GenAI is fundamentally distinct from previous shiftsin its speed and scope.2Its adoption rate is unm