The UAE has moved from AI ambition to practical capability, backed by government leadership, investment, infrastructure and a growing technology ecosystem. The next opportunity is to translate those foundations into sustained enterprise value by redesigning work, strengthening the capabilities needed for scale and measuring the impact.
As countries globally accelerate the adoption of artificial intelligence (AI) and build the capabilities required to scale it, the United Arab Emirates (UAE) has moved quickly and decisively. Rather than treating AI as a standalone technology, the UAE is embedding it across government services, priority sectors and infrastructure, using it to reshape how services are delivered, how decisions are made and how economic value can be created.
The UAE Artificial Intelligence Strategy 2031 established the early direction. Its ambition to make the UAE one of the world's leading AI nations reflects a broader conviction that AI, deployed purposefully and responsibly, can strengthen productivity, accelerate innovation and create new sources of value.1
Moving AI from ambition to execution
That direction is now visible in the scale and breadth of the country's AI ecosystem. Domestic AI-related investments are reported to have exceeded Dh543bn between 2024 and 2025.2 Stargate UAE is also moving from plan to deployment, with the first 200MW of its 1-gigawatt AI compute cluster targeted for completion in 2026 as part of the UAE’s wider 5-gigawatt AI infrastructure ambition.3 These investments are expanding the compute, infrastructure and partnership base needed to deploy advanced AI at national scale.
Homegrown institutions and national champions are also strengthening the UAE's role in the global AI ecosystem. MGX is investing across AI infrastructure, semiconductors and frontier technologies,4 while organisations including G42, e& and the Advanced Technology Research Council are scaling sovereign cloud, foundational models AI-enabled services and digital enterprise tools.5 At the same time, initiatives in the UAE's financial centres are bringing AI into regulatory frameworks, business environments and talent development, helping organisations apply it in sectors where trust, data protection and resilience are essential.6
Government is moving beyond digital enablement towards AI embedded in how services and operations are designed. The federal Agentic AI framework aims to transition 50% of government sectors, services and operations within two years.7 It is supported by process redesign, integrated data and a capability-building programme for 80,000 federal employees. The significance is not simply the introduction of more advanced tools. It is the effort to make AI part of the operating model of government, with clearer accountability for decisions, service quality and outcomes.8
Abu Dhabi provides a practical example of this shift. Its 2025–2027 Digital Strategy is backed by Dh13bn of investment and aims to make the emirate the world’s first fully AI-native government by 2027.9 More than 100 AI use cases are already in use across government, with a pipeline of more than 200 being developed.10 Most recently, an agentic AI platform was used for the first time in an Abu Dhabi Executive Council meeting to support analysis-based discussion and data-driven decision-making.11 Chief data and AI officer roles have also been established across every government entity to strengthen ownership, governance and innovation.12
Dubai is extending the same momentum into the private sector.13 Its two-year programme to accelerate the adoption of Agentic AI is being delivered through Dubai Chambers, which has launched specialised training tracks for more than 14,000 member companies through the new Dubai Chambers Academy.14 The wider programme also includes plans for Agentic AI incubators, dedicated funding mechanisms and broader capability-building. These initiatives create a practical bridge between government ambition and business adoption.
The shift towards AI-enabled government is also taking shape across the northern Emirates.15 In Ajman, the government launched the Ajman Artificial Intelligence Programme in May 2026 and, two months later, completed the UAE’s first trade-license renewal using Agentic AI through a proactive, “headless” government service model. Sharjah is similarly accelerating the integration of AI assistants into government operations through its Sharjah AI Assistant Programme, alongside a broader 2026–2028 digital transformation strategy focused on integrated services, data and AI-enabled government.16
This progress is increasingly visible in both AI adoption and demand for skills. Microsoft’s latest Global AI Diffusion Report ranks the UAE first globally for AI diffusion, with 73.3% of the working-age population using AI in the second quarter of 2026.17 At the same time, PwC’s 2026 AI Jobs Barometer ranks the UAE among the world’s fastest-growing AI talent markets, with the share of job postings requiring AI skills more than tripling from 2021 to 2025.18
These advances show a shift from ambition to capability and, increasingly, to execution. The UAE has created many of the conditions needed for AI at scale: national direction, public-sector deployment, infrastructure, investment, an enabling ecosystem and a growing talent base. The next phase of growth would be to use those foundations to generate sustained and measurable enterprise value.
Turning national momentum into enterprise value
Progress at national level changes the question facing business leaders. The priority is no longer simply to increase the number of AI tools or pilots in use. It is to improve the rate at which AI activity translates to better decisions, stronger customer outcomes, new revenue, lower structural cost and faster growth.
PwC's global AI performance study shows why this matters.19 PwC defines AI fitness as the combination of the foundations that make AI reliable and scalable and the ways in which it is applied to create value. Those foundations include strategy, investment, data and technology, workforce, governance and risk, and innovation. They are reinforced by how broadly, deeply and intelligently AI is used across the organisation.
The lesson is not that organisations should slow adoption. It is that they should become more deliberate about where AI is applied, what must change around it and how outcomes will be measured.
Three shifts can help focus the next phase.
1. From task-level use cases to redesigned end-to-end workflows
Many organisations begin with targeted applications that draft, summarise, analyse or recommend. These uses can save time, but faster task execution does not automatically create economic value. Value appears when released capacity is redirected, hand-offs are removed, service levels are improved, costs are structurally reduced or new revenue is created.
The next step is therefore to redesign priority workflows end to end to deliver outcome: clarifying where AI should support or execute decisions, how roles and decision rights need to change, where human judgement remains central and how quality will be monitored. PwC's global research found that AI leaders are twice as likely as other organisations to have AI scaled or embedded across major parts of the value chain.20 Agentic AI makes this shift more important because autonomous execution works best when it is built into a coherent process, with clear guard rails and accountability, rather than added to a single task in isolation.
2. From incremental efficiency to growth and reinvention
Productivity remains an important source of value, but the larger opportunity is to use AI to change what an organisation offers, how it serves customers and where it competes. This may involve reconfiguring capabilities and value chains, changing propositions and, where the economics support it, reshaping business models. The question is no longer only where AI can improve the existing business, but what new sources of value become possible because AI changes how customers can be served and how the organisation can compete.
The global evidence points in the same direction. AI leaders are 2.6 times as likely as other organisations to report that AI has improved their ability to reinvent their business model, and they are more likely to use AI to identify emerging value pools and pursue opportunities across sector boundaries.21 The UAE's concentration of government, capital, technology companies, research institutions and sector leaders creates a strong environment for this kind of collaboration. The task for individual organisations is to translate that environment into a small number of growth priorities with clear owners, investment choices and measures of success.
3. From enabled adoption to owned, repeatable scale
External partners can accelerate adoption, but sustainable advantage requires organisations to own the outcomes. That means retaining the internal capability to set priorities, understand the economics, govern risk, manage partners and continuously improve what has been built. It also requires the enterprise backbone for repeatable scale: consistent and accessible data, reusable AI components, integration into core systems and architecture that allows successful solutions to be deployed repeatedly rather than rebuilt each time.
Focused foundations improve the conversion of AI activity into performance. PwC's global study found that companies with strong foundations see nearly twice the improvement in AI-driven performance when they increase AI use, compared with those whose foundations are weaker. Workforce capability is part of that equation. AI leaders are more likely to provide ongoing, role-based learning, and their employees are around twice as likely to trust AI-generated insights enough to act on them. Training therefore needs to be combined with role redesign, clear guidance on responsible use and incentives that encourage people to apply AI where it improves outcomes.22
Trust runs through each of these foundations. As AI moves further into regulated, customer-facing and decision-intensive activities, cybersecurity, responsible AI, model governance, data protection and data residency become business priorities, not simply technical safeguards.
For leaders, the question is not 'how much AI?' but 'what changed?'
The practical agenda is now more than simply launching more AI initiatives. Governance is an important part of that agenda. Much of the global debate around AI has focused on extreme future scenarios, but the questions facing organisations today are increasingly practical: who is accountable for AI-enabled decisions, how data and models are governed, where human oversight remains essential, and how cybersecurity and resilience are maintained as systems become more autonomous.
The UAE is increasingly formalising these questions alongside adoption. The federal framework for Agentic AI defines roles and responsibilities across ministries and entities, while the new Artificial Intelligence and Data Authority brings AI policy, data governance, standards and compliance under a single national mandate.23, 24
• Where should AI fundamentally change how work gets done? Which end-to-end workflows should be redesigned, and how should hand-offs, decision rights and the balance between human judgement and AI-enabled execution change?
• Where can AI change the economics of the business? Which customer propositions, products, services, value-chain opportunities or business models become possible because of AI?
• What must the organisation own to scale AI repeatedly and responsibly? Which capabilities need to sit inside the business — from data, architecture and reusable AI components to governance, cybersecurity, model oversight, partner management and critical skills — and where must human accountability remain explicit?
• How will the organisation know whether AI is creating value? What outcomes and baselines will be used, who owns the benefits, and can improvements be traced through to revenue, margin, cost, capacity, customer outcomes or operating performance?
The UAE's AI story is entering an important new phase. Government leadership has created strong national momentum and an environment in which advanced AI can be built and deployed at scale. The next step is to convert that momentum into an operating discipline that redesigns work, strengthens workforce capability, supports reinvention and consistently improves measurable outcomes, while maintaining the governance and trust needed to scale responsibly.
The organisations that do so will not simply be the UAE's most active users of AI. They will be the ones that turn national AI momentum into enterprise advantage and use that advantage to compete for value well beyond the domestic market.
UAE Country Senior Partner, PwC Middle East
