Gulf organisations race ahead on AI adoption, but scaling and workforce gaps persist
Within just a few years, AI has become a near-default layer within organisations across the region, with more than 9 in 10 now applying AI in some form. That is according to research from Korn Ferry – yet beneath its headline adoption figures, the firm highlights there remains substantial work to be done around scaling and enterprise-wide rollout.
The report from Korn Ferry, based on insights from leaders across more than 100 organisations in Saudi Arabia, the UAE, Qatar, Oman, Bahrain, and Kuwait, highlights AI as a defining force in regional transformation. Its growth path of AI across the Gulf Cooperation Council (GCC) has been nothing short of remarkable and its impact is expected to reshape sectors, business processes, and innovation cycles.
Across sectors as diverse as energy & utilities, retail, consumer goods, financial services, manufacturing, government, and oil & gas, organisations are increasingly using AI to improve efficiency, enhance decision-making, strengthen foresight and planning, improve customer experience, and run complex analyses beyond human capability.
The benefits extend across the entire make-up of organisations – from customer-facing and commercial functions to internal operations and support teams.
Uneven adoption across countries and sectors
However, beneath the surface-level momentum, adoption paths diverge significantly. Korn Ferry’s findings point to variation in how AI is being adopted across the Gulf, both at country and sector level.
The UAE stands out for more advanced deployment, with around 20% of organisations already using AI across multiple functions and comparatively lower levels of inactivity. Saudi Arabia, by contrast, shows the largest absolute number of organisations in pilot or exploration phases, reflecting the scale and breadth of transformation underway under Vision 2030.
Meanwhile, Qatar, Oman, Bahrain, and Kuwait exhibit more measured adoption profiles.
From an industry perspective, technology firms are the clear frontrunners, with a majority already deploying AI across core functions. Energy & utilities follow closely, leveraging their long-standing strengths in data and advanced analytics.
Financial services – the most heavily represented sector in the study – presents a more cautious trajectory, with most organisations still in pilot or exploration phases. Oil & gas, despite vast data reservoirs and a strong analytics legacy, similarly shows limited full-scale deployment.
The pilot phase dominates GCC AI maturity
Overall, the study reinforces a consistent pattern seen across multiple AI adoption surveys in the region: the dominance of the pilot phase.
Nearly half (49%) of organisations describe themselves as piloting AI in selected functions – active enough to deploy tools and test use cases, but not yet at the stage where AI is fundamentally reshaping operating models. A further 28% remain in exploration mode.
Taken together, more than three-quarters of organisations are still positioned between intent and impact. In other words, while experimentation is widespread, organisation-wide deployment remains a work in progress.
Getting it right
As GCC organisations scale their AI investments, the report warns against treating AI as a purely technological initiative. AI transformations, it argues, are inherently complex and multidisciplinary, affecting workforce structures, ways of working, and organisational culture – and often encountering resistance along the way.
To succeed, AI programmes must follow an integrated roadmap that combines technical capability with organisational design, workforce readiness, and cultural alignment. Yet on several of these factors, the research highlights structural gaps.
One of the most notable sits at leadership level. In around 60% of cases, accountability for AI sits with CIOs or Digital or IT leaders. Far fewer organisations assign ownership to other CxO roles, and HR is almost entirely absent at just 3% – despite the fact that workforce impact is among the most immediate and significant consequences of AI adoption.
A second major challenge is workforce readiness. While ambition is high, organisational preparedness remains limited. Only 1% of organisations in the GCC consider themselves fully equipped to adopt AI at scale. Around 30% say they are not ready at all, while the majority (46%) describe themselves as only somewhat ready.
Beyond readiness, organisations face a range of structural barriers that continue to slow the transition from pilot to enterprise scale. The most significant challenge is technology integration (61%), followed by talent gaps (44%) and uncertainty around return on investment (37%). Importantly, these issues are not purely technical – they reflect broader organisational constraints that limit execution at scale.
Regulatory risk adds another layer of complexity, as organisations must balance innovation with compliance requirements related to privacy, security, and ethical use of data.
Leadership alignment is also cited as a barrier, indicating a disconnect between strategic intent at board level and operational execution within business units – often the “missing middle” where AI value is either unlocked or lost.
Closing the gap between ambition and execution
Commenting on the findings, Jonathan Holmes, Managing Director for the Middle East, Turkey & Africa at Korn Ferry, said: “The Gulf has no shortage of AI ambition. What it needs now is the organisational architecture to turn pilots into performance – and that requires leaders to make decisions that go well beyond the tech budget.”
