The Gulf is aiming to become a global AI hub, with businesses and governments deploying generative tools, building sovereign stacks, and enacting data rules at a frenetic pace. Still, experts warn that the region’s ambitions risk outpacing its ability to deliver measurable value. Surveys show deep penetration of AI pilots across the GCC, while workforce readiness, governance, and production-grade implementations remain the biggest hurdles.
“Our technology is far ahead of our human capacity to collaborate,” argues the acclaimed author and futurist Gerd Leonhard in an interview with TRENDS. “We are inventing very powerful things, but we don’t collaborate on how we use them and what the standards are and who is in charge,” he said.
Adoption at Warp Speed, Value Realization Lags Behind
A recent regional roundup put AI adoption in the Middle East at around 75 percent, for businesses using generative models in at least one function—higher than the global average hovering at 65 percent.
This signals rapid embrace across industries, and yet consultancy research cautions that adoption has so far largely been experimental. “Organizations in the region have been quick to adopt generative AI, but very few are yet seeing much benefit,” McKinsey notes in its 2024 report card on generative AI in the Middle East.
Sovereign capability and data localization are central to Gulf strategy. The UAE and Saudi initiatives aim to keep sensitive data under national control and to build local cloud and model-training capacity, part of a wider drive to reduce vendor dependence and protect national security. The UAE’s leadership has made its intentions clear.
“For the UAE, it’s not about saving money when it comes to AI but ensuring that people here stay and spend money, build families, and live for the long term,” said Omar Sultan Al Olama, UAE minister of state for artificial intelligence, digital economy, and remote work applications, at a recent conference of heads of state, ministers, policymakers, and AI pioneers in the capital.
The Readiness Gap: Talent, Governance, and the Human Bottleneck
The enthusiasm exhibited by leadership has not fully translated to the workforce. Multiple regional surveys have found a sizable share of workers not yet ready to use AI effectively—roughly in the 50–65 percent range, depending on the sample and question. Corporate readiness studies also highlight talent gaps.
Cisco’s AI Readiness Index for Saudi Arabia reports that “less than half (49 percent) of respondents in Saudi Arabia report high readiness from a data perspective to adapt, deploy, and fully leverage AI technologies.”
“The race to adopt and deploy AI has triggered a widespread discussion on the lack of skilled talent in the field, due in part to the pace at which the technology is evolving, with only 46 percent of organizations in Saudi Arabia claiming their talent is at a high state of readiness to fully leverage AI,” the Cisco study reveals. “More than one in 10 (14 percent) of respondents say that their organizations are under-resourced in terms of in-house talent necessary for successful AI deployment.”
Market forecasts point to a sizable prize. Statista-based projections put the Gulf AI market on a fast growth trajectory to around $15.4 billion by 2030, reflecting rapid investment and government support. The AI market in the region is projected to grow at a compound annual growth rate (CAGR) of 28.63 percent between 2024 and 2030.
From Pilots to Productivity: The Region’s Real Test Begins
Analysts say the region’s real test will be turning pilots into production systems that deliver measurable economic and social outcomes. “The conclusion is that while many organizations are investing in gen AI, few have begun to scale its implementation and extract value from their investments,” McKinsey warns, pointing to governance, data quality, and change management as sticking points. A small number—those McKinsey calls “value realizers”—stand out, already generating more than 5 percent of their earnings from generative AI.
For governments and corporates across the Gulf, the immediate task is pragmatic: marry sovereign ambition with sustainable skills programs, robust governance frameworks, and infrastructure investments so that high adoption statistics translate into productivity gains, new services, and jobs—not just trophy projects. As Leonhard notes in the interview, “It’s an obvious thing that you want to be a leader in AI and you want to be a leader in digital healthcare and so on, but it’s not that simple. You also need to create a good life in a culture.”
