AI ambitions outpace data readiness in MEA
IBM study reveals growing gap between AI goals and ability to implement
#MiddleEast #sentiment - Chief Data Officers across the Middle East and Africa are racing to scale artificial intelligence capabilities whilst confronting a widening gap between ambition and readiness, according to a new study by US technology company IBM’s Institute for Business Value. The research reveals 77 percent of surveyed MEA data leaders prioritise investments that accelerate AI capabilities, yet only 25 percent express confidence their data can support new AI-enabled revenue streams. Advanced data skills have emerged as the top challenge for 54 percent of respondents, nearly doubling from 28 percent in 2023.
SO WHAT? - IBM’s findings expose a critical gap at the heart of the Middle East and Africa’s AI transformation. Whilst organisations are moving rapidly from pilots to deployment, fundamental barriers around data accessibility, integrity and talent prevent many from capturing AI’s full economic potential. The near-doubling of skills concerns in just two years suggests the talent gap is growing faster than many anticipated, potentially constraining the pace at which MEA organisations can operationalise AI initiatives and generate competitive advantage.
Here are some key points from the research:
There is a widening gap between AI ambition and readiness among organisaitons in the Middle East and Africa (MEA), according to a new study by the IBM Institute for Business Value.
The institute surveyed 1,700 Chief Data Officers and senior data leaders worldwide across 27 geographies and 19 industries between July and September 2025, providing insights into how enterprise data strategies are evolving amid the AI transformation.
Three-quarters (76%) of MEA Chief Data Officers report their organisation’s data strategy is now integrated with technology roadmap and infrastructure investments, rising from 55% in 2023, yet only 27% are confident their organisations can use unstructured data to deliver business value.
Deploying data for competitive advantage has become the top priority for MEA data chiefs, overtaking governance and actionable insights as core responsibilities, with 78% reporting their unique data products have already provided significant competitive advantages to their organisations.
The talent challenge has intensified dramatically, with 79% of surveyed MEA leaders struggling to fill key data roles and only 51% saying recruitment efforts deliver needed skills and experience, down from 66% in 2024.
Despite readiness concerns, 75% of MEA respondents believe potential benefits of deploying AI agents outweigh risks, and 70% are comfortable with their organisations relying on outcomes from AI agents.
Data democratisation is gaining traction, with 72% of MEA data chiefs saying it helps their organisation move faster and 64% believing data is wasted without broad employee access.
The study reveals only 28% of MEA respondents strongly agree they can clearly convey how data facilitates business results, and just 27% have clear measures to determine the value of data-driven business outcomes.
To address the AI-data gap, 75% of MEA Chief Data Officers say they bring AI to data rather than centralising it, whilst 68% have started developing diverse datasets to train AI agents.
ZOOM OUT - Overall, the 2025 CDO study’s global findings reveal a fundamental shift in how enterprises approach data strategy, with 81 percent of Chief Data Officers worldwide now prioritising investments that accelerate AI capabilities. Organisations are allocating 13 percent of IT budgets to data strategy, up from just 4 percent in 2023, whilst 75 percent have established data platforms enabling integration across silos. Yet only 26 percent globally express confidence their data capabilities can support AI-enabled revenue streams.
[Written and edited with the assistance of AI]
The skills gap doubling from 28% to 54% in just two years is really alarming. It shows that while compaines are moving fast on AI adoption, the talent pipline simply cant keep up. The focus on bringing AI to data rather than centralizing it makes sense given the distributed nature of modern enterpise architectures. It will be intresting to see if MEA organizations can solve this through partnerships with universities or if they need to look at reskilling existing workforces.