FEATURE
Ahmed Al-Anqari, CEO of Etihad Salam Telecom Company
Federico Pienovi, CEO of MENA & APAC at Globant
There is growing evidence that Middle East enterprises are moving beyond the exploratory phase of AI adoption, although progress remains uneven.
Ahmed Al-Anqari, CEO of Etihad Salam Telecom Company( Salam), believes organisations are becoming increasingly focused on tangible outcomes rather than technical demonstrations.
" The ambition for digital transformation across the Middle East is undeniable, but execution remains a critical factor in translating that ambition into measurable outcomes," he said.
According to Al-Anqari, enterprises are no longer satisfied with proofs of concept that demonstrate technical feasibility but fail to deliver production value. Instead, they are seeking technology partners capable of helping them deploy AI across operations while addressing connectivity, cloud infrastructure, cybersecurity and business continuity requirements.
This represents a significant change in expectations. Rather than procuring individual technologies, organisations increasingly want integrated solutions that can support longterm transformation.
Federico Pienovi, CEO of MENA & APAC at Globant, sees similar momentum across the GCC, where investment, regulatory developments and infrastructure expansion are creating favourable conditions for AI deployment.
However, he cautioned that ambition should not be confused with operational maturity.
Research cited by Pienovi suggests that roughly half of GCC organisations are still piloting AI in selected functions, while only 1 % consider themselves fully equipped to adopt the technology at scale.
He also pointed to global research indicating that many AI initiatives fail to generate meaningful business value, often because organisations lack the execution frameworks needed to translate experimentation into operational results.
For Pienovi, the distinction lies in measuring AI through governed business outcomes rather than the number of capabilities deployed.
Haider Amjed, Head of Technology for the UAE at NTT DATA, believes the UAE and wider GCC are making progress towards production-grade AI.
National strategies, executive sponsorship and sustained infrastructure investment are helping accelerate adoption across government services, financial institutions, healthcare and industrial operations.
" The next phase is not about proving that AI works; it is about industrializing what works through reusable platforms, governance, integration patterns and talent," he said.
For CIOs, this means shifting attention from individual use cases towards the underlying capabilities required to deploy AI repeatedly and reliably.
Breaking down the barriers to scale
Moving AI across multiple business functions introduces challenges that are often less about the sophistication of algorithms and more about enterprise complexity.
Large organisations typically operate diverse technology environments, with different departments maintaining separate applications, datasets, processes and governance requirements.
A pilot developed within one business unit may perform successfully in isolation but encounter significant obstacles when integrated with enterprise systems.
Arturo Buzzalina, Chief Product and Innovation Officer at Epicor, said fragmentation remains one of the biggest barriers to scaling AI.
" The biggest challenge isn ' t the technology itself; it ' s moving beyond isolated use cases and embedding AI into core business processes," he said.
According to Buzzalina, organisations must align people, processes, data and governance to create a consistent AI strategy. This requires treating AI as an enterprise capability rather than allowing departments to develop disconnected solutions.
Al-Anqari believes the complexity is compounded by the number of technology providers involved.
Many enterprises continue to manage separate relationships with connectivity vendors, cloud providers, cybersecurity specialists and AI companies, even as the boundaries between these technologies become increasingly blurred.
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