DISRUPTIVE TECH
Artificial Intelligence that is Open- Source, freely available for use, study, modification and sharing, has been the focus of interest of insiders and ordinary citizens for quite some time now. In recent weeks, attention on the topic has increased exponentially, with concerns over the latest DeepSeek updates and a surge of interest in Middle Eastern initiatives from entities such as G42 in the UAE and STC in Saudi Arabia, as the region seeks to keep pace with established Chinese and U. S. models.
Homegrown efforts like Falcon, Fanar, and Jais are placing the region firmly on the global AI development map. At the regional level, institutions like the Mohammed Bin Zayed University of Artificial Intelligence, MBZUAI have launched specialised AI programmes and large language models, while other players across the GCC are deploying advanced solutions on locally operated architectures.
Although the emergence of new players in the market reinforces some existing complexities, related for example to the quality and protection of the information they use, there are advantages arising from this competitive landscape, and companies in the Middle East should be ready to recognise.
Regardless of their level of maturity with respect to AI adoption, organisations should be aware of the new scenarios that the latest developments in the field are shaping. Given the broad potential of Generative AI, advancements that make adoption easier and more secure should be embraced, especially by organisations navigating complex data environments.
But what, in detail, are these benefits?
Cost reduction
Although Generative AI has tremendous transformational potential, its development and management costs have, to date, held many organisations back from using it. Against this backdrop, any technical advances that enable its adoption to be simplified and the associated expenses to be contained should be seen as beneficial to companies interested in implementing it in the Middle East, particularly those aiming to optimise costs while pursuing large-scale digital transformation.
Increased efficiency
Energy demand has grown by 14 % in the past 10 years, and it is predicted that, on the back of AI, data centre electricity consumption in 2026 will be double what it was in 2022, according to data from International Energy Agency.
In short, the issue of AI sustainability is not secondary.
Compared to more established solutions, DeepSeek has a strong focus on efficiency and is based on the Mixture-of-Experts, architecture: this allows only a subset of its parameters to be activated during calculations, thereby reducing consumption without compromising performance quality.
In the Middle East, where energy resources are a key economic driver, the push for efficient AI aligns with many national strategies targeting sustainable growth and reduced carbon footprints.
Technological progress
For those who have faith in innovation, another of the benefits of the race to Open Source AI is the democratisation of technological progress: for example, by open-sourcing the R1 LLM code, DeepSeek has enabled further improvements to the model by engineers and AI scientists from around the world.
For that matter, the source code of the R1 LLM model is to date already available from several other providers, including AWS and Azure. This collaborative momentum resonates with technology ecosystems in Dubai, Riyadh, and Abu Dhabi where governments are investing heavily in Open-Source communities, startup incubators, and cloud-native development frameworks.
Flagship initiatives such as the UAE’ s Falcon, developed by TII, Jais, created by G42 and MBZUAI, Qatar’ s Fanar, and Saudi Arabia’ s ALLaM model are reshaping the narrative, positioning the Middle East not only as an AI adopter, but as a serious contributor to global AI innovation.
In the context just outlined, however, there is no shortage of complexities-especially those related to information management.
According to a recent Gartner study, 30 % of Generative AI projects will be abandoned by the end of 2025 precisely because of poor data quality and other factors, such as inadequate risk controls, rising costs or unclear business value. Organisations in the Middle East, from government agencies to private enterprises, must similarly ensure that robust data governance supports AI initiatives.
Gabriele Obino, Regional VP Sales, Southern EMEA and ME, Denodo
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