The MENA AI landscape appears to be vibrant, with many entities catalyzing smart technologies for digital transformation. Moreover, AI is predicted to have a considerable impact on the region’s economy, across all sectors and labour market, fueling $320 billion in the next decade.
At present however, a scarce amount of sources exist on what constitutes the AI MENA landscape. There have been efforts to bring together the pan-Arab AI community in conferences such as the Arab AI Summit hosted in Jordan in 2019, the Arab IOT and AI Challenge hosted in Egypt. But details about key players and entities, policies and research that revolve around AI are sparsely documented. In order to fully exploit the potential of existing capacities and understand gaps in practices, it is essential to map this ecosystem.
While this is not meant to be an exhaustive map, we do aim to capture essential data to encourage future work. We hope this snapshot will be a first step from which we can foster a stronger understanding of how AI is being leveraged in the region.
You can find the full written report here.
In this mapping, we cover the Arabic-speaking countries in the MENA region. According to the United Nations Office of the High Commissioner of Human Rights (UNOHCHR), the MENA region consists of 19 countries of which 17 are Arabic-speaking. We study the below 17 countries:
- Algeria
- Bahrain
- Egypt
- Iraq
- Jordan
- Kuwait
- Lebanon
- Libya
- Morocco
- Oman
- Palestine
- Qatar
- Saudi Arabia
- Syria
- Tunisia
- UAE
- Yemen
This mapping includes:
- Industry: entities who develop or specialize in AI, for profit
- Government: entities who engage in AI policies
- Civil society: entities who question AI and AI policies
- Education and research: entities who engage in AI research or capacity building
- Funding: entities who fund AI initiatives, directly or indirectly
TBA
Distributed under the CCO license. See LICENSE for more information.
- Email: info (at) jordanopensource (dot) org
- Twitter: @jo_osa
- Data for Tunisian institutions have been developed thanks to the special contributions of Data Engineering and Semantics Research Unit, University of Sfax with the collaboration of the Technopark of Sfax and the Ministry of Higher Education and Scientific Research, Tunisia.