NCEILEBANON pledges support for a National AI Strategy in Lebanon , launches 961ai Network

NCEILEBANON pledges support for a National AI Strategy in Lebanon , launches 961ai Network

The National Council for Entrepreneurship and Innovation in Lebanon (NCEILebanon) hosted a landmark seminar, on AI for a National Strategy in Lebanon, as an introduction to NCEILebanon AI Initiative

The event brought together government officials, academic leaders, and industry experts to lay the groundwork for Lebanon’s comprehensive national AI strategy.

To note that NCEILebanon has officially launched its National AI Initiative, reaffirming its commitment to nurturing startups focused on artificial intelligence solutions for public governance.

Central to this initiative is the 961AI Network, an ambitious platform designed to unite Lebanon’s largest community of AI innovators, entrepreneurs, and tech enthusiasts. Through these efforts, NCEILebanon reiterates its dedication to boosting the country’s startup ecosystem and positioning Lebanon as a regional leader in AI-driven public sector transformation.

The seminar opened with a keynote address, “AI for National Progress: A Vision for Lebanon,” followed by presentations on the government’s AI policy roadmap and national governance strategy. These sessions will focus on strategic objectives such as security, economic growth, governance, and digital infrastructure.

The opening session on “AI for Public Governance: Supervision and Governance”  featured Dr. Manal Abdel Samad Najd, former Minister of Information and Senior Advisor, discussing AI’s role in enhancing fiscal transparency, tax administration, and anti-corruption. Maan Barazy, President of NCEILebanon, presented the state of the AI Ecosystem in Lebanon, its frameworks for AI governance, including the AIGP Certification, NIST AI Risk Management Framework, and ISO/IEC 42001 standards. NCEILebanon presented a research on  AI INDEX Application to Lebanon, developing a comprehensive state-of-AI report for Lebanon, detailing market size, development and adoption levels, as well as our capacity for future advancements.

In another session the seminar spotlighted AI in academia, with Dr. Shehayeb presenting on AI-driven mapping and analytics for resource management and climate resilience. The presentation highlighted how to bridge this gap,through RESOLVE project, led by ESDU at AUB  which aims to establish an interactive AI-driven map that will provide real-time insights into Lebanon’s natural resources and agricultural practices. By leveraging geospatial mapping, remote sensing, and AI analytics, this tool will predict resource availability, identify areas at risk of depletion, and support policymakers, farmers, and donors in making informed decisions. The map will integrate key datasets, including soil health, water availability, agricultural biodiversity, and regenerative farming practices, offering a comprehensive decision-support system for sustainable resource management.

The event continued with a session on building Lebanon’s AI ecosystem, moderated by Mr. Maan Barazy. This segment will explore the application of the global AI Index to Lebanon and strategies for advancing the country’s AI ranking. Contributions from Dr Rabih Baalbaki President EdTech Syndicate in Lebanon, Co-Founder MENA EdTech Alliance, President at Lebanese Association for IT Professionals, Board Member at PCA, Digital & Governance Transformation Network of Lebanon, and Dr Noura Merhebi - EdTech Expert  and e-Governance Advisor , Techwomen Emerging Leader 2024. The session highlighted the importance of research, innovation, and mentorship in the sector.

The agenda has also introduced many pioneer startups, mainly aresearch presentation by Mrs. Elma Abou Raffoul will examine machine learning models for predicting consumer behavior in e-commerce, demonstrating the effectiveness of Random Forest classifiers in improving purchasing intent predictions. This research investigates the use of machine learning to predict purchasing intent on e-commerce platforms, aiming to reduce bounce rates and abandoned sessions. Utilizing a dataset of approximately 12,000 user sessions, the study analyzes behavioral features such as session duration, page views, and visitor status. To address class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was employed. Three machine learning models were evaluated: k-Nearest Neighbors, Random Forest, and Logistic Regression.

A panel on  “AI for Smart Cities,” featured case studies from Afif Tabsh on AI adoption in Lebanon’s social impact sector, and Dr. Wassim Katerji on the integration of AI in GIS and remote sensing.

Dr Katergi study highlighted a case study which highlighted  into the transformative impact of artificial intelligence on Geographic Information Systems (GIS) and Remote Sensing. By integrating AI technologies such as machine learning, deep learning, and predictive analytics, these fields are experiencing unprecedented advancements in efficiency, accuracy, and innovation.

To note that NCEILebanon will follow up closely National AI Initiative and the 961AI Network which  are transformative steps towards uniting Lebanon’s innovators and fostering a dynamic, collaborative, and ethical AI ecosystem.

To date NCEILebanon has emerged as a visionary force in shaping the country's technological policies and fostering collaboration. Beyond its past role in drafting the government's digitalization program and studying patient trends, the center has launched a groundbreaking initiative to establish Lebanon's national AI policy. This effort seeks to define the ethical, strategic, and regulatory framework for artificial intelligence deployment across sectors. Through this initiative, NCEILebanon is working tirelessly to unite diverse stakeholders, including government entities, private sector leaders, academic institutions, and civil society, in a shared vision for AI adoption. By encouraging dialogue and fostering partnerships, the center aims to ensure that the AI policy reflects both national priorities and international best practice

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