LBN-001

ILO PROSPECTS Lebanon – SkillLab AI Skills Profiling for Refugees and Host Communities

Download PDF
Lebanon Middle East, North Africa, Afghanistan & Pakistan Lower middle income Pilot / Controlled Trial Phase Confirmed

International Labour Organization (ILO) Lebanon; implementing partners: Caritas Lebanon, AVSI, Safadi Foundation, The Lee Experience

At a Glance

What it does Classification — Matching and recommendation
Who runs it International Labour Organization (ILO) Lebanon; implementing partners: Caritas Lebanon, AVSI, Safadi Foundation, The Lee Experience
Programme ILO PROSPECTS Lebanon – SkillLab Skills Profiling Pilot
Confidence Confirmed
Deployment Status Pilot / Controlled Trial Phase
Key Risks Market, sovereignty and industry structure risks
Key Outcomes 500 Lebanese and Syrian individuals profiled across three Caritas centres; participants reported recognising previously unarticulated skills; professionally formatted multilingual CVs auto-generated; referrals to TVET, apprenticeships, and MSME employment; career counsellors transitioned from one-on-one to group sessions with maintained quality.
Source Quality 5 sources — Other, Report (multilateral / development partner), Government website / press release

The International Labour Organization (ILO), through its PROSPECTS programme in Lebanon funded by the Government of the Netherlands, has piloted the SkillLab mobile application to deliver AI-driven skills profiling, career orientation, and job-application support to vulnerable Lebanese nationals and Syrian refugees. The PROSPECTS programme itself has been operational in Lebanon since January 2019 and is scheduled to run until December 2027, with career guidance and employment services delivered through implementing partners including Caritas Lebanon, AVSI, the Safadi Foundation, and The Lee Experience. The SkillLab component was introduced as a digitalisation initiative within this broader programme framework, with first references appearing in ILO reporting from May 2022.

SkillLab is a Netherlands-based social venture that has developed a technology platform employing multiple machine learning algorithms written in Python. The platform's core function is an AI-based skills assessment engine that determines which competences to query and adapts the duration and content of the assessment based on user responses. The system is built on the European Skills, Competences, Qualifications and Occupations (ESCO) ontology, which contains 13,485 unique skills mapped to 2,942 occupations. Through the assessment process, the engine captures an individual's employable skills gained through professional, educational, and informal learning experiences, automatically generates and translates comprehensive skill profiles, and maps each person's unique skill set directly to occupations and career pathways. The platform supports 27 languages during assessment with automatic translation of outputs into host-country languages, a feature particularly relevant in the Lebanese context where beneficiaries include Arabic-speaking Syrians and Lebanese alongside other language groups.

The system architecture follows a microservices approach. The mobile application is built in React and is available on the Google Play Store, Apple App Store, and as a web application. A separate React-based web interface serves career counsellors and employment service providers. The skill assessment engine operates as a Python-based machine learning service, while the backend infrastructure runs on Ruby on Rails hosted on Google Cloud Platform. These components are connected via APIs. SkillLab won the Google AI Impact Challenge and received support through the Google SDG Accelerator programme, which contributed to its technical development.

In the Lebanon implementation, Caritas Lebanon served as the primary implementing partner for the Akkar and North Lebanon regions. Caritas supported 500 Lebanese and Syrian individuals across three centres with a programme budget of USD 250,000 over a 10-month period during 2023-2024. The programme activities included SkillLab profile creation, career counselling sessions, awareness training on decent work conditions, on-the-job training, technical and vocational education and training (TVET), and apprenticeship placements. Training was delivered in groups of 25 participants across five sessions covering SkillLab onboarding, skills importance in employability, career counselling, interview preparation, personal development, and workplace rights. Participants were subsequently referred to TVET programmes, apprenticeships, or micro, small and medium enterprise employment opportunities, with graduates expected to receive Ministry of Education certificates plus Safadi Foundation accreditation.

The SkillLab tool enabled participants to identify previously unarticulated skills, generate professionally formatted and internationally standardised CVs in multiple languages, receive AI-generated career recommendations matched to their skill profiles, and understand skills gaps relative to desired career pathways. Career counsellors at Caritas reported that the tool facilitated a transition from one-on-one counselling sessions to more efficient group-based sessions while maintaining quality of career guidance. An earlier phase under the PROSPECTS programme, between March 2021 and February 2022, had supported around 40,000 severely vulnerable Syrian refugee families with multi-purpose cash assistance, alongside which 370 beneficiaries received skills and entrepreneurship training delivered under the Norwegian government-supported Skill-Up Phase II and the Dutch-funded PROSPECTS projects.

Lebanon hosts approximately 1.5 million Syrian refugees, representing the highest per capita concentration of refugees globally. The country has been classified as a fragile and conflict-affected situation by the World Bank, and a November 2024 World Bank report estimated the cost of physical damages and economic losses due to conflict at USD 8.5 billion, with real GDP growth cut by at least 6.6 percent in 2024. This context of economic crisis and large-scale displacement makes digital employment services and AI-driven skills matching particularly relevant for facilitating labour market integration of both refugee and host community populations.

Classifications follow the DCI AI Hub Taxonomy. Hover over field labels for definitions.

Social Protection Functions

Implementation/delivery chain
Profiling, job matching and support services primary
SP Pillar (Primary) The social protection branch: social assistance, social insurance, or labour market programmes. Labour market programmes
Programme Name ILO PROSPECTS Lebanon – SkillLab Skills Profiling Pilot
Programme Type The type of social protection programme, classified under social assistance, social insurance, or labour market programmes. View in glossary Job search assistance and placement services
System Level Where in the social protection system the AI is applied: policy level, programme design, or implementation/delivery chain. View in glossary Implementation/delivery chain
Programme Description Component of the Dutch-funded ILO PROSPECTS programme (2019–2027) delivering AI-driven skills profiling, career orientation, and job-application support to vulnerable Lebanese nationals and Syrian refugees through the SkillLab mobile application, implemented by Caritas Lebanon, AVSI, Safadi Foundation, and The Lee Experience.
Implementation Type How the AI output is produced: Classical ML, Deep learning, Foundation model, or Hybrid. Affects validation, compute requirements, and governance profile. View in glossary Classical ML
Lifecycle Stage Current stage in the AI lifecycle, from problem identification through to monitoring, maintenance and decommissioning. View in glossary Integration and Deployment
Model Provenance Origin of the AI model: developed in-house, adapted from open-source, commercial/proprietary, or accessed via third-party API. View in glossary Commercial/proprietary
Compute Environment Where the AI system runs: on-premise, government cloud, commercial cloud, or edge/device. View in glossary Commercial cloud
Sovereignty Quadrant Classification of data and compute sovereignty: I (Sovereign), II (Federated/Hybrid), III (Cloud with safeguards), or IV (Shared Innovation Zone). View in glossary IV — Shared Innovation Zone
Data Residency Where the data used by the AI system is stored: domestic, regional, or international. View in glossary Not documented
Cross-Border Transfer Whether data crosses national borders, and if so, whether documented safeguards are in place. View in glossary Not documented
Decision Criticality The rights impact of the decision the AI supports. High criticality requires HITL oversight; moderate requires HOTL; low may operate HOOTL. View in glossary Low
Human Oversight Type Level of human involvement: Human-in-the-Loop (active review), Human-on-the-Loop (monitoring), or Human-out-of-the-Loop (periodic audit). View in glossary HITL
Development Process Whether the AI system was developed fully in-house, through a mix of in-house and third-party, or fully by an external provider. View in glossary Fully third-party developed
Highest Risk Category The most significant structural risk source identified: data, model, operational, governance, or market/sovereignty risks. View in glossary Market, sovereignty and industry structure risks
Risk Assessment Status Whether a formal risk assessment, informal assessment, or independent audit has been conducted for this system. Not assessed

Risk Dimensions

Data-related risks
Governance and institutional oversight risks

Impact Dimensions

Autonomy, human dignity and due process
Systemic and societal
  • Human oversight protocol
CategorySensitivityCross-System LinkageAvailabilityKey Constraints
Unstructured and text-based contentPersonalSingle source (no linkage)Currently available and usedSelf-reported skills data from user assessments; quality depends on user input accuracy and ESCO ontology coverage of local occupational contexts

Caritas Lebanon (2024) 'ILO Prospects – Integrating Career Guidance and Employment Services in Akkar and North Lebanon', Caritas Lebanon Programme Page. Available at: https://caritas.org.lb/program/ilo-prospects-integrating-career-guidance-and-employment-services-in-akkar-and-north-lebanon/ (Accessed: 24 March 2026).

View source Other

International Labour Organization (2022) 'Steps towards digitalizing skills system in Lebanon', ILO News, 26 May 2022. Available at: https://www.ilo.org/resource/article/steps-towards-digitalizing-skills-system-lebanon (Accessed: 24 March 2026).

View source Report (multilateral / development partner)

International Labour Organization (2024) 'Partnership for improving prospects for forcibly displaced persons and host communities (PROSPECTS) in Lebanon', ILO Programme Page. Available at: https://www.ilo.org/prospectslebanon (Accessed: 24 March 2026).

View source Report (multilateral / development partner)

MIT Solve (2020) 'SkillLab – Overview', MIT Solve T-Prize Challenge, March 2020. Available at: https://solve.mit.edu/challenges/TPrize/solutions/18144 (Accessed: 24 March 2026).

View source Other

SkillLab (2025) 'Enhancing Job-Seekers Work-Readiness in Lebanon Using the Language of Skills', SkillLab News, January 2025. Available at: https://skilllab.io/en-us/news/enhancing-job-seekers-work-readiness-in-lebanon (Accessed: 24 March 2026).

View source Government website / press release
Deployment Status How far the system has progressed into real-world operational use, from concept/exploration through to scaled and institutionalised. View in glossary Pilot / Controlled Trial Phase
Year Initiated The year the AI system was first initiated or development began. 2022
Scale / Coverage The scale and geographic or population coverage of the deployment. 500 beneficiaries across three centres in Akkar and North Lebanon (Caritas component); 370 beneficiaries in earlier Skill-Up/PROSPECTS training phase
Funding Source The source(s) of funding for the AI system development and deployment. Government of the Netherlands (PROSPECTS programme); Norwegian government (Skill-Up Phase II)
Technical Partners External technology vendors, academic partners, or development partners involved. SkillLab (Netherlands)
Outcomes / Results 500 Lebanese and Syrian individuals profiled across three Caritas centres; participants reported recognising previously unarticulated skills; professionally formatted multilingual CVs auto-generated; referrals to TVET, apprenticeships, and MSME employment; career counsellors transitioned from one-on-one to group sessions with maintained quality

How to Cite

DCI AI Hub (2026). 'ILO PROSPECTS Lebanon – SkillLab AI Skills Profiling for Refugees and Host Communities', AI Hub AI Tracker, case LBN-001. Digital Convergence Initiative. Available at: https://socialprotectionai.org/use-case/LBN-001 [Accessed: 1 April 2026].

Change History

Created 30 Mar 2026, 08:40
by v2-import (import)