Strengthening TVTO: Empowerment of Crisis Affected Women Through AI and Digitalization

About this project

In a disaster-stricken setting, women are among the most vulnerable groups, requiring support and assistance to resume and recover their livelihoods. In line with the UNDP’s Leave No One Behind (LNOB) agenda and in order to mitigate the impacts of crisis on women, it is essential to empower their capacities and enhance their resilience through different means including up-to-dated trainings (with a focus on digitalization and AI) and employment opportunities. To achieve this, it is required to strengthen the capacity of the Technical and Vocational Training Organization (TVTO), affiliated to the Ministry of Cooperative, Labour, and Social Welfare (MCLSW), as the custodian organization for vocational trainings nationwide. The cooperation between UNDP, MCLSW, and TVTO for women empowerment will consist of three main components including:• Providing training for TVTO trainers as well as development of standard training content and material on AI and digitalization• Improvement of women target group’s capacity on AI/digitalization and provision of required facilitation for joining the marketplace• Development of a roadmap on mainstreaming AI in TVTO’s trainingFirst and foremost, this initiative is expected to enhance the capacities of TVTO trainers on how to leverage AI and other digital tools for different professions and skills, which enables transfer of practical knowledge to the target groups.Additionally, this initiative expects to provide the required training facilities f…

Goals

Sustainable Development Goals this project works towards

• 4Quality Education

Published by

United Nations Development Programme · Multilateral

Countries

Iran

Sectors

Vocational training

Funded by

GOVERNMENT OF IRAN (ISLAMIC REPUBLIC OF)

Implemented by

UNDP

Accountable

UNITED NATIONS DEVELOPMENT PROGRAMME

Published by United Nations Development Programme to the International Aid Transparency Initiative (IATI), last updated 5 Oct 2026 and imported automatically. IATI identifier: XM-DAC-41114-PROJECT-01006240.

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