This hackathon serves as the first among the ITU AI Readiness hackathon series. AI Readiness aims to measure the ease and ability of reaping benefits from the integration of AI in various domains and use cases. In 2024, ITU published version 1.0 of AI Readiness report, identifying 6 key foundational factors to measure AI Readiness. In 2026, ITU published version 2.0 of AI Readiness report, and identified 13 more dimensions with detailed metrics mapped to the 6 key factors. ITU is also designing the AI-RE (AI Readiness Enablement) Toolkit, a dynamic model that can help in providing customized dimensions, indices, and metrics based on user input. A primary component of the toolkit is a Knowledge Base (KB), allowing customizations based on granular priorities.
Objective
The objective of this hackathon is to harness crowdsourced inputs and actively involve vast communities, including students, researchers, and professionals, in building AI-Ready use cases aligned with ITU standards in various domains.
Tasks for participants
- Participants are required to design, submit use cases and authentic materials in education, agriculture, health, and finance domains, aligning with ITU-T Y.3172 machine learning pipeline, and reflect factors and dimensions identified in the ITU AI Ready reports.
- Participants are also required to collect and curate national AI-related policy papers (with reference link) to contribute to the ITU AI Readiness knowledge base.
Participants will closely work with the ITU AI-RE Toolkit, contributing domain-specific knowledge base to AI Readiness.
The hackathon is open for all. A team is formed with a maximum of 4 members.
Timeline
- 1 May – 10 July
Registration for hackathon and use case title submission - 10 July – 31 August
Weekly mentoring session - 31 August
Deadline for submission - 7 September
Announcement of shortlisted teams - 14 September
Final evaluation, Riyadh
Evaluation Criteria
The use cases will be evaluated based on the following criteria:
- Clear description of use case with respect to ITU T Y.3172 machine learning pipeline
- Clear mapping to ITU AI Readiness factors and dimensions
- Contribution to knowledge base, reviewed by ITU experts
- Input to AI strategies and policies, reviewed by policymakers and dignitaries
Note: Participants are required to submit the reference links to materials proposed to the knowledge base.
Benefits
This hackathon provides an opportunity for participants to collaborate globally, in creating a shared AI knowledge infrastructure and to win exciting prizes.
Monetary incentives: USD 3,000
- First prize: USD 1,200
- Second prize: USD 800
- Third prize: USD 500
- Women’s prize: USD 500
Note: Only teams with a lady leader are eligible for the Women’s prize.
Winners
- First prize: Team SANAD
- Second prize: Team AI Guardian
- Third prize: Team Samaam
- Special Women’s prize: Team Nakheel Doctor
Mentoring session: Participants will work closely with ITU experts in drafting and polishing the use cases. Mentoring sessions will be provided weekly up till the event.
Contribution to international standardization building efforts: Use case submission could have the opportunity to be integrated into ITU Study Group or Focus Group.
