EDSAFE AI Alliance 2026 Women in AI Fellowship

If you’re a woman working in education, edtech, policy, or advocacy — especially with a passion for how AI can support learners in equitable and meaningful ways — the EDSAFE AI Alliance 2026 Women in AI Fellowship offers a unique platform to grow, connect, and lead. Applications are open now, and here is a full guide to help you understand, prepare, and succeed.

🎓 Fellowship Summary

• Location: Virtual with at least one in-person gathering (global, remote format)

• Organizer: EDSAFE AI Alliance (InnovateEDU)

• Program Type: Year-long Fellowship (Women in AI cohort)

• Target Group: Women professionals in education, technology, policy, advocacy, or related fields

• Thematic Areas: AI in education through a lens of equity, ethics, and the SAFE (Safety, Accountability, Fairness, Efficacy) framework

• Duration: 1 year, including workshops, mentorship, cohort learning, and a capstone project

• Coverage: Fellowship is offered to participants at no cost (i.e. no participation fee) — the public information does not clearly indicate whether stipends or salary support are included

• Application Deadline: November 30, 2025, at 10 p.m. EST

• Announcement / Start: Fellows will be announced in January 2026

  
  

🌐 Program Overview & Structure

The Women in AI Fellowship is intentionally designed to create a supportive, collaborative space for women in the overlapping domains of AI, education, and policy.

Key components include:

1. Interactive Learning & Workshops

   Fellows engage in virtual sessions led by experts in AI ethics, safety, governance, education, and policy. The curriculum is anchored around the SAFE framework—Safety, Accountability, Fairness, Efficacy—and includes both foundational and emergent topics in AI and learning systems.

2. Cohort & Mentorship

   You’ll join a cohort of peers (often around 30, similar to other EDSAFE cohorts) to share insights, challenge assumptions, and learn together. Past Women in AI Fellows and other leaders serve as mentors and guides.

   The fellowship includes at least one in-person gathering to strengthen relationships and deepen shared learning.

3. Applied Capstone Project

   At the end (or toward the end) of the fellowship, each fellow will design and carry out a micro capstone or “problem of practice” in her own context. This project is intended to be directly relevant: whether enhancing AI literacy in schools, building data governance tools, designing equitable access systems, or promoting privacy and ethics.

4. Community, Networking, & Impact

   Beyond learning and project work, fellows join a network of women leaders in AI and education. They co-create knowledge, exchange resources, and amplify underrepresented voices in AI policy and education discourse.

🎁 Benefits & What You Gain

If selected, as a Women in AI Fellow you can expect to receive:

• Expert Access & Learning: Deep exposure to leaders and thinkers in AI ethics, safety, policy, and educational innovation

• Mentorship & Support: Guidance from past fellows and domain experts

• Peer Community: A cohort of women with shared interests, challenges, and ambition

• Real-World Application: A capstone project allowing you to test and enact practical, context-specific AI solutions

• Voice & Influence: Platform to share your insights, influence policy conversations, and contribute to the global field

• Professional Growth: Enhanced skills in leadership, AI strategy, ethics, and policy

✅ Eligibility Criteria & What They Look For

• Identify as a Woman in AI / Education / Tech / Policy: The fellowship is explicitly for women (self-nominations allowed)

• Active or Aspiring Influence: You should already be engaged (or intend to be engaged) in domains like education, edtech, research, policy, or advocacy, ideally with potential to deploy your work locally

• Alignment with SAFE Principles: Your values, proposals, or prior work should indicate interest in safety, fairness, accountability, and efficacy in AI systems

• Contextual Leverage: Preference likely for those who can implement change or pilots in their environments (schools, district, NGOs, edtech)

• Collaborative & Learning Mindset: Because this is cohort-based, applicants who show openness to peer learning, diversity, iteration, feedback, and collective work are strong fits

• Capacity & Commitment: You need sufficient bandwidth and institutional or structural ability to carry out your capstone

• Compelling Vision / Problem Focus: Your proposed project or trajectory should be clearly articulated, relevant, and impactful

📝 Application Procedure

1. Application / Nomination Form

   EDSAFE invites self-nominations or third-party nominations. The form asks for name, affiliation, country, sector of engagement, examples of work, LinkedIn/social profile, a statement of fit, and leadership / AI & education examples. Apply here

2. Personal / Vision Statement (250 words or so): Explain why you are a strong candidate: your passion for AI in education, your alignment with the Women in AI mission, and how you will leverage the fellowship to effect change.

3. Project / Leadership Example: Describe past initiatives you have led (even small) in AI / education, with links or artifacts if available.

4. Institutional or Organizational Context: Indicate your current role, affiliation, or workplace, and how your environment could support or benefit from your fellowship work.

5. Supporting Document: This may include CV/resume, portfolios, project reports, recommendation letters or endorsements (if requested).

6. Submit Before Deadline:;Applications must be submitted by November 30, 2025, at 10 p.m. EST — no late submissions accepted.

👌🏻 Tips & Strategies to Strengthen Your Application

• Ground your project idea in a clear problem of practice — what challenge in your local educational or policy context you want to address

• Use the SAFE framework language in your proposal (safety, accountability, fairness, efficacy) to show you understand the fellowship’s ethos

• Demonstrate how you will sustain or scale your work beyond the fellowship

• Highlight collaborative or cross-context thinking: how insights from other fellows or global contexts might enrich your local work

• Provide concrete indicators / outcomes: how will you know your intervention has worked?

• Show institutional buy-in / feasibility: what support or pathway you have in your context (school district, NGO, policy office)

• Prepare any recommendation or referral early — guide referees to emphasize leadership, alignment with women in AI, and your project ambitions

🔗 Apply Now

🔗 Official Website

---