With the USAID organization and funding in a quagmire, policymakers in the Global South must find creative and innovative methods to continue investing in their socioeconomic priorities. This is an urgent issue. According to UNESCO’s latest data, there is a concerning reversal in global education access, with 250 million children and adolescents now excluded from formal schooling—a dramatic increase of 6 million since 2021. This regression jeopardizes progress toward Sustainable Development Goal 4, which aims to ensure inclusive and equitable quality education for all by 2030.  

In the Middle East and North Africa (MENA) region specifically, profound inequalities tragically define the education landscape. While a few students have access to well-resourced classrooms with personalized tutoring and state-of-the-art facilities, most school goers face the stark reality of overcrowded classrooms, overextended teachers, and a chronic shortage of learning materials. These disparities constrain the human potential of the region and perpetuates the cycle of disadvantage. 

USAID’s funding cuts highlight a hard truth: external aid cannot provide long-term solutions for underserved communities in the MENA region. But now, with advances in artificial intelligence and machine learning models, there is a possibility of a powerful counter narrative. 

This is demonstrated by the recent project in Nigeria that has the potential to empower self-sufficiency among educators. The program provides instructors an opportunity to use offline AI tools and gives local stakeholders control over digital infrastructure—initiatives that avoid reliance on unstable external donor funding. The program’s success is built on adapting existing resources to local contexts and offers a model that can be applied to other areas. 

Instead of reinforcing dependency, this approach builds long-term independence, allowing education communities to continuously improve their solutions. The outcome is not temporary relief but lasting change, driven by communities themselves to ensure equitable education access. By harnessing these machine learning technologies, countries in the MENA region have a transformative opportunity to democratize education and bridge the persistent divide. 

AI Adaptations for Local Learning

This pilot program, implemented in collaboration with local schools and community organizations, involved 759 students in Nigeria between June and July 2024. It utilized Microsoft Copilot and adaptive learning platforms to provide tailored content based on each student’s progress. Teachers were trained to integrate these tools into their after school sessions, ensuring that the technology complemented, rather than replaced, traditional instruction.      

Students accessed the platform through tablets provided by the program, which were preloaded with content to minimize reliance on internet connectivity—a crucial adaptation for low-resource settings. During six weeks of after school sessions, students used written prompts to interact with the AI, focusing on English grammar, vocabulary, and critical thinking. Teachers supervised the students’ platform engagement, while a digital monitoring system tracked attendance and adapted the program to local challenges like seasonal flooding. Designed for low-tech integration, the program prioritized skill building by leveraging existing devices and internet infrastructure. 

The results are astounding. Test scores jumped by 0.31 standard deviations on an assessment that included English proficiency and digital skills—a gain equivalent to two years of typical learning progress. This outcome is not just about numbers—it is about possibilities. If a program like this can transform learning outcomes in one community, it isn’t a stretch of the imagination to see its potential for other parts of the region.

One of the core strengths of this pilot program is the emphasis on personalized learning. The AI tutors delivered real-time feedback, identified learning gaps, and adapted the pace and content of instruction to meet each student’s unique needs. Such individualized attention is often unattainable in traditional classrooms, especially in low-resource settings with high student-to-teacher ratios. 

It is particularly inspiring to observe how the program addressed gender disparities. Female students, who initially lagged their male peers, showed the most significant improvement. On average, female students improved at nearly double the rate of their male counterparts, narrowing the performance gap and highlighting the role of AI in promoting educational equity.

In future use, this personalized AI approach could boost confidence among female students, encourage deeper academic engagement, and help them overcome societal educational obstacles.  

For boys and girls alike, the program’s outcomes extended beyond academic performance. Surveys conducted among participants revealed increased levels of engagement and confidence in their abilities. Students also reported feeling more motivated to attend school and participate in lessons, while teachers observed a marked improvement in classroom dynamics and student-teacher interactions. 

The positive impact of this project on student engagement, motivation, confidence, and parent satisfaction should serve as a lesson for policymakers on prioritizing the scaling of these programs. 

Complementing Traditional Structures

Far from replacing teachers, AI has the potential to empower them. By automating routine administrative tasks such as grading and attendance tracking, AI frees educators to focus on what they do best: teaching. Instructors in the pilot program used AI tools to gain insights into their students’ performance, enabling them to tailor lessons more effectively. For example, if several students struggled with fractions, the teacher could adjust the curriculum accordingly. Furthermore, AI can serve as a professional development tool for educators, offering real time feedback on teaching methods and access to a wealth of instructional resources. When teachers are equipped with the right tools and training, the possibilities are endless.

For most resource-constrained settings, access to high-quality educational materials is still inaccessible. AI-powered platforms can change this by providing students with a vast digital library of resources, from interactive simulations to virtual field trips, accessible anytime, anywhere. By democratizing access to knowledge, machine learning models can help level the playing field for learners in the Global South. The success of this pilot offers a roadmap for replicating this model in other resource constrained settings. At the same time, scaling such initiatives requires addressing several critical challenges. Reliable access to technology and the internet is a prerequisite for these programs. State agencies, non-governmental organizations, and private sector partners must invest in infrastructure and digital literacy programs to ensure equitable access. 

Educators need comprehensive training to integrate these technologies effectively into their teaching. Professional development programs must emphasize digital literacy, pedagogical innovation, and the ethical use of AI. Issues like data privacy, algorithmic bias, and potential misuse of technology must be proactively addressed. Robust ethical frameworks are also essential to ensure that AI promotes inclusion and equity rather than exacerbating existing disparities. The goal is not to merely adopt new technologies but to fundamentally reimagine education as it is practiced today. By leveraging AI thoughtfully and inclusively, we can turn this vision into reality — building a future where education is not a privilege but a right for all.