Adaptive Artificial Intelligence Models for Enhancing Digital Inclusion and Sustainable Development in Underserved Communities

Technology is playing a vital role across various sectors like education, healthcare, agriculture, financial services, employment, governance, and social development. However, we still see significant digital inequalities, especially in underserved communities, particularly in rural and low-income areas. Here, challenges such as limited connectivity, high technology costs, lack of digital skills, language barriers, and inaccessible digital services hinder meaningful participation in the digital economy. This conceptual paper delves into how adaptive Artificial Intelligence (AI) models can boost digital inclusion and support sustainable development in these communities. It brings together insights from literature on artificial intelligence, digital inclusion, adaptive learning, responsible AI, and sustainable development. The paper introduces the Adaptive AI Digital Inclusion and Sustainable Development (AIDISD) framework, which is built around five key dimensions: accessibility, personalization, contextual adaptation, resource efficiency, and community empowerment. It explores potential applications in education, healthcare, agriculture, financial inclusion, employment, and public services. Additionally, the paper highlights challenges related to infrastructure, data scarcity, algorithmic bias, privacy, cybersecurity, affordability, digital literacy, and institutional capacity. The analysis emphasizes that adaptive AI should be viewed as part of a larger socio-technical strategy rather than just a standalone tech solution. For inclusive deployment, we need local participation, suitable infrastructure, responsible data governance, human oversight, and ongoing evaluation. Ultimately, the paper concludes that well-designed adaptive AI systems can foster more inclusive and sustainable digital ecosystems, provided they are affordable, locally relevant, accessible, transparent, and aligned with the Sustainable Development Goals.

Authors

Institutions

Publication Details

Journal
Machine Learning Research
Published
2026-10-29
DOI
https://doi.org/10.11648/j.mlr.20261102.16
Primary Topic
ICT in Developing Communities
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive Artificial Intelligence Models for Enhancing Digital Inclusion and Sustainable Development in Underserved Communities

Kennedy Hadullo, Joel Charo
1 links
Machine Learning Research
ICT in Developing Communities
article

Adaptive Artificial Intelligence Models for Enhancing Digital Inclusion and Sustainable Development in Underserved Communities

Kennedy Hadullo, Joel Charo
article en

Abstract

Technology is playing a vital role across various sectors like education, healthcare, agriculture, financial services, employment, governance, and social development. However, we still see significant digital inequalities, especially in underserved communities, particularly in rural and low-income areas. Here, challenges such as limited connectivity, high technology costs, lack of digital skills, language barriers, and inaccessible digital services hinder meaningful participation in the digital economy. This conceptual paper delves into how adaptive Artificial Intelligence (AI) models can boost digital inclusion and support sustainable development in these communities. It brings together insights from literature on artificial intelligence, digital inclusion, adaptive learning, responsible AI, and sustainable development. The paper introduces the Adaptive AI Digital Inclusion and Sustainable Development (AIDISD) framework, which is built around five key dimensions: accessibility, personalization, contextual adaptation, resource efficiency, and community empowerment. It explores potential applications in education, healthcare, agriculture, financial inclusion, employment, and public services. Additionally, the paper highlights challenges related to infrastructure, data scarcity, algorithmic bias, privacy, cybersecurity, affordability, digital literacy, and institutional capacity. The analysis emphasizes that adaptive AI should be viewed as part of a larger socio-technical strategy rather than just a standalone tech solution. For inclusive deployment, we need local participation, suitable infrastructure, responsible data governance, human oversight, and ongoing evaluation. Ultimately, the paper concludes that well-designed adaptive AI systems can foster more inclusive and sustainable digital ecosystems, provided they are affordable, locally relevant, accessible, transparent, and aligned with the Sustainable Development Goals.

Machine Learning ResearchVol. 11(2)
Technical University of Mombasa (KE)
Reduced inequalities, Industry, innovation and infrastructure
Openalex Percentile: Top 6%
ICT in Developing Communities
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Adaptive Artificial Intelligence Models for Enhancing Digital Inclusion and Sustainable Development in Underserved Communities — Kennedy Hadullo, Joel Charo · Machine Learning Research (2026) | TGRS Research Map | TGRS