Telecom for Humanity: AI-Driven BSS Platforms for Digital Equity and Accessibility

Authors

  • Balakumar Ravindranath Kunthu
  • Naveen Prakash Kandula

DOI:

https://doi.org/10.22399/ijcesen.4259

Keywords:

AI-driven BSS, Digital equity, Telecommunications accessibility, Revenue assurance, Affordability barriers, Rural connectivity

Abstract

Digital exclusion remains a pervasive barrier to economic participation, education, healthcare access, and social inclusion for billions globally. Artificial intelligence-driven Business Support Systems within telecommunications represent a transformative opportunity to advance digital equity and accessibility through automated, affordable, and inclusive service delivery. This research examines the convergence of AI technologies with BSS architectures to address affordability barriers, operational inefficiencies, and service accessibility challenges confronting underserved populations. The global Digital BSS market, valued at $7.9 billion in 2024, demonstrates an 11.8% compound annual growth rate toward $15.4 billion by 2030, driven substantially by cloud-native deployments and AI integration. Key findings reveal that AI-driven customer service automation manages 80% of routine inquiries, achieves 87.2% positive user acceptance, and reduces revenue leakage by 30-40% within the first implementation year. Concurrently, 2.6 billion individuals remain offline globally in 2024, with 1.8 billion residing in rural areas where deployment costs exceed urban equivalents by 200-300%. This synthesis establishes that AI-enabled BSS platforms deliver measurable improvements in affordability, service velocity, fraud prevention, and multilingual accessibility, positioning telecommunications as a critical enabler of humanitarian outcomes and societal advancement.

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Published

2025-03-30

How to Cite

Ravindranath Kunthu, B., & Naveen Prakash Kandula. (2025). Telecom for Humanity: AI-Driven BSS Platforms for Digital Equity and Accessibility. International Journal of Computational and Experimental Science and Engineering, 11(4). https://doi.org/10.22399/ijcesen.4259

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Section

Research Article