Sovereign AI Engines for Industry–Academia Linkage: An Integrated Framework for AI-fication of Trade, Investment and Technology Transfer in Bangladesh

This article synthesises a set of interlocking policy and operational proposals developed for Session-02 of the Bangladesh AI Business Summit 2026. It begins from the complementary asset portfolios of academia, industry and government (particularly the Ministry of Foreign Affairs' trade, investment and technology functions) and identifies minimum viable innovation engines capable of strengthening industry–academia linkage for AI-driven business innovation. It then elaborates the concept of sovereign AI through three interlocking frontiers—the data lock, the compute and model lock, and the governance and application lock—and specifies purpose-built sovereign AI engines that support measurable outcomes in real trade, real investment and real technology transfer. These engines are embedded within an EPI/EVI (Export/Economic Performance Index / Economic/Export Vulnerability Index) benchmarking framework, augmented by a Trade Asset Digital Verification (TADV) protocol for trade finance and a governed compute bank that eases protocol shifts and transfers. Finally, the article demonstrates how the integrated framework augments both access to and production of knowledge under sovereign conditions. The proposals are designed to be lightweight, jointly owned and measurable, converting dialogue on AI-fication into operational instruments that improve market performance while reducing external dependence. Written in a personal capacity; the views expressed are those of the author. Published in the KSCCN series.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-31
DOI
https://doi.org/10.5281/zenodo.23832616
Primary Topic
University-Industry-Government Innovation Models
Type
article
Field-Weighted Citation Impact
0.00
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article

Sovereign AI Engines for Industry–Academia Linkage: An Integrated Framework for AI-fication of Trade, Investment and Technology Transfer in Bangladesh

Syed Muntasir Mamun
Zenodo (CERN European Organization for Nuclear Research)
University-Industry-Government Innovation Models
article

Sovereign AI Engines for Industry–Academia Linkage: An Integrated Framework for AI-fication of Trade, Investment and Technology Transfer in Bangladesh

Syed Muntasir Mamun
article en

Abstract

This article synthesises a set of interlocking policy and operational proposals developed for Session-02 of the Bangladesh AI Business Summit 2026. It begins from the complementary asset portfolios of academia, industry and government (particularly the Ministry of Foreign Affairs' trade, investment and technology functions) and identifies minimum viable innovation engines capable of strengthening industry–academia linkage for AI-driven business innovation. It then elaborates the concept of sovereign AI through three interlocking frontiers—the data lock, the compute and model lock, and the governance and application lock—and specifies purpose-built sovereign AI engines that support measurable outcomes in real trade, real investment and real technology transfer. These engines are embedded within an EPI/EVI (Export/Economic Performance Index / Economic/Export Vulnerability Index) benchmarking framework, augmented by a Trade Asset Digital Verification (TADV) protocol for trade finance and a governed compute bank that eases protocol shifts and transfers. Finally, the article demonstrates how the integrated framework augments both access to and production of knowledge under sovereign conditions. The proposals are designed to be lightweight, jointly owned and measurable, converting dialogue on AI-fication into operational instruments that improve market performance while reducing external dependence. Written in a personal capacity; the views expressed are those of the author. Published in the KSCCN series.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 8%
University-Industry-Government Innovation Models
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