AI & Computingarticle2026-10-14

Automating the understaffed library: a framework for low-code workflow automation in colleges of education libraries

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Abstract

Purpose This paper aims to address the problem of chronically understaffed academic libraries, using Ghanaian Colleges of Education as the case, and develops a practical framework for using low-code and no-code workflow automation to lift routine work without new hires. Design/methodology/approach The framework is developed through a conceptual synthesis of the general automation, library-practice and African library-technology literatures, adapted to the resource-constrained College of Education setting. Findings The paper sets out a four-stage framework – identify suitable workflows, select a tool, build along a maturity model, and govern the result – supported by a task taxonomy, an impact-and-effort prioritisation method, a tool-selection guide, a maturity model, and explicit boundary conditions for when not to automate. Originality/value Existing work is either not about libraries, code-heavy, tied to costly subscription platforms, or frames automation as expensive artificial intelligence. To the best of the authors’ knowledge, this is the first framework to treat low-code workflow automation as a deliberate, affordable strategy for the understaffed, resource-constrained academic library, built on self-hostable tools and within reach of a single capable librarian.

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View paper (DOI)OpenAlexLibrary Hi Tech NewsPublished 2026-10-14

Authors: Ronald Andoh-Kwaw, Martha Baidoo, Franklin Gyamfi Agyemang