TITLE:
Beyond Data Literacy: The Interpretive Competencies HR Professionals Need for AI-Augmented Performance Management in Sub-Saharan Africa
AUTHORS:
Jacob Patrick Belinga Bessala
KEYWORDS:
Algorithmic Interpretive Competence, AI-Augmented Performance Management, Institutional Voids, Sub-Saharan Africa, Data Literacy
JOURNAL NAME:
Journal of Human Resource and Sustainability Studies,
Vol.14 No.4,
October
23,
2026
ABSTRACT: Artificial intelligence (AI) now performs a large share of performance management (PM) work in organisations worldwide, yet the professionals responsible for governing these systems are widely reported to lack the skills to interpret what the algorithms produce. Industry frameworks respond by prescribing data literacy as the core AI-era competency, but this paper argues that data literacy is necessary and insufficient, and proposes a narrower, more precisely bounded construct to close the gap. Adopting an integrative literature review and conceptual framework design, with search-and-screening transparency limitations disclosed, the paper synthesises institutional theory, competence-in-action theory, algorithmic literacy scholarship, algorithmic-control theory and Ubuntu relational philosophy into a five-tradition architecture, illustrated by secondary evidence from Sub-Saharan Africa (SSA), including published empirical studies from South Africa and regional reviews, and contextualised through institutional data from the International Telecommunication Union and AfriCatalyst. It introduces algorithmic interpretive competence (AIC): the capacity of the HR professional responsible for governing an organisation’s AI-augmented PM system to interpret, translate, mediate and contest algorithmic performance outputs. Five propositions with falsifiability clauses link AIC to procedural justice, interactional justice, and trust outcomes, with institutional voids and infrastructure constraints as moderators. The paper is the first to theorise a PM-specific, institutionally contextualised interpretive-competency construct for AI governance, offering a research and curriculum agenda for HR development in institutionally constrained settings.