--- title: "IMPLEMENTING ARTIFICIAL INTELLIGENCE AND LABOR PRODUCTIVITY IN ENTERPRISES: THE ROLE OF DIGITAL COMPETENCIES · AI Fault Line" url: https://aifaultline.com/research/p/title-a2888bc2d5a90c14/ description: "AI Fault Line is a neutral, evidence-cited field guide to why experts looking at the same developments disagree about AI's effect on productivity, jobs, inequality, regulation and the pace of change." --- [Research](https://aifaultline.com/research/) # IMPLEMENTING ARTIFICIAL INTELLIGENCE AND LABOR PRODUCTIVITY IN ENTERPRISES: THE ROLE OF DIGITAL COMPETENCIES Maftuna Samiyeva · EduVision: Journal of Innovations in Pedagogy and Educational Advancements · 29 Oct 2026 [Read original source](https://brightmindpublishing.com/index.php/ev/article/view/3031) Open access Where this sits in the debate - [Will AI actually boost productivity and growth?](https://aifaultline.com/debate/productivity/) · its finding: it depends ([why studies differ](https://aifaultline.com/debate/productivity/#why)) Direction of the finding as read from the abstract by an AI model ([AI-written](https://aifaultline.com/about/)). ## Abstract This article examines the impact of introducing artificial intelligence (AI) technologies into enterprise operations on labor productivity, with particular attention to the mediating and enabling roles of employees’ digital competencies. The study aims to identify opportunities to improve efficiency through AI-driven automation, data-informed decision-making, and business process optimization, as well as to systematize the skills required to realize these opportunities. The analysis draws on a comparative review of scholarly literature, a systems approach, and logical synthesis. Digital competencies are considered in terms of searching for, analyzing, and interpreting data; using AI tools appropriately; critically assessing generated outputs; complying with cybersecurity requirements; and collaborating in digital environments. The analysis suggests that technological infrastructure alone does not guarantee greater productivity. Outcomes also depend on workforce readiness, management practices, organizational culture, and the extent of workflow redesign. AI can reduce time spent on routine tasks, limit errors, and improve resource allocation. However, insufficient skills may increase risks associated with excessive reliance on technology, information security, and the quality of managerial decisions. To address these challenges, the article proposes an approach that combines initial competency assessment, role-specific training programs, practice-based learning, and regular evaluation against labor productivity indicators. Suggested indicators include output per employee, task completion time, and quality measures. The conclusions provide a conceptual basis for aligning enterprise investment in AI with human capital development and for designing management decisions that support sustainable productivity growth. ## About this publication **Academic journal.** Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth. Published 2026 (recently) Citations 0 (OpenAlex) 0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison. [Chart: published 2026] ## More on this topic Related by theme, not necessarily by method or conclusion. - [Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality](https://aifaultline.com/research/p/doi-10-2139-ssrn-4573321/) SSRN · 2023 - [Generative AI at Work](https://aifaultline.com/research/p/doi-10-1093-qje-qjae044/) The Quarterly Journal of Economics · 2025 - [The Impact of AI on Developer Productivity: Evidence from GitHub Copilot](https://aifaultline.com/research/p/doi-10-48550-arxiv-2302-06590/) arXiv · 2023 - [The Productivity J-Curve: How Intangibles Complement General Purpose Technologies](https://aifaultline.com/research/p/doi-10-1257-mac-20180386/) American Economic Journal Macroeconomics · 2020 Overview assembled automatically from collected metadata. [How this site is built](https://aifaultline.com/about/).