Principles for Building a Responsible Artificial Intelligence Strategy in Technology Companies

Elena Levi

Citation: Elena Levi, "Principles for Building a Responsible Artificial Intelligence Strategy in Technology Companies", Universal Library of Innovative Research and Studies, Volume 03, Issue 02.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This article examines how technology companies can build a responsible artificial intelligence strategy at a time when generative tools accelerate prototyping, compress product cycles, and intensify pressure to scale AI quickly. The study addresses a practical gap between high level responsible AI principles and the managerial logic required to turn them into stable product decisions. The aim is to formulate an analytically grounded strategy model that connects governance, trust, data quality, and product management discipline. The materials consist of ten recent scholarly sources covering AI governance, responsible AI implementation, trust in AI adoption, generative design, new product development, data quality, and measurement systems. The method combines source analysis, comparative analysis, conceptual synthesis, and analytical generalization. The results identify three interdependent foundations of responsible AI strategy: organizational governance architecture, product level decision discipline, and measurable assurance mechanisms. The article offers an implementation logic and monitoring structure suitable for technology firms building enterprise facing AI products.


Keywords: Responsible AI, AI Governance, Technology Companies, Product Management, Generative AI, Prototyping, Trust In AI, Data Quality, AI Strategy, Enterprise Software.

Download doi https://doi.org/10.70315/uloap.ulirs.2026.0302007