Investigating Knowledge-Based Requirements for Design and Production of AI-Driven Software Products

The emergence of artificial intelligence as a transformative technology has fundamentally altered the landscape of software product development, necessitating a comprehensive reassessment of the knowledge domains, organizational structures, and methodological approaches required for successful design and production. This paper examines the multifaceted knowledge-based requirements spanning technical, architectural, organizational, regulatory, and business dimensions that organizations must establish to develop AI-driven software products effectively. Through synthesis of contemporary research and industry practices, we identify a critical paradigm shift from implementation-centric to specification and architecture-centric development lifecycles, accompanied by substantial talent transformation requirements and emerging business model innovations. The analysis reveals that emerging technology ecosystems, particularly in developing markets, possess distinctive advantages in adopting these new frameworks due to reduced legacy system constraints and lower infrastructure costs. We propose an integrated knowledge-based framework encompassing AI-native software development lifecycle practices, distributed human expertise models, and governance structures that balance innovation velocity with responsible AI deployment. The implications extend beyond individual organizations to reshape entire technology ecosystems, creating unprecedented opportunities for developing economies to establish indigenous AI capabilities while competing in global software markets.

کلیدواژه ها:

artificial intelligence ، software engineering ، knowledge-based systems ، AI-driven product development