Designing Human-Centered AI Platforms for Scalable Global Software Through Integrated Product Engineering with Market-Ready Architecture

Abstract

The growing demand for intelligent, scalable, and ethically aligned software has intensified the need for AI platforms that balance technological robustness with human-centered design. This study presents a holistic framework for designing human-centered AI platforms intended for global scalability by integrating product engineering principles and market-ready architecture. Employing a design-based research methodology, the platform was co-developed with users through iterative prototyping and evaluated for usability, scalability, and fairness. Usability assessments using the System Usability Scale (SUS) showed high satisfaction rates across professional developers, citizen developers, and end users. Performance benchmarks confirmed the system's ability to operate efficiently across cloud, edge, and on-premise environments, with edge deployment yielding the most balanced latency and throughput. Multiple regression analysis revealed that architectural modularity, transparency, and multilingual support significantly influenced user adoption. A fairness audit across demographic groups found equitable outcomes overall, with slight disparities observed for non-native-language users. These results emphasize the importance of integrating human-centered principles into AI development to ensure accessibility, trust, and adaptability. The study concludes with a validated design approach that positions AI platforms to succeed both technologically and socially in global software ecosystems.