Comparing Research Related to Technology Management: Lessons Learned from Two Research Papers on Project Management in Artificial Intelligence.

This article presents a comparative study of two key artificial intelligence (AI) technologies: human-AI collaboration and predictive guidance. Based on recent peer-reviewed research, it explores how AI tools and techniques can address critical service delivery challenges, including innovation, risk mitigation, resilience, and sustainability. Human-AI collaboration, as demonstrated by its prominence in storytelling tools, enriches and expands knowledge through meaningful and actionable collaboration. Predictive analytics, on the other hand, provides evidence for eliminating predictive bias and improving risk management by making decisions based on real data. This article combines these two models through a comparison table and a realistic synthetic model, focusing on theoretical foundations, methodological approaches, and opportunities for integrating ESG (Environmental, Social, and Governance) criteria. The findings demonstrate that integrating advanced AI with data can lead to stronger, more accurate, and more sustainable business outcomes. This paper contributes to an integrated technology management model that balances innovation with rigorous testing in complex enterprise environments.

Technology Management, Human-AI Collaboration, Reference Class Forecasting, Project Complexity, Behavioral Bias, Generative AI, Risk Management, Sustainability Integration and AI-Augmented Projects

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