AI-Augmented Technical Program Management: Bridging Human Judgment and Machine Intelligence in Complex Engineering Programs

Abstract

This paper examines how large language models and predictive machine learning are augmenting the Technical Program Management (TPM) function- specifically in predictive risk forecasting, dependency and workflow intelligence, natural-language status reporting, and decision-support copilots. Drawing on evidence from management research (notably Dell'Acqua et al.'s "jagged technological frontier" finding), software engineering studies, and organizational-behavior literature, the paper proposes a four-part taxonomy of AI-augmented TPM and discusses open challenges around trust calibration, accountability, and skill development. This work was drafted with AI assistance (Claude, Anthropic) for structuring and literature synthesis, with sources verified and content reviewed by the author.