PhD Defence: Yassine Lamrani Abou Elassad

Abstract

This dissertation investigates how firms achieve and sustain persistent high growth, and how the rise of artificial intelligence reshapes the strategic foundations that underpin such trajectories. While traditional theories portray rapid growth as destabilizing and suggest that moderate expansion offers the safest path to survival, recent evidence highlights the societal and economic importance of high-growth firms and raises questions about whether these assumptions still hold. Across three empirical studies, this dissertation re-examines the benefits, mechanisms, and vulnerabilities of persistent high growth by integrating insights from growth–survival theory, competitive dynamics, organizational learning, and AI-enabled strategy.

The findings demonstrate that persistent high growth is neither a rare accident nor an inherently hazardous deviation, but instead reflects cumulative, path-dependent processes through which firms build capabilities, legitimacy, and competitive position. Ventures that sustain growth across multiple episodes exhibit stronger survival prospects than those that follow moderate or irregular growth paths. At the same time, persistent high growth emerges not from single categories of strategic action but from synchronized portfolios of growth and restructuring moves whose effectiveness depends on firm context and strategic history. Furthermore, we show that while AI improves predictive accuracy and raises performance, it can also accelerate the erosion of strategic decision value as all firms gain access to optimal decisions. Yet this erosion is cyclical rather than permanent: recursive feedback, input heterogeneity, and adaptive search processes generate renewed value of decision making over time.