CAPITAL STRUCTURE TRANSFORMATION IN THE ERA OF ARTIFICIAL INTELLIGENCE: EVALUATING CORPORATE SOLVENCY AND LIQUIDITY SECURITY IN BIG TECH

Abstract

The rapid expansion of Artificial Intelligence (AI) investments between 2020 and 2025 has substantially increased capital expenditure (CapEx) among global technology companies, creating new challenges for corporate capital structure, liquidity, and long-term financial resilience. This study examines the financial performance of eight leading technology companies Microsoft, Apple, Alphabet, Amazon, Meta Platforms, NVIDIA, IBM, and Oracle using a three-dimensional analytical framework comprising Capital Structure Alignment (G1), Liquidity-Based Asset Security (G2), and Operational Servicing Capacity (G3). Empirical panel data covering the 2020–2025 period were analysed using fixed-effects econometric modelling to investigate the relationship between financing structure and corporate financial resilience under intensive AI investment. The findings suggest the existence of two distinct financing patterns within the technology sector. The first, observed primarily in Alphabet, NVIDIA, and Microsoft, is characterised by comparatively low financial leverage and strong internally generated cash flows that support continued investment while maintaining high liquidity. The second pattern, identified in Oracle and IBM, is associated with higher leverage ratios and greater reliance on debt financing during infrastructure transformation and cloud-computing expansion. The empirical analysis indicates that stronger liquidity positions are positively associated with corporate financial resilience throughout periods of intensive AI-related investment, whereas higher leverage may increase refinancing exposure under adverse market conditions. These findings provide practical implications for corporate financial managers, institutional investors, and policymakers concerned with capital allocation, financial stability, and debt sustainability in technology-intensive industries.