AI Investment and the Pendulum Effect: The Crisis of Software Quality & Infrastructure
DOI:
https://doi.org/10.15662/IJRAI.2025.0806018Keywords:
AI investment, pendulum theory, software quality crisis, quality assurance, outages and recalls, hybrid AI–human testing, enterprise risk managementAbstract
Pendulum theory, which describes the tendency of systems to swing between extremes before returning to balance, provides a useful framework for analyzing the current trajectory of Artificial Intelligence (AI) adoption in 2025. Organizations across industries are investing heavily in AI infrastructure and applications, often reallocating resources from critical functions such as quality assurance and testing. This paper argues that such measures represent an overcorrection to the promise of AI, creating a crisis in software quality.
Drawing on perspectives from quality assurance engineers and developers, the paper highlights the risks of sidelining quality divisions, including increased outages, customer dissatisfaction, and erosion of trust. By applying pendulum theory, the analysis demonstrates that both extremes - overprotective quality divisions that delay releases and passive divisions that rubber-stamp code - are counterproductive. The path forward requires balance, where AI innovation is complemented by independent, knowledgeable, and customer-focused quality teams. Without this equilibrium, the industry risks undermining the very progress AI seeks to achieve.
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