Artificial intelligence is positioned as a pivotal element of digital advancement for progressive businesses. While AI and generative AI present opportunities for innovation, they also introduce financial risks that may impede their sustained utilization.
Understanding the foundation of AI’s functionality is crucial in addressing this challenge. AI heavily depends on computational power and cloud storage capabilities. Together, they empower AI; separately, they hold little value.
Cloud infrastructure and applications provide the necessary infrastructure for advanced analytics, hyper-automation, and large language models to operate efficiently. Nonetheless, this setup can result in unforeseen and unmonitored cloud expenses. The financial burden imposed by AI is underscored in a recent article in The Wall Street Journal, highlighting the escalating costs associated with invisible network and applications that complicate the cloud landscape:
GenAI is driving a new wave of technical indebtedness for many enterprises.
The integration of AI, an expensive yet indispensable asset, with the escalating demand for cutting-edge GenAI tools can quickly render investment strategies unsustainable. The mounting pressure for continuous innovation may accelerate the expansion of the AI cloud at unprecedented rates. By 2024, the accumulation of cloud-related expenses over the past three years could culminate in complete AI-cloud insolvencies. These hidden costs pose a significant threat to AI advancement, constraining the capacity of CIOs and CFOs to devise new budgets and secure internal funding to sustain the economic rhythms of digital transformation.
