Harnessing AI to Control Rising Cloud Costs in the Age of Generative AI

As AI costs continue to escalate, companies worldwide are feeling the substantial financial impact. The average business has observed its cloud spending surge by 30% over the past year, with the rapid growth of generative AI being a significant contributing factor. Stories of astonishing expenses are increasingly common, such as amassing a $30,000 bill in just 12 hours due to excessive calls to AI services. Meanwhile, frontline practitioners find themselves burdened, with over 70% reporting that AI-driven cloud spending has become “unmanageable.” This issue perfectly illustrates a persistent problem: the unpredictability and uncontrollability of cloud costs. Projections show that spending on public cloud services will likely surpass $800 billion in 2024, a 20% increase from the previous year. Alarmingly, more than three-quarters of businesses admit that 20%-50% of their cloud spend is wasted.

Despite these rising expenses, it doesn’t have to be an insurmountable challenge. While AI may be driving up cloud costs, it also holds the potential to control them for those grappling with soaring budgets. Understanding why cloud costs are so high, and learning how to manage and mitigate these expenses, can be crucial for businesses.

Gain a Clearer Insight into Your Expenditures

Cost management tools for the cloud have existed for some time. However, until recently, many of these tools were cumbersome to configure and required constant maintenance. At best, they would flag overrun costs, leaving the responsibility of addressing them to the individual teams. AI and automation, though, have revolutionized the identification of wasteful spending, making it significantly easier to pinpoint areas where costs can be reduced.

Today, the most advanced cloud cost management tools allow users to pose questions in plain language and receive prompt, comprehensible responses. For instance, users can ask, “What are the anticipated cloud costs for this new product feature?” or “Which teams are utilizing the most cloud services?” Such tools can even break down the top three actions a development team can take to reduce their cloud spending. In the past, deriving these insights required meticulous examination of numerous spreadsheets; now, AI can handle these complexities with ease and efficiency.

Understanding your expenditures is the first step toward controlling cloud costs. With AI-powered tools providing a clearer and more straightforward view of spending, businesses can begin to manage and mitigate their expenses effectively.

Determine the Necessary Actions

Visibility into cloud expenditures is merely one part of the equation. Equally critical is understanding the required actions to optimize these expenditures and ensure efficiency. Modern tools empower developers not only to identify where spending overruns occur but also to receive actionable recommendations based on historical patterns and resolutions. This could involve actions such as disabling idle resources or optimizing storage costs by relocating infrequently accessed data to more economical storage solutions.

However, clarity on the path forward often isn’t enough. In fact, the latest FinOps Foundation survey reveals that, while automation is a priority for many companies, the vast majority still have employees manually addressing these fixes. On a busy software team, time is a precious resource, and manual adjustments can be both time-consuming and prone to oversight.

Despite having a roadmap for cost optimization, executing these actions efficiently remains a challenge. Therefore, companies must seek out ways to streamline the process, ensuring that the necessary steps are taken without overburdening their teams or sacrificing productivity.

The Essential Step—Automate Cloud Adjustments

As AI costs continue to soar, businesses globally are experiencing significant financial strain. On average, companies have seen a 30% increase in cloud spending over the past year, largely due to the rapid expansion of generative AI. Reports of staggering bills are increasingly common; for instance, some have accrued $30,000 in just 12 hours from excessive AI service usage. Meanwhile, over 70% of frontline practitioners report that AI-driven cloud expenses have become “unmanageable,” highlighting the persistent issue of unpredictable and uncontrollable cloud costs. It’s projected that spending on public cloud services will surpass $800 billion in 2024, marking a 20% increase from the previous year. Alarmingly, more than three-quarters of businesses acknowledge that 20%-50% of their cloud spend is wasted.

While these rising costs are daunting, they are not insurmountable. AI, which is driving up cloud costs, also has the potential to help manage them. Understanding why these costs are high and learning strategies to control and mitigate expenses can be vital for businesses struggling with inflated budgets.

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