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.

Explore more

Can Federal Lands Power the Future of AI Infrastructure?

I’m thrilled to sit down with Dominic Jainy, an esteemed IT professional whose deep knowledge of artificial intelligence, machine learning, and blockchain offers a unique perspective on the intersection of technology and federal policy. Today, we’re diving into the US Department of Energy’s ambitious plan to develop a data center at the Savannah River Site in South Carolina. Our conversation

Can Your Mouse Secretly Eavesdrop on Conversations?

In an age where technology permeates every aspect of daily life, the notion that a seemingly harmless device like a computer mouse could pose a privacy threat is startling, raising urgent questions about the security of modern hardware. Picture a high-end optical mouse, designed for precision in gaming or design work, sitting quietly on a desk. What if this device,

Building the Case for EDI in Dynamics 365 Efficiency

In today’s fast-paced business environment, organizations leveraging Microsoft Dynamics 365 Finance & Supply Chain Management (F&SCM) are increasingly faced with the challenge of optimizing their operations to stay competitive, especially when manual processes slow down critical workflows like order processing and invoicing, which can severely impact efficiency. The inefficiencies stemming from outdated methods not only drain resources but also risk

Structured Data Boosts AI Snippets and Search Visibility

In the fast-paced digital arena where search engines are increasingly powered by artificial intelligence, standing out amidst the vast online content is a formidable challenge for any website. AI-driven systems like ChatGPT, Perplexity, and Google AI Mode are redefining how information is retrieved and presented to users, moving beyond traditional keyword searches to dynamic, conversational summaries. At the heart of

How Is Oracle Boosting Cloud Power with AMD and Nvidia?

In an era where artificial intelligence is reshaping industries at an unprecedented pace, the demand for robust cloud infrastructure has never been more critical, and Oracle is stepping up to meet this challenge head-on with strategic alliances that promise to redefine its position in the market. As enterprises increasingly rely on AI-driven solutions for everything from data analytics to generative