Agentic AI is one of those relatively rare technologies that deserves to be called ‘revolutionary.’ For the first time in history, machines capable of making decisions and acting on them autonomously will play a significant role in our economy. Science fiction has become reality.
Generative AI has the potential to add trillions of dollars in annual value to the global economy, and agentic AI represents a major next phase of that opportunity. But realizing that value depends on whether enterprises can invest in the right infrastructure at the right time. For this, cloud cost optimization is key.
Enterprises struggle to reduce cloud costs
Investing in agentic AI infrastructure is easier said than done. A recent Harvard Business Review (HBR) study found that although 96% of business leaders believe AI is critical, only 23% have the infrastructure to support it. Cost is a significant barrier, with nearly half (47%) of respondents to HBR’s survey saying that infrastructure costs are higher than expected.
Increasing pressure on cloud compute budgets is another major challenge, particularly for on-premises data centers that do not benefit from the economies of scale enjoyed by cloud companies. Many enterprises will struggle to maintain their existing cloud compute infrastructure for core enterprise workloads before they can even consider investing in the next generation of CPUs and GPUs for agentic AI. The imperative to reduce compute costs is clear.
Costs are rising rapidly due to an imbalance between supply and demand, driven by hyperscalers building out data centers for AI. This isn’t going to resolve any time soon. If enterprises are to build out their own agentic AI infrastructure, they’re going to have to look for efficiencies to release the budget for investment. Affordable cloud computing has become a crucial lever in a successful agentic AI investment strategy.
The role of CPUs in cloud cost optimization
On the surface, efficiency-optimized (ARM-based) processors can help organizations reduce costs. Using Reduced Instruction Set Computing (RISC) rather than Complex Instruction Set Computing (CISC) architecture, efficiency-optimized custom silicon can complete tasks with fewer transistors, thereby improving efficiency. However, these CPUs come with their own challenges.
Most notably, because nearly all enterprises use data centers running existing x86 processors, they will need to completely refactor to migrate to efficiency-optimized silicon. That means moving from a CISC to a RISC mindset, decoupling the enterprise software stack from x86-specific hardware assumptions, and integrating with unique custom-silicon features. This is a highly disruptive process that can take months or even years to complete. Additionally, as custom silicon is unique to each vendor, organizations can be effectively locked into their hyperscaler’s stack.
The path to low-cost cloud computing should not be this convoluted.
Enter Vultr VX1™ Cloud Compute
Fortunately, a new solution from Vultr offers enterprises a simpler and more effective approach to CPU optimization. Vultr VX1™ Cloud Compute plans are up to 33% more affordable per vCPU and offer up to an 82% performance-per-dollar advantage over efficiency-optimized (ARM-based) compute plans from the traditional hyperscalers.
These savings free up significant funds for organizations to spend on GPUs and CPUs. What’s more, Vultr VX1 is based on AMD processors – it’s x86-native. That means businesses can immediately start enjoying the benefits of low-cost cloud computing without the need for a long, technical refactoring process.
Agentic AI is ushering in a new era of enterprise IT that demands a wholesale data center transformation. By using Vultr VX1 Cloud Compute for core workloads, businesses can source the money they need for data center modernization. Additionally, by using Vultr VX1 for data-center modernization, they can ensure their new AI-ready infrastructure is cost-effective and high-performance from day one.
To learn more about CPU modernization and the shift to agentic AI infrastructure, read our new whitepaper: Seize the Advantage: How Cloud Cost Optimization Can Fuel Agentic AI.