How can you afford AI?

The world is all-in on AI and organizations are showing no signs of reining in their AI ambitions, but one question most likely plagues you: How can I afford AI?

Perhaps, new investments for AI aren’t part of your budget nor do you know a way to use your current IT investments to support AI workloads. So, how can you afford AI? According to IDC, gen AI is triggering hyper-expansion of AI spending, with organizations expected to spend USD 371.6 billion on products and services to implement gen AI from 2024 to 2027.

The key is balance — balance between ambitions and costs, between new investments and the current ones, and between going at it on your own and relying on trusted experts.

"CIOs don’t have to tackle this challenge alone; the trick is to start small and go from there. Don’t try to boil the ocean." - Joe Cropper

Like most IT leaders, you’re expected to tackle seemingly unlimited to-do lists with decidedly limited IT budgets. These days, AI adoption is chief among your priorities, but investing in AI means a large capital outlay that has no room in your stretched-thin budgets.

How do you ensure that these tight budgets don’t hinder your AI journey? Here’s how: start with small and focused use cases. Starting small has many benefits, but the most notable one is that it allows you to achieve better outcomes with less risk.

An important point to remember is that AI isn’t a technology that you can install one day and hope to see immediate benefits the next day. You need to be realistic and clear-sighted about your goals and have a three-to-five-year vision of what your AI journey will be.

Pro tip: Seek the help of industry leaders, such as IBM, that have a strong point of view and a proven track record to help identify the right use cases for your organization.

How accurate do you feel your costs are? To make AI more affordable and take the necessary modernization and investment decisions, you need to have a handle on what you’re spending—and where. In many cases, you may have a high-level view of your IT spend, but what’s the view like at the workload or application level?

You can’t optimize what you don’t understand. A comprehensive view into your IT operations, consumption and spend will help you identify and target not just overspending and over-provisioning but also inefficiencies. Here’s where automation and IT management solutions—including ITOps, AIOps and FinOps tools—come in handy.

These solutions help you have full oversight of your technology assets throughout their operational lifecycle—from inception to retirement.

They help provide a centralized view of your IT operations, deliver real-time insights on costs and resource utilization from across your organization, and automate tasks to optimize performance and security. When you understand your IT environment better, you manage your costs better.

Pro tip: Seek emerging management tools you can use to increasingly capture the value of AI, not just the costs.

You want to get the most from your existing infrastructure—that’s the only cost-effective path to AI you see ahead of you. An intentionally designed hybrid cloud enables you to do that. It gives you the choice and flexibility to modernize your infrastructure at your own pace— so you can pivot quickly if or when you need to.

While hybrid cloud isn’t a new concept to most organizations, an IT foundation that’s merely hybrid by default won’t deliver the expected benefits. AI and other emerging technologies require an IT foundation that’s intentionally designed to support their implementation and use.

With a hybrid by design approach, you can use the public cloud to train your AI models—and lessen the investment burden on your on-premises infrastructure. At the same time, you can use your on-premises infrastructure for inferencing to meet any data sovereignty or privacy regulations that you need to comply with.

This approach also enables you to have seamless access to data across your IT estate. Since data quality can have a direct impact on AI costs, easy access and management of data is crucial.

Pro tip: Understand your current cloud and IT environment. Don’t think of cloud as a location—rethink and reframe your cloud strategy to encompass a hybridized, connected IT.

"In today’s era of generative AI, your data and your models are going to be two of your most important assets. However, finding those assets in a complex IT environment sometimes can feel a lot like playing a game of hide and seek.” - Hillery Hunter

This is an excerpt from our IT Optimization Guidebook. Access all the chapters here.