Future-Proofing Your Cloud Budget in the Age of AI

By John Pettit, Promevo

The AI boom is upon us — and it shows no signs of letting up. Businesses across sectors are implementing creative cloud-based initiatives that place AI at the forefront.

While AI expansion presents tremendous opportunities for business leaders, it can also cause significant uncertainty around cloud costs: Nearly three quarters of IT and finance professionals say the growth of AI adoption has made cloud bills "unmanageable." Scrambling to fit new AI initiatives into a pre-existing cloud budgets can grind innovation to a halt — while coming at the expense of other cloud-dependent resources.

To keep the AI momentum rolling, IT leaders must find a way to better forecast and manage this uptick in expenses. After all, AI isn't worth it if it breaks the bank.

Why AI's Resource Demands Are Throwing IT Budgets Off Balance

So, what exactly makes cloud cost management so difficult in the era of AI expansion?

It's a multi-pronged problem — but the core of it lies in the unpredictability of AI processing. As AI technology evolves, the amount of resources it needs to sustain itself evolves with it. IT leaders planning their budgets for the upcoming year may not have insight into these future needs, leaving them to scramble and potentially cut corners on other cloud-based products.

Related:Harness the Cloud: Critical Benefits of Cloud Computing

Another difficulty lies in the inconsistency of AI processing power. Many AI and machine learning (ML) models can vary in terms of workloads — for instance, the inference phase requires minimal computation while training demands significant processing power.

Businesses not only need to invest in the cloud costs associated with deploying AI but also the resources required to train staff to manage these advanced technologies. Hiring skilled talent is another option, but with demand for knowledgeable engineers at a premium, this is easier said than done. The only sustainable path forward is through AI upskilling — which isn't a one-time cost, but an ongoing investment.

3 Tips for Future-Proof AI Budgeting

Regardless which stage of the budget planning process you're in, AI cost management should be top of mind. As you evaluate how to sustainably fit AI into your budget, here are a few best practices to consider.

1. Optimize AI-related training

AI training and upskilling can be a major drain on resources — thus, learning how to optimize this process is key to limiting cost.

To begin, encourage a "train-the-trainer" approach, in which you identify in-house experts who can then train other team members, reducing the need for repeated external training. This approach fosters a more collaborative learning environment that encourages employees to share knowledge and resources amongst themselves.

Related:U.S. Leads Global Cloud Adoption, Fueled by AI and FinOps Expansion

Also, take advantage of your network. Many cloud providers, including Google Cloud and Amazon Web Services, offer free or discounted training resources for partners and clients. These can be a cost-effective starting point for more formalized training.

2. Choose the right AI model for your needs

Rolling out an AI model that is a poor fit for your organization's needs is the fastest way to bloat your cloud budget. After all, large AI models consume more resources, which translates to higher costs and potentially slower response times.

When choosing the right model size, consider the complexity of the task at hand. For instance, natural language understanding might require a larger, more advanced model, while simpler tasks can often be managed with smaller models.

There are even instances where a model may not be necessary at all. If a task can be achieved with rule-based automation or simple statistical methods, those approaches might be more cost-effective and easier to maintain. An example of this would be applications that require high precision or that have clearly defined answers.

3. Use AI to help optimize cloud usage and costs

Ironically, the answer to inflated AI spend may lie in AI itself — or rather, using AI-powered insights to learn more about your cloud usage patterns. The right AI platform can offer predictive analytics that forecast future costs, empowering your team to make more informed decisions.

Also, make sure you're taking full advantage of your cloud platforms' tools. Many providers offer tools to help right-size resources, shut down idle instances, and identify underused resources. Sadly, far too often these features go ignored. Don't leave these tools on the table — use all the resources at your disposal to make your budgetary decisions.

Building a Sustainable AI Strategy Starts Today

As AI growth continues, the impact on cloud budgets will only become more unpredictable. To cope, IT leaders need to lay the groundwork for sustainable AI implementation. This includes approaching AI training in a collaborative, cost-effective manner, as well as learning how to get the most out of their existing cloud resources.

By establishing this blueprint today, your organization puts itself in a better position to implement new AI technologies faster, without destroying your budget in the process.

About the author:

John Pettit is CTO at Promevo.