It's a safe bet that artificial intelligence will top most lists of major technology trends for 2023. Although AI certainly isn't new, the release of a new breed of generative AI tools has unleashed a frenzy of interest in AI.
The question now is what the AI boom will mean for different sectors of the IT industry. This article explores one of them by looking at five ways that AI could help reshape cloud computing.
- Demand for AI-Friendly Cloud VM Instances
- More Sophisticated AI-Powered Cloud Cost Management
- Leveraging AI for Cloud Administration
- Even More Adoption of the Cloud
- Increased Demand for AI-as-a-Service
1. Demand for AI-Friendly Cloud VM Instances
One fairly obvious effect that the AI trend is likely to exert on cloud computing is that it will increase demand for cloud-based virtual machine instances that are optimized for running AI workloads.
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Specifically, we're likely to see more interest in bare-metal cloud VMs, as well as VMs that offer GPUs for the purposes of accelerating AI workloads.
These types of cloud VMs aren't new; on the contrary, they've been available from the major cloud vendors for years. But more and more businesses will likely want to use them to help perform tasks like AI/ML training.
2. More Sophisticated AI-Powered Cloud Cost Management
Another practice that isn't new, but is likely to be the subject of more intense interest, is the use of AI to help reduce cloud computing costs.
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Many cloud cost management tools already use some form of AI, such as predictive analytics, to assess cloud workload configurations and recommend changes that could reduce costs. Going forward, however, the generative AI boom could drive more demand for cloud cost management tools that can do more than just suggest ways to rightsize cloud workloads. They might also allow engineers to ask open-ended questions about how a configuration change could impact cloud spending, for example.
3. Leveraging AI for Cloud Administration
AI tools could also help cloud admins manage their clouds more effectively in all ways, not just those related to cost.
For example, one of the things that tools like ChatGPT can already do quite well is configure IAM security policies or generate infrastructure-as-code (IaC) templates to set up cloud workloads. Leveraging AI for these purposes will help cloud admins add more efficiency to their cloud workflows, which will likely translate to an enhanced ability to manage cloud environments that are growing more complex all the time.
4. Even More Adoption of the Cloud
AI tools like ChatGPT are great examples of a workload that needs to scale considerably, making it an ideal candidate for cloud-based hosting. For that reason, the AI trend will probably drive even more organizations to migrate to the cloud, since hosting highly scalable workloads on-prem is more difficult (and, in many cases, more costly).
Granted, not every business is going to be hosting AI services comparable to ChatGPT. But it's reasonable to expect more organizations to deploy AI-powered chatbots, analytics tools, and similar solutions that work best when hosted on massively scalable cloud infrastructure.
5. Increased Demand for AI-as-a-Service
Cloud providers have long offered AI-as-a-service solutions, which customers can use to run AI/ML workloads without having to set up their own software or infrastructure. For example, if you want to incorporate image recognition into your app, you could use a service like AWS Rekognition.
But thanks to the generative AI revolution, those services feel increasingly basic. Going forward, expect more demand for AI-as-a-service solutions that allow businesses to leverage AI in broader and more flexible ways. Companies will want cloud-based AI solutions that allow them to implement their own equivalents of ChatGPT, for example.
You can already do this sort of thing using the OpenAI APIs, of course, which make it possible to integrate the AI engine behind ChatGPT into custom applications. But in the near future, I expect that the big cloud providers, like AWS and Azure, will be rolling out their own cloud services designed with the same use cases in mind.
Conclusion
Again, AI in the cloud is not new. For years, businesses have been using the cloud to help power AI workloads, while also using AI to help manage their cloud environments.
But the latest generation of AI tools opens up a host of new opportunities to apply AI in more interesting ways to the cloud. I suspect that we'll see a lot of innovation on this front in the next few years as AI converges with cloud computing in novel ways.
About the author
Christopher Tozzi is a technology analyst with subject matter expertise in cloud computing, application development, open source software, virtualization, containers and more. He also lectures at a major university in the Albany, New York, area. His book, “For Fun and Profit: A History of the Free and Open Source Software Revolution,” was published by MIT Press.
