Over the years, cloud-native has become an integral part of many businesses' operations, with a cloud-first approach to tech and a focus on application scalability.
According to the Cloud Native Computing Foundation (CNCF), these applications live in public, private, and hybrid clouds and are defined by the presence of containers, service measures, microservices, and other infrastructure qualities.
A new version of this framework is coming to the fore as businesses look to ramp up the adoption of AI and generative AI tools. This framework is known as AI-native cloud or cloud-native AI.
What does cloud native have to do with AI? Well, the two digital technologies have quite a lot in common as AI applications often benefit from the scalability of the cloud native framework.
That’s where the idea of AI-native cloud comes in, a concept still in its infancy in terms of definition, but that can be understood as an extension of cloud-native for AI deployments.
AI-native cloud can be broadly understood as a framework that puts AI front and center when thinking about cloud, and cloud front and center when thinking about AI.
Companies that adopt this framework will be defined as those which build their AI applications in a cloud native way, but also those which organize the structure of their cloud to suit the development of AI applications.
How do AI and cloud-native work together?
The interplay between cloud-native technologies and AI technologies is wide in scope, and both technologies can be used in conjunction to deliver valuable results.
The CNCF defined its own understanding of cloud-native AI in its ‘Cloud Native Artificial Intelligence Whitepaper,’ focusing it around the construction of systems that can deploy, run, and scale AI workloads.
“Cloud Native Artificial Intelligence (CNAI) refers to approaches and patterns for building and deploying AI applications and workloads using the principles of Cloud Native. Enabling repeatable and scalable AI-focused workflows allows AI practitioners to focus on their domain,” the CNCF said.
Such workloads can often be very taxing in terms of compute as research from the start of this year revealed - the average capacity of data centers set to open four years will be almost double that of current facilities owing to the high demand of AI workloads.
Cloud-native AI addresses some of the challenges that AI applications face in this regard, the CNCF said, by leveraging cloud infrastructure’s underlying computing, network, and storage capabilities to improve performance and reduce cost.
The CNCF sees cloud-native AI as an extension of traditional cloud-native concepts. For example, AI can be packaged into the containers and K8 clusters of Kubernetes, the container orchestration platform at the heart of most cloud native infrastructures.
“Containerization is especially crucial for AI models because different models typically require different and often conflicting dependencies. Isolating these dependencies within containers allows for far greater flexibility in model deployments,” the CNCF said.
AI and cloud-native are synergetic, as AI can hugely benefit from a scalable, cloud-first approach to infrastructure, while cloud-native forms an ideal bedrock for AI technologies.
What does it mean for businesses?
The benefits of AI-native cloud for businesses are myriad. It only takes a glance at what value cloud native can drive for businesses to imagine what similar advantages AI-native cloud may offer.
For example, by building applications in cloud-native fashion, they are purpose-built to live in the cloud and so can take full advantage of everything the cloud has to offer. This includes enhanced scalability, developer efficiency, and resilience.
“If something has been designed especially for the cloud … then it's much more likely to easily exploit the full potential and capability of the cloud and run more efficiently,” Adrian Bradley, head of cloud transformation at KPMG, told ITPro in 2024.
The same principle applies to AI-native cloud. Any businesses designing their cloud and AI infrastructure to be collaborative and synergetic will be able to take full advantage of all that both technologies have to offer.
Businesses can gain a huge amount of value from AI-native cloud infrastructure, as it allows firms to ramp up their AI adoption in a way that prepares them for the ever-changing demands of the technology.
UK firms are particularly well placed to capitalize on AI-native cloud given that they currently lead the way on the containerization of applications, though skills gaps could hamper the region's lead on this front.
What industries/use cases lead the way with AI-native cloud?
Industries across the board stand to gain from AI-native cloud, though some areas, in particular, show use cases that appear well positioned to take advantage of the framework.
Business areas such as automotive, e-commerce, entertainment, finance, healthcare, and technology, also all stand to benefit significantly from AI-native practices, according to a blog post from Legitt.
That’s because such sectors often rely on real-time analytics, automation, and personalization, all processes that can be more effectively achieved with an AI-native cloud infrastructure.
Just as the concept of cloud native has revolutionized the speed and efficiency of business practices, AI-native cloud will have a similar impact on the next generation of AI-first companies.
