According to a Katonic AI report, data triangulated from Gartner, IDC, and Forrester showed that Cloud spends grew from less than USD 20 billion in 2010 to a whopping USD 400 billion in 2024 – in a mere span of 15 years.
According to new analysis, Agentic AI could follow an even steeper curve. A handful of hyperscalers hold an overwhelming majority of the market share today, but an emerging architectural pattern could shift the balance of power from these Cloud giants to intelligent agents, commoditising the very services that built their empires.
This paradigm shift is driven by Generative Artificial Intelligence (GenAI), which represents a new way of designing, deploying, and managing software, and is aptly being called “Agentic Cloud.” It has the potential to dismantle the primary proposition of these hyperscalers, breaking through their seemingly unconquerable moat and creating a genuine opportunity for new players to disrupt the market for the first time in nearly 10 years.
Instead of competing on the catalogue size, Agentic Cloud competes on the agent’s intelligence. Let’s delve into a world where Agentic AI is intersecting with the Cloud, which is a technology shift that might have an even steeper adoption curve than the original cloud adoption.
The Cloud Story – And Where Agentic AI Comes In
The growth and evolution story of the Cloud offers a relevant analogue for how Agentic AI might also play out, as both represent structural technological shifts for the enterprise. As we mentioned earlier, Cloud spends grew phenomenally in 15 years at an annual rate of nearly 25%, with an even faster growth rate of 30% per annum in its early years of 2010–2015. This wasn’t merely “growth” – it was completely reimagining the IT infrastructure.
Agentic AI is landing in an environment that’s already digital-first, unlike the early days of Cloud where physical infrastructure had to be designed and built, and trust had to be earned. Agentic AI basically employs autonomous AI agents, which are specialised programs which perform complex tasks by combining LLMs (large language models) with software tools. These agents use integrated tools to interpret natural language requests and execute all necessary actions.
For instance, cloud administrators could prompt AI agents to “deploy a new storage bucket and configure it to be read-only.” Then, AI agents would automatically create the said storage bucket and apply all the required security settings. This approach eliminates the need for manual policy writing and provisioning, thus simplifying cloud administration and greatly reducing the time people spend on routine tasks.
The Agentic Cloud
Agentic Cloud could be defined as AI systems that translate high-level, intent-driven specifications into fully-configured, provisioned, deployed, and autonomously managed applications and infrastructure. Agentic AI allows administrators to automate tasks that usually require hands-on management, such as managing Kubernetes clusters, configuring access policies, and provisioning resources.
In fact, there are certain real-world implementations that already showcase the technology’s potential, such as MCP (Model Context Protocol) servers designed using the MCP framework.
Agentic AI in the Cloud represents a significant shift in approach for administrators who are accustomed to manually writing policies or using command-line interface tools and consoles. Overall, it’s a more efficient and intuitive way to manage modern infrastructure.
How Agentic AI Works In The Cloud
What happens when AI agents work alongside clouds – and humans? Valuable business outcomes are realised — faster deliveries, lower costs, stronger customer loyalties, and compliance integrated into daily operations.
Firstly, Agentic AI makes it simpler to connect the technology stack across clouds, data centres, networks, and more, with AI agents governing and protecting your data, and spotting and resolving issues before they happen, and driving efficiencies in workflows. AI also greatly simplifies and speeds up cloud migration.
In fact, GenAI can actually extract data from existing environments, automatically reconstructing it within hyperscalers of your choice. What’s more, Agentic AI can drive intelligent agents to provide Tier 1 and Tier 2 services for infrastructure, architectures, and applications hosted in the cloud. Delivering omnichannel support, these agents provide quick automated assistance.
With workloads within cloud-native environments, service providers can simulate and deploy agents directly within the cloud setup, fine-tune them, and even export them for the full use of an enterprise. Just like service providers monitor application performance, they can also manage and monitor these AI agents.
Moreover, this cloud-native development allows teams to design and release applications at breakneck speed. However, the real breakthrough is this approach empowering developers to continuously iterate — whether it’s refining user journeys in real time, rolling out improvements, or even testing new features.
AI agents also add another dimension – observing system performance and user behaviour to guide enhancements and smart decisions, resulting in a cycle of constant innovation. And finally, agentic AI protocols support secure cross-platform communication between agents, making it possible to design multi-agent flows in multi-cloud environments.
What About Humans?
If you’re thinking that Agentic AI is going to replace your teams, relax. It won’t replace them, but will rather elevate them. The future of cloud management is a collaborative one involving both AI agents and humans, and with humans at the helm, the convergence of Cloud and Agentic AI can pave the way for true business transformation.
If the agentic market were to grow at the same rate as the Cloud did in 2010–2024, we could expect nearly USD 300-$600 billion of the total global services opportunities to be realized by 2035–2040 – in merely 10 to 15 years.
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