How agentic AI transforms cloud — with humans at the helm

Ten years ago, cloud moved from a promising concept to a proven business enabler. For CIOs, it delivered three critical advantages: speed to market, the ability to scale operations on demand and the ability to keep services running reliably. These capabilities reshaped how they invested in technology, transforming IT from a cost center into a driver of growth and innovation.  

Fast forward to today, and a new wave is crashing in: AI. But not just AI in theory: Practical, agentic AI-driven automation is taking routine tasks off our plates, applying intelligence to spot risks before they escalate and giving teams back the time to focus on real growth.

Far from just another passing technology trend, the convergence of AI and cloud is the disruption that redefines the digital era. Cloud gave organizations speed, scale, and resilience; AI adds intelligence, automation and adaptability. Together, they form a platform that streamlines operations, fuels innovation, accelerates decision-making and opens doors to opportunities we’ve only begun to imagine.

These intelligent agents as tireless digital teammates. Even the most complex cloud migration projects can now benefit from AI-powered discovery, with trained models and analytics delivering critical insights on your environment. Your teams reach their targets faster and with less effort because of these extensive AI-powered and AI-automated capabilities.

This is the start of a new chapter for CIOs, where the cloud becomes less of a utility and more of a growth engine — with humans firmly in the driver’s seat.

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5 areas where agentic AI is changing cloud management

What happens when AI agents work alongside clouds? You realize valuable business outcomes — faster delivery, lower cost, stronger customer loyalty and compliance built into daily operations:

1. Cloud platforms

Agentic AI makes it simpler to connect your technology stack across clouds, networks, data centers and more, with AI agents driving efficiencies in workflows, protecting and governing your data, and spotting and resolving issues before they happen.

2. Cloud migration

AI speeds up and simplifies cloud migration. GenAI can extract data from existing environments and automatically reconstruct it within your hyperscaler of choice.

3. Operational support

Agentic AI can power intelligent agents that provide Tier 1 and Tier 2 services for applications, architectures and infrastructure hosted in the cloud. These agents deliver omnichannel support to provide rapid, automated assistance.

4. User experience

Once workloads are in a cloud-native environment, a service provider can deploy and simulate agents directly within the cloud setup, fine-tune them and export them for an organization’s full use. Just as the service provider monitors application performance, they can monitor and manage these AI agents to keep them working optimally.

Cloud-native development — powered by AIOps, microservices and accelerators — also allows teams to build and release applications with unprecedented speed. The real breakthrough lies in how this approach empowers developers to iterate continuously — testing new features, rolling out improvements and refining user journeys in near real time.

AI agents add another dimension, observing user behavior and system performance to guide smart decisions and enhancements. The result is a cycle of constant innovation: applications that evolve seamlessly with changing customer needs and deliver personalization, speed and reliability at scale.

5. Multicloud environments

Standardized agentic AI protocols support secure, cross-platform communication between agents. This makes it possible to design multiagent workflows that span different clouds — an agent in Azure can collaborate seamlessly with one that’s accessing a dataset in Google Cloud Platform. In a supply chain scenario, this could enable real-time coordination between procurement, logistics and inventory agents across different cloud providers.

The importance of human oversight

Agentic AI won’t replace your teams. It will elevate them — and with humans at the helm, the convergence of AI and cloud can enable true business transformation.

The future of cloud management will be a collaborative model involving both humans and AI agents. Already, generalist agents assist employees with day-to-day tasks such as data retrieval, report generation and workflow coordination, while specialized agents focus on cloud optimization, networking, security and compliance. Over time, these agents will become even more personalized and context-aware — but their greatest value will emerge when paired with skilled human control.

While agentic AI can handle well-defined tasks with remarkable speed and accuracy, the cloud is a complex, dynamic environment where variables change constantly and unexpected dependencies can appear. Human-in-the-loop oversight is the guardrail that builds trust.

In practice, this means AI agents can recommend actions, but a human cloud engineer, security analyst or site reliability engineer can review and approve changes before they are executed in production. This approach also allows for critical context to be provided, including organizational priorities, regulatory nuances or new business requirements.

And when AI decisions are transparent, auditable and aligned with enterprise priorities, CIOs instill confidence in boards, regulators and stakeholders.

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The CIO as strategist

As this convergence takes shape, the role of the CIO is also evolving. Instead of just managing technology, you’re orchestrating business transformation. AI agents free your teams to innovate, compliance becomes more proactive, and resilience is built into the way the business operates.

But accessing the full potential of AI and cloud requires collaboration. Work with other C-level leaders, business units and managed service providers with full-stack expertise to align these capabilities with what matters most: growth, efficiency and customer trust.

NTT DATA’s Agentic AI Factory helps organizations that are caught in the “pilot trap,” with scattered experiments, siloed expertise and an inability to industrialize AI. It’s a platform and operating model designed to transform your entire organization’s approach to every aspect of agentic AI: intake and ideation, rapid prototyping, compliant deployment and continuous improvement.

This is part of the evolution of our Smart AI Agent™ Ecosystem, which draws on our full-stack value proposition to address this transformation comprehensively — through strategic consulting, implementation and system integration, industry-specific use cases, proprietary agent orchestration platforms, managed operations and private AI capabilities.

A new focus for the AI era

Still, technology is just one side of the equation. To unlock AI’s full potential in the cloud, CIOs must ensure their organizations are developing the right skills both within their IT teams and in several other key areas, including:

• Data quality: AI relies on unified, clean and trusted data. Robust data governance, proper labeling and regular quality checks are fundamental.
• Compliance: Any automation in a cloud environment must meet strict compliance requirements, especially in industries such as finance, healthcare or government. Make compliance teams part of the full deployment lifecycle, from design to continuous monitoring.
• Ethical and governance considerations: Consider broader ethical concerns about transparency, fairness and accountability in AI decision-making. In the cloud context, AI agents that learn from skewed historical data may inadvertently make biased decisions, such as prioritizing certain workloads or users. Set out clear ethical and governance guidelines for AI use in your organization.
• Financial discipline: FinOps practices create transparency and give you control over consumption.

Simply put, the value of AI and cloud must be pursued together. Cloud provides the foundation, while AI extends its value. Combined, they enable responsible and sustainable transformation.