The next phase of cloud: Reimagining innovation with AI

Cloud computing has long been the backbone of digital transformation. Initially adopted to meet infrastructure demands and reduce costs, it evolved into a platform for building applications faster through cloud-native architectures. Today, we stand at the threshold of a new era — one where AI and cloud-native data platforms converge to unlock unprecedented innovation. Let’s explore what CIOs need to focus on to make sure these platforms are delivering.

The journey of cloud innovation from infrastructure to intelligence has unfolded in three distinct phases:

1. Cost efficiency (cloud as scalable infrastructure to cut IT overhead): This efficiency frees resources and budget that can be reinvested into new ideas and innovation.
2. Agility (cloud-native development for faster delivery of applications): Greater agility allows organizations to experiment rapidly and bring innovations to market sooner.
3. Intelligence (AI-powered applications on cloud platforms to transform processes and experiences): Intelligence elevates innovation by enabling smarter decisions and new capabilities.

This last phase is where the real gains become clear. At NTT DATA, we’ve experienced this firsthand after embedding AI into our engineering processes, with productivity gains of 30%–40%.

Are you cloud-aware or cloud-evolved?

Most CIOs are very much cloud-aware. They recognize it as a priority infrastructure solution, understand the importance of security and threat protection, and analyze cloud workloads and usage to contain costs. But that’s no longer enough. The rise of AI — and especially agentic AI, which can act, adapt and learn with minimal human input — demands a shift. The real question is: Are you simply cloud-aware or truly cloud-evolved?

Being cloud-evolved means using cloud and AI not just to run operations more efficiently but also to unlock opportunities to innovate. It’s about moving from managing resources to creating value by leveraging AI and modernization to invent new business models, speed up time to market and deliver a higher ROI.

By using cloud-native platforms, modernized applications and microservices to embed AI deeply into organizations, CIOs can deliver richer customer experiences, empower employees with intelligent workflows and innovate at a pace that matches market disruption.

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What does this look like in real life?

AI has moved far beyond chatbots. For organizations that have modernized applications and embraced cloud-native data platforms, the cloud has become an engine of innovation. They are reimagining entire workflows, launching new products directly in the cloud and reshaping business models in ways that were not possible before. Here are some examples of how the combination of cloud and AI is fueling real-world innovation:

• A Malaysian airline replaced their legacy chatbot with a virtual concierge powered by agentic AI — a 24x7 travel buddy that handles complex inquiries and itinerary planning. This transformation, incorporating Google Gemini and Google Agentspace, has streamlined customer issue resolution, boosted loyalty and increased sales.
• In Chile, the global personal care company L’Oréal launched a GenAI-powered beauty consultant embedded in WhatsApp and Instagram. Built on Microsoft Azure OpenAI, it delivers hyperpersonalized product recommendations to turn everyday social platforms into powerful ecommerce engines. The result? Improved customer data collection, deeper personalization and accelerated conversions.
• In India, HDFC ERGO General Insurance Company, a multinational insurance provider, set a mandate to foster innovation and accelerate transformation through AI and a digital-first mindset. To expand their customer base and improve customer engagement, they modernized and migrated their on-premises applications to the cloud, paving the way for them to emerge as a leader in AI-driven innovation and digital transformation.

Agentic AI has changed the game

Agentic AI is bringing “systems of action” to the forefront. Instead of just following preset rules, these systems make dynamic, context-aware decisions in real time. And when the AI agents are also industry-specialized, they can both execute and evolve generic workflows.

4 key dimensions of agentic AI that stand out and drive cloud innovation:

1. Agentic AI for business applications: Integrating AI and agentic AI into business systems — enterprise resource planning, customer relationship management, supply chain and more — enables predictive insights, automation and decision-making support. From demand forecasting to intelligent customer support, AI and AI agents enrich business processes with intelligence and speed.
2. Agentic AI for customer engagement: This is a new frontier. Autonomous agents can learn, reason and act on behalf of customers or employees. Imagine service bots that don’t just resolve issues but anticipate needs, or procurement agents that autonomously negotiate contracts, creating new ways to innovate customer and partner relationships.
3. Agentic AI for IT process automation: With agentic AI, systems can autonomously manage and optimize enterprise IT operations in real time. By reducing manual effort and making your operations more resilient, it frees your IT team to focus on higher-value work instead of routine firefighting.
4. Agentic AI for software engineering: Here, technology accelerates development by autonomously generating, testing and refining code. Developer teams can build more reliable software through continuous innovation and faster delivery of new capabilities.

The value you gain is immense: customer satisfaction soars because of hyperpersonalized engagement; operational efficiency benefits from the automation of complex, multistep workflows; and innovation happens faster than before as AI agents streamline experimentation and feedback loops. Now, CIOs can elevate IT from a service center to a strategic driver of innovation.

Instead of “build once, use everywhere” for static use cases, we’re entering the “build once, evolve everywhere” era for industry-specific AI systems, where business processes adapt to new regulations, customer demands and market shifts automatically, without months of development.

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How to become a cloud-evolved organization

Migrate: Take the first step to innovation

Migrating workloads to a cloud-native environment is the catalyst for innovation. It reduces legacy constraints, accelerates application development cycles and enables business applications and processes to evolve in sync with market changes. This transforms the cloud from an IT platform into an engine of business innovation.

Modernize: Build cloud-native engines to power innovation

Modernization turns migration into measurable business impact. By refactoring applications, adopting microservices and using cloud-native platforms, you can create modern applications and processes that are intelligent, adaptive and built to scale. Modernization embeds AI into the heart of your operations, resulting in faster product development, smarter workflows and continuous delivery. The result: Your organization runs more efficiently and stays ahead of disruptions through ongoing innovation.

Establish strong data-governance practices

Cloud-native platforms provide the foundation for AI, but it’s data governance that determines whether innovation succeeds or stalls. Without trusted, well-managed data, even the most advanced AI models will fail to deliver impact. By using the cloud to unify data, enforce governance and streamline workflows across environments, you gain both efficiency and resilience. The payoff is reduced risk and the ability to innovate fast and confidently at scale.

Achieve “always on” efficiency, reliability and top performance

To keep critical business services resilient under pressure, embrace site reliability engineering (SRE) alongside AIOps and agentic systems that automate reliability, scalability and recovery. In this way, you gain observability as well as the ability to proactively detect and autonomously resolve issues. Service delivery is faster without sacrificing quality, compliance and security.

Upskill your workforce

Cloud architects, developers and data engineers must understand and master the capabilities of AI frameworks, AIOps practices and the design of AI-native applications. Equally, business leaders need to understand AI’s capabilities before they can envision the fusion of AI with high-value use cases. Finally, to accelerate the design of AI solutions, create cross-functional teams that blend IT expertise, business expertise and domain knowledge.

Take the (strategic) lead

For CIOs, the journey from cloud-aware to cloud-evolved is a strategic mind shift that brings innovation to the forefront. Cloud migration lays the foundation; application modernization unlocks agility; AI and agentic AI create new possibilities; skill-building empowers people; and the combination of microservices and accelerators drives speed.

But the true mandate is bigger: To transform cloud from an IT platform into a business innovation engine. The CIO’s leadership turns these capabilities into competitive advantage — reshaping customer experiences, reinventing business models and driving growth.

The organizations that succeed will be those that innovate continuously, with CIOs leading the way as strategic visionaries who will define what comes next.

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