Kyndryl Cloud Readiness Report: Hybrid cloud shapes the future of AI and enterprise agility
Organizations adopt strategic cloud architectures to drive innovation, strengthen governance,
and secure AI value
The report reveals that while cloud computing has become the backbone of enterprise operations — growing into a more than
"The gap between a reactive and a deliberate cloud strategy has never been more consequential," said Nicolas Sekkaki, Global Cloud Practice Leader,
Key findings from the report:
- Sovereignty and security are reshaping cloud strategy – 75% of leaders express concern about the geopolitical risks of storing and managing data in global cloud environments, while 65% have already modified their strategies in response to new data sovereignty regulations.
- Hybrid and multi-cloud are now the norm – 84% of leaders intentionally use multiple clouds, and 41% are repatriating at least some data to on-premises environments — balancing control, performance, and compliance.
- AI depends on deliberate cloud design – 89% of leaders say cloud investments have made it easier to use AI, but 35% cite integration challenges as a top barrier to realizing ROI. Organizations are increasingly turning to specialized infrastructure, including private AI or neoclouds, both optimized for GPU-powered AI workloads, to balance computational power with cost control.
- Cloud security is evolving for an AI era. As threats rise — with 82% of organizations experiencing a cyber-related outage this year — enterprises are responding with more adaptable architectures and enhanced security capabilities. 91% say their cloud infrastructure provides the flexibility to adapt to new regulations, and 75% are investing in AI for cybersecurity — more than any other AI capability.
From reactive to strategic: designing the future cloud
The report underscores that architecture now defines enterprise control. Enterprises that approach cloud as a strategic, intentional capability — aligning infrastructure, governance, and data — are best positioned to integrate AI securely, meet regulatory demands, manage costs, and accelerate innovation.
The rise of agentic AI is driving this shift. Organizations are increasingly training models in public clouds for scalability and running them in private environments for governance — combining performance with trust. Hybrid architectures are emerging as the intelligent foundation that connects public and private environments seamlessly, enabling enterprises to balance performance, security, and cost as they operationalize AI.
Security and sovereignty are no longer constraints, but design principles for trust and interoperability – essential for the AI-ready enterprise. Global hyperscalers are localizing infrastructure to meet new regulatory standards, while enterprises are building architectures that allow data to move securely across borders and providers.
Drawing on insights from
To read the report, visit
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