AI is Moving Faster Than the Enterprise

The Enterprise Cloud Index is Nutanix's annual research report that examines how cloud, IT, and engineering executives are navigating infrastructure modernization. The 2026 edition specifically focuses on how AI is transforming the way organizations modernize their infrastructure and applications.

This report is designed for cloud, IT, and engineering executives who are responsible for infrastructure modernization, application strategy, and AI readiness. It's particularly valuable for leaders navigating the challenges of scaling for AI while maintaining application agility, portability, sovereignty, and cost control.

The 2026 Enterprise Cloud Index examines AI's impact on infrastructure modernization, the role of containers in AI strategies, challenges with shadow AI and departmental silos, data sovereignty concerns, and how enterprises are preparing their infrastructure for AI workloads.

The 2026 Enterprise Cloud Index is available as an ungated resource. Simply click the 'Get the Report' button on this page to download your copy immediately—no forms or registration required.

According to the research, 87% of executives believe that AI tools and agents implemented outside of official oversight create business risk. This 'shadow AI' phenomenon occurs when business departments operate in silos and implement AI initiatives without consulting IT.

The data reveals that 79% of organizations encounter AI applications or agents implemented by employees in non-IT functions. This decentralized approach to AI adoption, while demonstrating enthusiasm for innovation, introduces governance and security challenges.

Yes, significantly. 82% of executives believe that silos between business units and IT make it difficult to effectively execute technology initiatives. This fragmentation becomes especially problematic when scaling for AI.

AI is accelerating containerization dramatically—85% of executives think AI is meaningfully accelerating adoption of containers for their organization. Containers are becoming a core strategy for providing application and workload agility, portability, data sovereignty, and cost control.

Containers are becoming the default method for delivering cloud-native, portable, and scalable architectures that AI requires. They can provide standardization, governance, and enable scalable AI operations while addressing infrastructure gaps.

The research identifies several key hurdles: AI is outpacing enterprises' readiness, shadow AI creates governance issues, organizational silos prevent coordinated execution, and infrastructure gaps limit scalability. Containers offer a path forward by providing standardization and governance.

AI amplifies sovereignty concerns because of regulatory demands, data privacy requirements, and compliance obligations. Enterprises are adopting hybrid, local, and compliant architectures that balance AI performance with regulatory demands.

Digital sovereignty is becoming a strategic priority as organizations seek greater control over the infrastructure, platforms, and environments where AI operates. While data sovereignty focuses on where data resides and how it is regulated, digital sovereignty extends to how AI applications are deployed, governed, and controlled across jurisdictions.

As AI adoption accelerates, organizations must keep data and AI processes compliant while retaining operational control. This is driving increased adoption of hybrid and on-premises architectures that balance AI innovation with sovereignty, security, and regulatory requirements.

Infrastructure modernization for AI involves ensuring your technology foundation can support application and workload agility, portability across environments, data sovereignty requirements, and cost control—while enabling the scale and performance AI workloads demand.

Hybrid cloud architectures are increasingly important for balancing AI performance needs with data sovereignty, compliance, and cost considerations. They allow enterprises to deploy AI workloads where they make the most sense while maintaining governance.

The report suggests that standardization through technologies like containers, establishing clear governance frameworks, and breaking down silos between business units and IT are essential steps for managing shadow AI risks while enabling innovation.

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