Public sector modernisation accelerates but 73% lack infrastructure for AI workloads on-premises

Public Sector Modernisation Gains Momentum Despite Readiness Gaps

India's government agencies and educational institutions are accelerating AI adoption to transform citizen experience and operational efficiency, yet face significant infrastructure challenges that threaten to slow deployment at scale. According to the 8th Annual Nutanix Enterprise Cloud Index Public Sector Report, while organizations are embedding artificial intelligence into mission-critical functions such as fraud detection, service delivery, decision-making and resource management, 73% of public sector infrastructure remains unready to run complex AI workloads on-premises1

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Shadow AI Emerges as Critical Governance Challenge

The research reveals a troubling governance gap as public sector modernisation efforts advance. An overwhelming 96% of IT leaders report AI applications being implemented outside IT functions, with 91% confirming that unvetted AI usage creates mission and security risks1

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. This proliferation of shadow AI has become the defining governance challenge for the sector. Meanwhile, 84% of respondents indicated that organizational silos make technology initiatives harder to execute, compounding the difficulty of maintaining regulatory compliance across distributed environments.

Containerization to Support AI Drives Infrastructure Strategy

Despite these infrastructure challenges, public sector organizations are increasingly turning to application containerization to modernize their technology foundations. The Nutanix survey found that 87% of public sector technology leaders expect their reliance on containerization to scale up over the next three years, while 86% believe AI adoption is accelerating container adoption1

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. Already, 83% are building new applications using containers as they prepare for distributed data environments, escalating cyberattacks, and AI-driven innovation1

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Hybrid Infrastructure Becomes Essential for AI Workloads

Government and education institutions are adopting hybrid infrastructure to balance innovation with security, compliance, sovereignty, and operational resilience. Daryush Ashjari, Chief Technology Officer and Vice President of Solution Engineering, APJ at Nutanix, emphasized that "the organisations moving ahead are those that stop chasing every new capability in isolation and instead consolidate their foundations. By prioritising secure, containerised architecture, these leaders are establishing the guardrails required to harness AI confidently"2

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. The challenge lies in juggling legacy systems, private clouds, and migration to modern cloud infrastructure simultaneously, often without a unified control plane2

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Leadership Mandates Outpace Infrastructure Reality

The report highlights a critical disconnect between executive directives and operational readiness. While mandates to deploy AI applications often come from leadership driven by modernization goals and efficiency targets, these directives frequently fail to account for what is required to operationalize AI at scale, particularly the infrastructure needed for on-premises AI support1

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. This gap creates pressure on IT teams to deliver transformational capabilities while ensuring data sovereignty and maintaining security across hybrid environments that serve diverse communities2

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. The findings suggest organizations must build modernized infrastructure capable of delivering performance, maintaining regulatory compliance, and supporting mission governance not just centrally, but at the point of delivery where AI directly affects citizen services, public safety, and educational outcomes2

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