Five in every six (83%) public sector organisations have a generative AI strategy in place, with 54% actively implementing, and 29% preparing for implementation.
This is according to a report from Nutanix. It is based on a study conducted in the fall of 2024 by Vanson Bourne. The research firm surveyed 1,500 IT and DevOps/Platform Engineering decision-makers in North and South America; Europe, the Middle East and Africa (EMEA); and Asia-Pacific-Japan (APJ) region.
As public sector organisations ramp up generative AI adoption, 76% of IT decision-makers say their current infrastructure needs moderate to significant improvement to support modern, cloud native applications at scale.
This year’s public sector ECI found that infrastructure modernisation emerged as a top priority, underscoring the growing demand for systems capable of meeting generative AI’s requirements for enterprise-ready data security, data integrity and resilience.
This year’s report also revealed that public sector leaders are increasingly leveraging generative AI applications/workloads into their organisations. Real-world generative AI use cases across the public sector gravitate towards constituent/employee support and experience solutions (like chatbots) and content generation.
However, concerns remain with 92% of public sector leaders highlighting the need for their organisations to do more to secure generative AI models and applications.
The results of that need, according to 96% of respondents, is security and privacy becoming higher priorities for their organisations.
“Generative AI is no longer a future concept, it’s already transforming how we work,” said Greg O’Connell, VP of federal sales, public sector at Nutanix.
O’Connell noted that 94% of public sector organisations are already putting AI to work and expect returns in as little as one year.
“As public sector leaders look to see outcomes, now is the time to invest in AI-ready infrastructure, data security, privacy, and training to ensure long-term success,” he said.
Public sector survey respondents were asked about generative AI adoptions and trends, Kubernetes and containers, how they’re running business and mission critical applications today, and where they plan to run them in the future.
Key findings show that generative AI solution adoption and deployment in the public sector will necessitate a more comprehensive approach to data security.
Among respondents, 92% agree that their organisation could be doing more to secure its generative AI models and applications. Still, 96% of respondents agree that generative AI is changing their organisation’s priorities, with security and privacy becoming higher priorities.
Also, there is a need to prioritise infrastructure modernisation to support generative AI at scale across public sector organisations. Unfortunately, 76% of respondents in the public sector believe their current IT infrastructure requires at least moderate improvement to fully support cloud native apps/containers.
In addition, generative AI solution adoption in the public sector continues at a rapid pace, but there are still challenges to overcome. Among respondents, 94% said their organisation is leveraging generative AI applications/workloads today.
However, organisations in the public sector also note a range of challenges and potential hindrances regarding generative AI solution development and deployment, including data security and privacy, and the need for continued upskilling and hiring to support new generative AI projects/solutions.
Further, application containerisation and Kubernetes deployment are expanding across the public sector. Results show that 96% of segment respondents saying their organisation is at least in the process of containerising applications. This trend may be driven by the fact that 91% of respondents in the public sector agree their organisation benefits from adopting cloud native applications/containers.
