Nutanix: The Global Enterprise Gen AI Adoption Problem
From automating mundane tasks to transforming business models, Gen AI is reshaping enterprise priorities.
New research from Nutanix, a cloud computing company specialising in hyperconverged infrastructure, reveals organisations are facing substantial challenges in modernising their infrastructure to support Gen AI initiatives.
The company's 7th Annual Enterprise Cloud Index (ECI) indicates that while over 80% of businesses have implemented a Gen AI strategy, nearly all are encountering obstacles when scaling these workloads from development to production environments.
“As businesses rush to harness AI's potential, they face a fundamental question – can their existing IT ecosystems support the scale and complexity Gen AI demands?” asks James Sturrock, Director of Systems Engineering at Nutanix.
“The answer, for many, is a resounding 'not yet.'”
The research identifies that 98% of organisations encounter difficulties when scaling Gen AI workloads from development to production – and integration with legacy infrastructure emerges as the primary barrier.
Scaling Gen AI - The infrastructure imperative
The ECI report highlights containerisation – a method of packaging applications and dependencies in isolated, portable units – as the current infrastructure standard, with 90% of organisations reporting at least partial containerisation of their applications.
Gen AI workloads require substantial computing power, scalability and flexibility, driving this shift toward containerised environments.
This approach provides portability across different computing environments and optimises resource usage.
“Without modernisation, enterprises risk encountering bottlenecks, inefficiencies and higher costs as Gen AI initiatives scale,” James says.
Despite recognising the benefits, 81% of businesses acknowledge their existing infrastructure requires improvement to fully support cloud-native applications and containers.
Nutanix findings show hybrid cloud essential for AI workloads
The report suggests organisations need to implement hybrid and multicloud strategies to ensure deployment flexibility across public and private environments.
Increased investment in orchestration platforms like Kubernetes – an open-source system for automating deployment and management of containerised applications – will be necessary to simplify AI workload management across diverse IT environments.
Security and compliance: A fundamental need
Nutanix reveals 95% of businesses acknowledge Gen AI is changing their security priorities, yet nearly the same percentage admit they could enhance protection for their AI applications.
- 98% of organisations struggle to scale Gen AI from development to production
- Over 80% have a Gen AI strategy, but nearly all face significant implementation hurdles
- 90% expect IT costs to rise due to Gen AI, but 70% anticipate ROI within two to three years
Data privacy, security governance and regulatory compliance have become critical considerations as AI models process vast amounts of sensitive information.
Industries with strict regulatory requirements such as finance, healthcare and government face additional scrutiny.
The implementation of new regulations, including the EU AI Act and UK AI governance frameworks, requires enterprises to embed security into their AI strategies from the beginning rather than applying it retroactively.
This approach encompasses ensuring AI models comply with global data protection regulations, protecting AI workloads from unauthorised access and implementing transparency mechanisms for auditing AI-driven decisions.
The skills deficit: Bridging the talent gap
Technology alone cannot realise Gen AI's full potential.
The ECI research highlights a significant skills gap, with 52% of organisations requiring IT training and 48% needing new hires to support AI initiatives.
“The rapid pace of AI evolution is outstripping the availability of skilled professionals, forcing businesses to rethink their approach to talent acquisition and development,” James explains
Encouragingly, 53% of respondents view Gen AI as an opportunity to develop new expertise within their organisations.
Upskilling programmes, educational partnerships, and AI-driven automation tools that simplify operations can contribute to addressing the talent gap.
Organisations need to implement continuous learning programmes to equip existing teams with AI and cloud computing skills.
Investment in low-code/no-code AI platforms – development environments requiring minimal programming knowledge – can democratise AI usage across non-technical departments.
Enterprise Cloud Index reveals cross-departmental AI collaboration crucial
Nutanix also emphasises that fostering cross-functional collaboration, aligning IT departments with business objectives, will maximise the impact of Gen AI implementations across organisations.
ROI and IT cost considerations
The report reveals 90% of organisations anticipate rising IT costs, primarily due to infrastructure upgrades, talent acquisition, and security investments.
However, 70% expect to realise returns within two to three years, driven by operational efficiency improvements and innovation.
Businesses must balance immediate expenses with long-term benefits by focusing on AI projects delivering measurable value.
Aligning AI initiatives with strategic goals such as improving customer experiences, automating repetitive tasks, and optimising operations will be essential for achieving return on investment.
“Organisations need to prioritise high-impact AI use cases with clear business outcomes to shorten ROI times, while leveraging cloud-based AI services to reduce upfront infrastructure investment,” says James.
The survey further indicates organisations should continuously measure AI performance to refine deployment strategies. Companies that fail to modernise infrastructure, secure data and invest in talent risk falling behind in the Gen AI-driven business landscape.
“From rethinking IT architectures to fostering an AI-ready workforce, the steps taken today will determine success tomorrow,” James says.
“With a clear strategy focused on modernisation, security, and people, businesses can unlock the full power of Gen AI, transforming not just their IT priorities but their entire approach to innovation and performance.”
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