27 May 2025

Nick Burling, Senior Vice President, Product, Nasuni

Pressure for transformation

And in such a competitive landscape, the pressure on company boards to lead change is unrelenting: in IBM research of 2,000 CEOs, nearly two-thirds (64%) acknowledge that ‘the risk of falling behind drives investment in some technologies before they have a clear understanding of the value they deliver.’ Consequently, there is no lack of expectation from boards, and lines of business, for AI-driven business transformation, whether across the enterprise or by individual ‘early adopter’ departments.

But are enterprises, driven by demands to do more with less, in danger of trying to run before they can walk in terms of data infrastructures that support AI and other priorities? Is the tilt towards AI investment detracting from enterprises’ wider modernisation plans and undermining IT leaders and storage teams’ efforts to build safe and robust data management foundations?

Nasuni’s own research of 1,000 purchasing decision-makers across the US, UK, France, and DACH* this year found that CIOs are successfully ring fencing a budget for AI - it’s the top spending priority for almost half (47%) of respondents and nearly all (92%) have found extra budget for AI initiatives. Nearly half (46%) anticipates reduced business costs from AI implementations.

Will data infrastructures cope with AI and transformation?

However, evidence is emerging that enterprises’ data infrastructure challenges are not only holding back CIOs’ desire for early AI adoption. Ongoing challenges such as updating legacy storage environments and consolidating data sets are also leaving many companies struggling to meet their AI, business transformation and data security requirements.

In a recent US/UK-focused survey of data management policy, 26% of organisations said they had no formal data strategy, while 39% admit to having inadequate data governance frameworks. Meanwhile, Nasuni data indicate that many IT and networking teams are grappling with fundamental cloud infrastructure and data connectivity questions: a majority of companies (53%) we questioned admit their data isn’t backed up, immutable and easily recoverable. Nearly half (48%) say security worries are holding up their migration of file data to the cloud.

CIOs are acting decisively to contain the risks from ageing infrastructures and under-realised data management strategies. We found that nearly three-quarters (72%) of firms have, or are planning to, integrate a hybrid cloud storage model combining object storage with intelligent file caching at the network edge, within the next 12 months. It’s telling that survey respondents regard better data security and business resilience as the leading benefit of having a cloud infrastructure - ahead of both cost efficiencies from automated processes, or having an effective AI strategy.

Security and privacy concerns

But the fact remains that, with data infrastructure strategies still playing catch up, C-suite pressure for investing in and implementing AI tools is also surfacing other business-critical security issues for IT leaders.

We found that one in three enterprises (34%) are more concerned by potential data security and privacy challenges ahead of AI adoption than they are about having the right skills on their team to integrate AI tools (27%), while half (51%) admit they don’t operate a dedicated security team for their infrastructure.

Cyber threats

But if planning an AI platform already carries security risks for many CIOs, their organisation’s varying ability to repel and recover from the daily onslaught of cyber-attacks, hints at deeper troubles ahead.

In our research, nearly seven in ten (69%) companies have experienced a cyber-attack and almost two-thirds (62%) are still confident of recovering their business-critical unstructured data and shaking off such attacks. However, we found that nearly half (45%) have experienced a security breach resulting in a ransom demand, business downtime, data loss, reputational damage, or other issues recovering their data. Enterprises’ real-life cyber-attack responses and data recovery processes could well be falling short of the best practices required for the AI era.

AI and hybrid cloud

Daily pressure for companies to transform operations and do more or better with less, is driving near-universal investment in AI tools. Our research shows, however, that CIOs and networking teams will need to secure further support and funding if they are to successfully deliver crucial advances such as hybrid cloud infrastructures and consolidated data to derisk and deliver AI and other innovation plans. Secure hybrid cloud infrastructures and data connectivity remain key touchpoints for today’s emerging dynamic AI-driven enterprises.