FEATURE: CLOUD SOLUTIONS

In an increasingly volatile world, Karl Havard, CCO, Nscale, says relying on large, multinational public cloud environments will be seen as a riskier option for an increasing number of businesses. and store data. Even before the GenAI boom, there was an increasing need for data privacy and security ushered in through GDPR regulations and rising cyberattacks. These concerns have not abated – as organisations are becoming increasingly aware of international regulations like the PATRIOT Act that put their data at risk, we’ re starting to see businesses take more of an interest in where their data is stored.

Growth in the private cloud services market is set to surge from $ 92 billion in 2023 to a staggering $ 405 billion in 2033 according to a report from Future Market Insights. And in a 2024 report on workloads from IDC, more than 80 % of respondents expected to see some level of cloud repatriation in the coming year.

The allure was enticing: lower costs, greater agility and access to cloud platform services that provide opportunities for innovation. For a while it seemed like the perfect solution for modern businesses.

However, as more companies adopted cloud services and data became increasingly valuable and abundant, the reality began to diverge from expectations.

As a result, businesses are increasingly revisiting private cloud today.

Reconsidering cloud strategies for the AI era

Whilst not solely down to the boom in AI, it is in large part responsible for this dramatic swing back to private cloud. AI holds a tantalising promise of immense productivity gains, but these advancements also come with important considerations on how it should be applied. Concerns remain around data security, privacy and the risks of accidentally leaking intellectual property or confidential company data with the negative impact this can have on a company’ s reputation.

To compete today, businesses need cloud infrastructure optimised for AI that doesn’ t incur unexpected usage surcharges or negatively impact other business applications.

However, public clouds are not proving sufficient for this and businesses also aren’ t adequately scoping out what they need for their AI projects.

The driving force behind the move to public cloud was cost. Most companies bought into it in the hopes of achieving significant savings by renting server space rather than owning them outright. It also meant they jettisoned any maintenance or upgrade costs. However, according to a report from McKinsey, only 55 % of European businesses are satisfied with their cloud investments.

Research by RAND found that the failure rate is higher than 80 %, despite $ 675 billion being spent on cloud computing last year. Although it is common to make use of the public cloud to run models, in part due to easy scaling capabilities, businesses are only just starting to recognise that it isn’ t a one-size-fits-all solution.

The retreat to private cloud

At the same time, businesses also began to gain a transformative understanding of how they should use

As well as having the infrastructure required to train and run the most advanced LLMs, businesses also need

40 INTELLIGENTCIO APAC www. intelligentcio. com