Aging IT infrastructure can have a significant detrimental impact on enterprises, not least of all in the age of artificial intelligence (AI) and an increasingly competitive global business landscape.
Research from McKinsey as far back as 2017 specifically highlighted legacy IT infrastructure as a major hurdle for tech leaders and organizations globally, with 85% of respondents identifying this as their key challenge in the years to come.
But while digitization and IT infrastructure overhauls have continued at pace, enterprises have frequently encountered problems in updating legacy IT systems.
Combined with technological advances, such as the need to accommodate AI workloads, this has presented IT leaders with acute challenges and created a delicate balancing act for those embarking on modernization programs.
A study from Expereo, for example, revealed that 40% of CIOs still report legacy IT systems as a major inhibitor to future growth. Similar analysis in NTT Data’s Lifecycle Management Report, published in June 2024, showed 94% of C-suite executives identified legacy infrastructure as the leading issue impeding business agility.
Given the issue is recognized by both these groups of people, it may seem strange that it persists. However, the sheer pace of modernization in recent years, the expansion of technologies adopted by enterprises, and the cost associated with IT modernization all play a role.
Additionally, many organizations made the shift to public cloud infrastructure over the last decade and while it enabled them to capitalize on new technology and software trends, it has come at a price. The convenience of public cloud has been paralleled by growing costs, which many enterprises have struggled to contend with in recent years.
In a survey by Daisy Corporate Services, for example, nearly one-third (31%) of IT decision-makers said budgetary constraints were the leading barrier to IT modernization in this regard.
However, the costs associated with failing to modernize can be even more consequential for enterprises, research shows, and can result in a vicious cycle of rising costs and the accumulation of additional, cumbersome technical debt.
In the same study, IT leaders revealed that almost one-third (29%) of their overall budgets are allocated toward maintaining inefficient legacy hardware.
This research aligns with previous industry analysis from Gartner, which predicted that by as early as 2025, enterprises that fail to grapple with technical debt and legacy hardware could spend around 40% of their budgets to maintain it.
With this confluence of issues in mind, it’s critical that IT leaders prioritize modernization to unlock benefits for their organizations – and there are many.
Analysis from Aberdeen Strategy Research in association with Hewlett Packard Enterprise (HPE) found businesses that upgrade and modernize server infrastructure are 40% more likely to reduce IT costs and unlock savings.
But performance improvements are also a major appeal for IT leaders in this regard, the study noted. Those who upgraded infrastructure were 80% more likely to deliver performance boosts.
Performance and sustainability are key
Enterprises approaching generative AI must be mindful of infrastructural considerations given its critical role in broader strategies. Infrastructure represents the critical foundation blocks for the enterprise, underpinning compute capabilities, enabling future scaling, and ultimately fuelling innovation.
With this in mind, choosing the right compute infrastructure can be the difference between delivering success and potentially falling behind competitors in the current business landscape.
Scalability of infrastructure has become a key focus for CIOs in recent years, especially amidst the growing adoption of generative AI tools and solutions. This enables enterprises to adapt resource allocation based on their unique individual
In addition, scalability provides enterprises with the ability to improve latency and, long term, reduce costs by allocating resources on an as-they-go basis.
But while the need for high-performing, scalable infrastructure is critical to the modern enterprise in the AI era, so too is sustainability.
The rise of the technology has prompted widespread industry concerns over the environmental impact of IT infrastructure as organizations globally race to develop, build, and roll out AI solutions.
Analysis from McKinsey predicts that demand for AI-ready data center capacity will surge at an average rate of 33% each year between 2023 and 2030, even in a “midrange scenario”. This accelerating demand is expected to place significant strain on both energy grids globally and the environment at large.
But infrastructure modernization investment is a two-pronged solution to both unlocking sustainability gains, and driving efficiency improvements.
Research from IDC, for example, shows that investment in sustainable infrastructure can have marked benefits, with 26% of firms reporting lower energy costs and an additional 26% delivering streamlined operational efficiency.
“Investment in modern, intelligently automated infrastructure helps lower energy costs and enables better operational efficiencies throughout the business — directly improving profitability,” the report states.
Choosing the right provider
Enterprises have a variety of options at their disposal today that maintain this balance between efficiency and sustainability – but this is where selecting a provider that matches both these prerequisites becomes critical.
Hewlett Packard Enterprise’s (HPE) ProLiant servers, for example, provide enterprises with the best of both worlds. Powered by Intel’s Xeon processors, these are designed specifically to handle complex AI workloads, such as computer vision or retrieval augmented generation (RAG).
This server series can provide up to one-third higher GPU density, enabling increased flexibility for AI workloads at the edge, according to HPE, and in the data center.
“Using HPE ProLiant Gen11 servers with Intel 5th Gen Xeon processors also helps organizations control costs through rightsizing and scaling on-demand,” the whitepaper noted. “Indeed, AI workloads run faster on HPE ProLiant Gen11 clusters with predictable, completely visible costs.”
Using ProLiant servers, enterprises have the flexibility to scale capacity up or down based on current demands. Similarly, this server series also allows users to add “burst capacity” to contend with heightened periods of demand.
ProLiant servers such as the DL320 Gen 11, for example, are also specifically designed for deployments at the edge, providing marked benefits for users in terms of flexibility.
Users can unlock lower latency and connectivity costs while enabling them to access real-time insights on-site where the data is generated, further improving flexibility and reducing their reliance on disparate data centers or cloud resources.
From a sustainability perspective, HPE ProLiant servers also boast equally impressive benefits for enterprises.
Research shows HPE ProLiant Gen 11/Gen12 servers deliver a 60% smaller data center footprint than industry counterparts, alongside 81% lower power and cooling costs compared to previous generation servers.
Energy-efficient performance isn’t the only key factor here, either. Next-gen servers such as the ProLiant series use liquid cooling techniques, as opposed to traditional air-based cooling.
Using liquid cooling has notable advantages for high-performance systems, enabling users to reduce their carbon footprint by 87%, as well as cost reductions of 86% annually, according to HPE.
Energy-efficient performance isn’t the only key factor here, either. Next-gen servers such as the ProLiant series use liquid cooling techniques, as opposed to traditional air-based cooling.
Using liquid cooling has notable advantages for high-performance systems, enabling users to reduce their carbon footprint by 87%, as well as cost reductions of 86% annually, according to HPE.
For more information on the HPE ProLiant series and how they can benefit your enterprise, please visit the HPE website.
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