You have AI ambitions. Can your infrastructure keep pace?

It’s been clear for some time that AI is not just another technology, but a fundamental shift in how we operate. It has the potential to change every aspect of an organisation, from operations to innovation right through to decision making.

But scratch the surface and you’ll uncover an age-old problem that AI has only accelerated: collecting, securing and managing data. Globally, 402.74 million terabytes of data is created each day and only a fraction of it is ever captured and utilised.

Data is the backbone of innovation, informing smarter decisions and unlocking opportunities for growth, productivity and exceptional user experiences. However, capturing and fully harnessing its potential isn’t as simple as it sounds.

Where data meets complexity

The large and dynamic digital landscape presents significant challenges in managing, securing and using this data to drive meaningful outcomes. Organisations are grappling with how to:

• regain control over sprawling data environments
• navigate evolving regulatory landscapes
• address mounting cybersecurity threats.
   

It is no surprise that 83% of enterprises plan to migrate workloads back to private cloud, reflecting the shift toward more controlled, secure and predictable data management solutions. While the public cloud provides flexibility, it often results in unexpected costs and offers limited control over mission-critical assets.

The rapidly increasing scale of cybersecurity threats, coupled with stricter regulatory requirements, makes visibility and control of data more essential. Without a secure and well-structured system for managing data, organisations risk operational inefficiency, compliance issues and security vulnerabilities.

A one-size-fits-all solution fails in this dynamic environment. Instead, organisations require purpose-built infrastructure tailored to support these varying demands. High-performance applications, for example, need speed and low latency, while capacity-intensive tasks demand scalability and cost efficiency.

Architecture that’s fit for purpose

Managing data isn’t just about where it’s stored — it’s about how it’s accessed, secured, and leveraged to fuel innovation. Organisations need the flexibility to adapt quickly to changing priorities, run diverse workloads where and how their business demands and view IT as a strategic driver for growth.

Doing so requires IT architectures that support diverse workloads. Odds are a modern business manages a wide variety of workloads, from legacy systems to cutting-edge applications. These span on-premises and, yes, all types of cloud environments, which means you require flexible performance solutions tailored to different locations and demands.

High-performance environments require high speed and low latency, while capacity-intensive tasks demand scalability and cost-efficiency. Universal solutions promise to do it all, but they often falter when it comes to the specific demands. A single platform trying to fit every scenario risks diluting its efficiency. You need purpose-built infrastructure solutions tailored to each workload.

The future is disaggregated

The path forward for modern enterprises is disaggregated infrastructure, which allows businesses to deploy resources strategically and efficiently, aligning with specific workload needs.

Disaggregated infrastructure gives you the best of traditional 3-tier IT and the more modular approach of hyper-converged infrastructure (HCI). This gives you both 3-tier flexibility and HCI simplicity. By pooling compute, storage, and networking resources, you access independent scaling, while reducing over-provisioning and cutting costs.

It also gives you support for diverse workloads without vendor lock-in, allowing you to choose hardware and software based on your requirements. This increases efficiency, simplifies management and ensures uninterrupted availability, positioning organisations for future growth.

Striving for simplicity

Speaking of simplifying management, this is key. As IT environments grow more complex, the need for simplicity becomes more apparent. Overly complex systems can lead to inefficiencies, increased costs and slower innovation.

Achieving this relies on automation and integration. This is where the power of AIOps — Artificial Intelligence for IT Operations — steps in, using AI and machine learning to automate IT operations, predict issues and analyse data in real time, reducing the need for your manual efforts and improving system reliability.

Keeping it all safe

Of course, none of this matters if your data and assets aren’t secure. Organisations are facing increasing pressure to protect against outages, cyberattacks and other security risks. The need for comprehensive data protection has never been greater.

You need to secure critical assets everywhere, creating an increasing need for elements such as advanced ransomware detection, zero-trust architecture and air-gapped recovery solutions.

This means you need to ensure consistent data protection operations across on-premises, edge and multicloud environments, providing the efficiencies and automation you need to manage the large amounts of data that will be generated by AI workloads and ensuring valuable information is secure and recoverable. Infrastructure agility keeps your business moving forward. As technology such as AI evolves rapidly, organisations must future-proof their storage infrastructure to keep up with changing demands. This means investing in smart solutions that can scale, integrate with emerging technologies and provide maximum resiliency in case of disruptions or disasters.

Top image credit: iStock.com/JackyLeung