Time to Reassess On-Premises Data Storage for AI?
Stephen Redmond
AI Visionary | Head of Data Analytics and AI at BearingPoint Ireland. Delivering real business value to our clients by harnessing the transformative power of data and AI.
Hard not to notice that #AI is reshaping industries, and IT organisations are coming under pressure from their business stakeholders to support delivery of AI use cases. This means that the infrastructure underpinning data strategies is coming under increasing scrutiny. For organisations still relying heavily on on-premises data storage, the question is no longer if a move to the cloud should be considered—but when and how.
One of the most critical steps in this journey is a comprehensive review of the Total Cost of Ownership (TCO) of existing on-premises infrastructure. This is especially vital for organisations looking to leverage AI, where data accessibility, scalability, and high levels of security are critical.
The Hidden Costs of On-Premises Storage
On the surface, maintaining data on-premises may appear cost-effective. The infrastructure is already in place and humming away nicely. However, a deeper look often reveals a different story:
Hardware depreciation and refresh cycles every 3–5 years for most organisations.
Energy and cooling costs, which can be substantial and impact carbon footprints.
Staffing and maintenance overheads for managing servers, backups, security and never-ending patch deployments.
Downtime risks and the cost of disaster recovery planning.
Scaling costs and the need for careful, pragmatic decisions on new hardware acquisition.
These costs are frequently underestimated or spread across departments, making them less visible in budgetary discussions.
AI Demands a New Kind of Infrastructure
AI workloads are data-hungry and compute-intensive. They require:
High-performance storage that can scale dynamically.
Access to GPUs and specialised compute resources.
Seamless integration with data pipelines and analytics tools.
On-premises environments often struggle to meet these demands without significant investment. In contrast, cloud platforms offer ready-to-use AI services, elastic compute, and global scalability, enabling organisations to innovate faster and more efficiently.
Why a TCO Review Matters Now
A full TCO review provides a clear, data-driven foundation for strategic decision-making. It allows organisations to:
Compare true costs of on-premises vs. cloud storage.
Identify inefficiencies and underutilised resources.
Model future needs, especially for AI and data analytics.
Build a business case for modernisation and digital transformation.
Key Considerations for a TCO Review
When conducting a TCO analysis, organisations should evaluate:
Capital Expenditure (CapEx): Initial hardware, installation, and setup costs.
Operational Expenditure (OpEx): Power, cooling, staffing, maintenance, and software licensing.
Scalability and Flexibility: How easily can the infrastructure adapt to changing needs?
Security and Compliance: Costs of maintaining regulatory standards and data protection. Especially constant patch roll-outs.
Innovation Potential: Ability to support AI, machine learning, and real-time analytics.
The Strategic Imperative
Your data is not just an asset, it’s a competitive advantage. But to unlock its full potential, organisations must ensure their infrastructure is fit for purpose. A thorough TCO review of on-premises data storage is not just a financial exercise, it’s a strategic imperative.
By understanding the true costs and limitations of legacy systems, organisations can make informed decisions about cloud adoption, modernisation, and future-proofing their data strategy.