AI Runs on Data, But its Future of AI Depends on How We Store It
Artificial intelligence is increasingly becoming central to how modern enterprises operate, compete and grow. From predictive analytics and automation to Generative AI and Large Language Models, organisations are investing heavily in intelligent systems that can improve decision-making, productivity and customer experiences.
Yet, behind every advanced AI model lies a more fundamental requirement: data. The quality, scale, security and accessibility of data determine how effectively AI systems can be trained, refined and governed. While the industry has rightly focused on compute power, processors and model performance, the next phase of enterprise AI will also depend on a less visible but equally strategic layer, how organisations store and manage the data that powers intelligence.
As AI adoption expands across sectors such as healthcare, financial services, manufacturing, governance, education and digital commerce, enterprises will need storage architectures that are not only fast, but also secure, cost-efficient, scalable and sustainable.
The Economics of Always-On...
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