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I dont think we can say any businesses are not considering how to weaveAI toolsinto their organization.
VP, Systems Engineering, EMEA, Nutanix.
Data: The Cornerstone of AI
At the heart of AI liesdata.
Without high-quality, well-structured data, even the most advanced AI models will fail to deliver meaningful insights.
Organizations must prioritize data readiness by ensuring it is appropriately structured, labelled, and protected from biases.
Failing to do so risks compromising IT integrity, breaking existingsecurityprotocols, and reinforcing incorrect assumptions within AI-driven decision-making.
Data accessibility must be carefully controlled.
AI thrives on information, but not all data should be universally available.
Proper governance ensures that sensitive data remains protected while enabling AI models to function effectively.
Companies that get data preparation right will unlock AIs full potential, turning information into actionable intelligence.
Without it, AI risks becoming a costly experiment.
Organizations must assess where their data resides - on-premises, in thecloud, or at the edge.
And ensure their networks can handle the high-volume data transfers required for AI workloads.
Inference points must also be sufficiently equipped to process information efficiently.
The goal should be to pick the smallest, most efficient models that meet business requirements.
Overengineering AI infrastructure leads to unnecessary costs and complexity, diverting resources from where they are most needed.
In so far as navigating the where AI lives question.
Sensitive data often necessitates on-premises deployment, while AI-driven customer-facing applications may benefit from cloud-based scalability.
A unified development environment supporting private and public infrastructures enables seamless integration and optimal performance.
AI as a Tool for Productivity Gains
AIs primary role is to enhanceproductivityacross an organization.
From automating repetitive tasks to personalizing customer interactions, AI is already demonstrating its ability to drive efficiency.
The Urgency of AI Adoption
Where to start?
Companies should take a phased approach, moving from exploration to full-scale implementation with careful planning.
This allows for refinement, addressing unforeseen challenges before they become costly missteps.
Finally, optimizing AI models and continuously refining processes ensures long-term success.
We’ve compiled a list of the best business cloud storage.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
