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At the core of AI-first operations lies data.
However, navigating this path can be daunting.
Leads the Microsoft Data business across Avanade and Accenture.
Inconsistent information residing in disparate silos renders it unusable for AI, which thrives on clean, unified datasets.
Getting clean, well-maintained data is a significant task and investment.
Making AI accessible is key to this.
This fosters a culture of data-driven decision-making, where insights inform every step of the business process.
This accelerates the realization of value from generative AI and allows organizations to quickly adopt new innovations.
Data governance is also critical to ensuring data quality, consistency, andsecurity.
This can significantly slow down AI development and implementation, especially for businesses dealing with vast and complex datasets.
Generative AI offers a game-changing solution to this bottleneck.
Once inconsistencies are identified, generative AI can then suggest potential corrections based on the context of the data.
This ongoing learning ensures that the data quality fed into AI models remains consistently high.
The impact of leveraging generative AI for data cleaning will be far-reaching.
Businesses must increase their data platform investments to achieve a unified, reliable data foundation.
Only then can they realise their AI aspirations and scale them across their enterprises.
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The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
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