Salesforce report shows poor data quality threatens AI success
Most organisations risk AI failure due to unreliable data, prompting Salesforce to call for unified, trusted, and well-governed data ecosystems.
A new Salesforce report warns that most organisations are unprepared to scale AI due to weak data foundations. The ‘State of Data and Analytics 2025’ study found that 84% of technical leaders believe their data strategies need a complete overhaul for AI initiatives to succeed.
Although companies are under pressure to generate business value with AI, poor-quality, incomplete, and fragmented data continue to undermine results.
Nearly nine in ten data leaders reported that inaccurate or misleading AI outputs resulted from faulty data, while more than half admitted to wasting resources by training models on unreliable information.
These findings by Salesforce highlight that AI’s success depends on trusted, contextual data and stronger governance frameworks.
Many organisations are now turning to ‘zero copy’ architectures that unlock trapped data without duplication and adopting natural language analytics to improve data access and literacy.
Chief Data Officer Michael Andrew emphasised that companies must align their AI and data strategies to become truly agentic enterprises. Those that integrate the two, he said, will move beyond experimentation to achieve measurable impact and sustainable value.
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