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ZDNET's key takeaways
Be warned: give AI rubbish data and it'll give you rubbish back.
Take a strategic approach to data collection that focuses on gold dust.
Be flexible, as language models and business demands can change.
Evidence suggests it's tough to generate value from AI projects, but one thing we can be sure of is that successful initiatives require data -- and lots of it.
Whether it's running a generative AI rollout or exploring agentic AI, the language models that power emerging technology solutions require access to vast informational resources. As businesses scale up their AI efforts through 2026 and beyond, having access to the right data assets has never been important.
Also: You should still learn to code, says top Google AI exec - here's why
But how can you ensure your organization is collecting the right information for its AI initiatives? Five business leaders give us their tips.
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