content will be AI-generated by 2026 . In addition to distorting quality , some researchers believe this AI feeding AI phenomenon could lead to Model collapse , and the gradual degradation in the output .
Safeguarding of models , is therefore , key . Rajagopal believes that the cloud could hold the key in this administration . “ For AI to be successful , it needs access to an intelligent data management cloud capable of quickly identifying all the necessary features for the model .”
Although , Rajagopal notes , “ Figuring out how to provision the huge amount of compute power needed is a challenge .” In lieu of such a cloud , responsible data management practices implemented at the human or organisational level will become increasingly important as AI advances .
“ The future of data processing in building AI models primarily concerns ensuring that a business using AI has a robust understanding of its data estate and an adequate data governance system in place ,” explains Andy Crisp , SVP Global Data Owner , Dun & Bradstreet . “ AI is only as smart as the data that fuels it , and so introducing policies and adhering to data quality standards is imperative to preventing the influx of substandard data that could compromise AI outputs . A solid data foundation not only enhances the accuracy of predictions but also fortifies the insights derived from AI algorithms , creating a robust framework for smarter decision-making .” aimagazine . com 137