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" ... It is imperative that leaders understand that data is the fuel that feeds AI models and if data is not robust then all their companies are doing is potentially deeply engraining the past into their operating methods and also with higher odds of data bias risks. The last thing we need in the AI reemergence industry is giving false hopes that AI models will see futures that they cannot see, and then over time, value realization in AI outcomes is questioned and organizations are not learning and AI investments become more constrained. Maintaining curiosity to learn and evolve is key given what China is doing in their longer term strategy to ensure AI is pervasive in all things. ... "