"Garbage in, garbage out." Biased or inaccurate training data leads to faulty predictions and discriminatory outputs.
AI is only as effective as the data it consumes. Most organizations struggle with fragmented, incomplete, or poor-quality datasets.
Many companies use legacy technology that was never designed to integrate with modern AI tools, creating "data silos" where information is unreachable.