Part 8/11:
A vital part of the discussion focused on the persistent data quality problem. Experts concurred that waiting for perfect data is futile; instead, organizations should build frameworks for observability and incremental cleaning, aligning AI projects with strategic business KPIs. Recognizing that many decision-makers lack technical AI expertise, the panel highlighted the importance of cultivating internal "AI champions" who can bridge strategy and execution, sharing success stories that demonstrate AI’s tangible value.