AI project success
Data Readiness for AI: What Enterprises Need to Get Right
AI success relies on quality data, yet poor data costs businesses trillions. A 2018 AI project failed due to bad data, while a 2024 one thrived by prioritizing data readiness. Key steps: align AI with goals, engage stakeholders, assess data, run pilots, and manage change.