• The industry needs to deliver new services quickly and efficiently.
• A shared understanding of intelligent networking needed to optimize interoperability.
• Some AI/ML is in place, but more research and development needed to establish best practices.
• The Open Source community can play a key role in furthering the development of frameworks and best practices.
• Start simple – Learn to trust your data and results
• Address the low hanging fruit first -- Anomalies, Forecasts, Statistical Models
  • Creating the data lakes is difficult
  • Within a company across business units
• Security and privacy concerns hamper data gathering efforts
• Need to create cross industry anonymized data. Creating a shared data model to test the algorithms

Be prepared for bias and unintended or unexpected results if the AI/ML system is too much of a black box.