Part 12/14:
Cooper also highlights that responsible deployment involves balancing innovation with safeguards—avoiding unintended consequences like data privacy breaches or malicious attacks.
The Maturing Lifecycle of AI in Business
He observes that AI's lifecycle—research, development, deployment, and continuous retraining—is still evolving. Different applications require varied update schedules, from daily retraining in markets like finance to quarterly updates in healthcare for low-frequency events.
Understanding the lifecycle, data dependencies, and retraining needs is fundamental to successful AI integration. Cooper underscores that human oversight continues to be essential, even as models become more sophisticated through unsupervised learning and automation.