Part 6/12:
Monitoring Data Drift: Data evolves; hence, models require periodic retraining and updates to sustain accuracy over time.
Cost-Benefit Analysis: Understand computational costs versus expected gains, balancing innovation with resource constraints.
This disciplined methodology enables organizations to prioritize use cases with tangible value, minimizing wasted efforts and maximizing AI’s strategic benefits.
Balancing Innovation with Risk Management
While generative AI offers transformative opportunities, it also introduces significant risks related to data privacy, security, and ethical concerns. Chandra advises that organizations conduct thorough risk assessments before scaling AI initiatives. Key steps include: