Part 10/12:
Vishal advises organizations to embrace failures as learning opportunities. Even imperfect models (70-80% accuracy) can provide valuable insights and drive iterative improvements. Crucially, early experimentation and rapid learning are necessary to capitalize on potential benefits.
What Can Go Wrong? Challenges and Pitfalls
Despite the optimism, Vishal cautions that multiple risks can hinder the successful deployment of AI:
- Model Failures and Performance Gaps: New AI models may not deliver expected results initially, which can tempt organizations to delay deployment. However, Vishal stresses that waiting for perfection often hampers innovation.