Building AI features requires looking at all costs and benefits, not just the initial price tag. Start by calculating development costs including data collection, labeling, model training, and hiring AI experts. Add ongoing costs like infrastructure, monitoring, retraining, and fixing errors. Don't forget opportunity costs: what else could you build with the same resources?

Quantify benefits:

• Time saved for users
• Better accuracy than manual work
• New features previously impossible
• Improved user satisfaction scores
• Ability to serve millions without hiring more people
• Competitive advantages in your market
• Less mental effort and frustration for users

Weigh risks:

• Potential AI errors and their impact
• Users not trusting the system
• Ethical concerns and bias issues
• Meeting regulatory requirements

Calculate when benefits will cover your investment. Remember hidden costs like explaining AI to users, handling edge cases, and keeping performance high. Compare the total AI investment against simpler alternatives. Sometimes basic solutions give better returns even if they're less impressive technically.