2.3. Evaluating Costs and Benefits

AI projects fail more often from poor business justification than from technical shortcomings. The exam tests whether you can build a credible ROI case, make defensible sourcing decisions, and optimize costs through intelligent model selection. These aren't soft skills — they're architectural decisions with direct budget implications.

The financial decisions here are architectural decisions in disguise. Choosing between building custom, buying prebuilt, or extending existing solutions determines your entire technology stack, team structure, and maintenance burden for years.

Think of the build-buy-extend decision as a spectrum: at one end is full control with maximum investment (custom AI models), at the other is fast deployment with limited customization (prebuilt agents). Model routing sits in between — intelligently selecting the right model per request to optimize the cost-capability trade-off.

⚠️ Common Misconception: ROI for AI solutions is measured only in cost savings. The exam tests a broader view: revenue growth, customer satisfaction, employee productivity, time-to-market, and strategic competitive advantage all factor in.