Completely rewrote the FAQ page to focus on practical AI adoption questions answered with evidence from the claims library. This optimizes for search discovery and provides immediate value to visitors.
New Questions (Evidence-Based):
1. Why do 95% of companies see zero ROI from AI?
- BCG data on 1,250 companies
- Top 5% strategy: Focus on revenue functions
2. What's the typical ROI from AI adoption?
- Department-specific data: 70% product teams report revenue increases
- Real examples: Nike $11.8B→$23B, Voice AI 30% cost cuts
3. How long does AI implementation take?
- Build vs buy timeframes (18-36 months vs quarters)
- Specific examples from claims
4. What's the biggest mistake companies make?
- Training vs workflow redesign
- Thomson Reuters 100% adoption case
- Costly mistakes: 99% cause losses, 42% abandoned
5. Which department should adopt AI first?
- Revenue-driving functions with specific ROI data
6. Should we build custom AI or use existing tools?
- Decision framework with timing/cost data
- Calabrio 80% satisfaction increase case
7. What makes a good AI prompt?
- 4-element framework with examples
- Links to structured prompt approach
8. How big is the AI market opportunity?
- Voice AI: $3.14B→$47.5B projection
- Enterprise adoption: 78% of firms
9. How do I measure AI success?
- Track dollars not hours
- Specific metrics from top 5%
SEO/GEO Benefits:
✓ Answers actual search queries ("AI ROI", "AI implementation time")
✓ Every answer links to specific claim pages for evidence
✓ Question-based structure helps LLMs extract and cite
✓ Uses data from 24 articles across 120 claims
✓ Demonstrates expertise through evidence, not opinions
Old FAQ content (technical library usage) can be moved to /how-i-built-this page.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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