Practical AI Travel Planning Workflow: What Works and What Doesn't

AI Travel Planning: One Year, Six Countries

A developer has been using AI tools for travel planning for about a year, covering six countries ranging from weekend city breaks to two-week trips. The experience reveals specific strengths and weaknesses of current AI systems for practical travel planning.

What AI Does Well

• Rapid itinerary creation: Building day-by-day itineraries in minutes instead of hours. Example: Giving Claude "4 days in Dubai, 2 colleagues, architecture and food, mid-range budget" produced a solid plan in 2 minutes.
• Discovering hidden gems: Surfacing experiences not found on page 1 of Google. A suggested dhow dinner cruise became a trip highlight.
• Logistics optimization: Grouping nearby attractions, estimating transit times, and suggesting optimal visit order.
• Budget accuracy: Budget breakdowns were within 10-15% of actual spending.

Where AI Still Fails

• Opening hour inaccuracy: Opening hours are wrong approximately 20% of the time.
• Over-scheduling: AI consistently suggests too much content. The developer cuts about 30% of what any AI suggests.
• No real-time awareness: Without browsing capabilities (like Perplexity), AI doesn't know about closed restaurants, renovations, or seasonal changes.
• Missing local nuance: AI won't identify tourist traps or provide genuine local insights.

Current Workflow

The developer has refined their approach to a five-step process:

1. Use ChatGPT or Claude for initial itinerary framework
2. Use Perplexity for anything requiring current information (prices, hours, availability)
3. Verify everything on Google Maps
4. Check Reddit/forums for local perspective
5. Return to AI to adjust based on all verification

The developer has written a full breakdown of tools, workflows, and mistakes to avoid at their personal site.