I recently used AI to help plan a fairly detailed road trip from Minnesota to Kentucky and Indiana, and I thought it might be useful to share the process for anyone considering using AI tools for travel planning, genealogy travel, or route optimization.
The trip itself involved:
- Driving from St. Cloud, Minnesota to the Cincinnati area
- Avoiding the Chicago metro area
- Avoiding toll roads
- Staying primarily on major highways
- Scheduling genealogy research time in Corydon, Indiana
- Coordinating hotel stays around fixed dates
- Preferring Hilton properties when possible
- Balancing driving fatigue against available travel days
What impressed me most was not just that AI could generate a route, but that it could iteratively refine the itinerary based on changing constraints.
Starting With the Basic Trip
The initial request was straightforward:
- Travel dates
- Start and destination cities
- Lodging location in Erlanger, Kentucky
- Desire to avoid Chicago traffic
- One overnight stop about halfway each direction
The AI generated a preliminary route using:
- I-94
- I-39
- I-74
- Indianapolis bypass routes
- Southern Indiana connectors into Corydon
This immediately solved one of the biggest headaches for Upper Midwest travelers: avoiding Chicagoland congestion while still staying on efficient interstate highways.
Refining the Route
The next step was adding additional constraints.
I asked the AI to:
- Avoid toll roads
- Keep the route on major highways when possible
- Maintain reasonable daily drive times
This caused the route to change in subtle but important ways.
For example:
- Louisville toll bridges were avoided
- The Indiana Toll Road was excluded
- Routing shifted toward I-39 and I-74 corridors
- Alternate crossings near Louisville were used instead
The AI also explained why certain roads were chosen, which made it easier to evaluate whether the tradeoffs were worthwhile.
Planning Around Genealogy Research
One of the more interesting uses was incorporating genealogy research into the itinerary.
The trip included several days in Corydon, Indiana for:
- deed research
- probate records
- cemetery visits
- plat map review
- courthouse records
- local archives
Instead of simply scheduling hotel nights, the AI reorganized the trip around research efficiency.
It suggested:
- using Corydon as a dedicated research base
- allowing multiple full archive days
- planning lighter travel days before and after research sessions
- selecting hotels with easy parking and quick archive access
It also identified local genealogy resources and helped structure the research days logically.
Hotel Selection Preferences
Another useful feature was refining hotel preferences.
I requested:
- Hilton-family hotels when practical
- convenient interstate access
- comfortable overnight stops for long driving days
The AI then revised the itinerary to:
- prioritize Hampton Inn and Home2 Suites properties
- identify practical alternatives where Hilton options were limited
- balance location convenience against chain preference
This saved a significant amount of manual searching.
Compressing the Schedule
The most impressive part was when the travel dates changed.
The departure date moved later, but several fixed requirements remained:
- Corydon genealogy time could not be shortened
- Erlanger hotel nights were fixed
- Return timing had to stay manageable
Instead of rebuilding everything manually, the AI recalculated:
- which overnight stops could be removed
- where longer drive days made the most sense
- how to preserve the genealogy research schedule
- how to keep the route toll-free and Chicago-free
The final version ended up being a very practical compromise between efficiency and comfort.
What AI Did Well
A few things stood out during the process.
1. Constraint Handling
AI was very good at balancing multiple requirements simultaneously.
For example:
- avoid tolls
- avoid Chicago
- preserve genealogy time
- use major highways
- include preferred hotel brands
- maintain reasonable drive days
Normally this would require multiple mapping apps, hotel searches, and manual revisions.
2. Iterative Planning
Travel plans change.
AI handled itinerary revisions quickly without losing track of previous constraints.
That made it especially useful for refining the trip over several rounds.
3. Contextual Suggestions
The genealogy-related recommendations were surprisingly useful.
Rather than treating the trip as pure navigation, the AI recognized that archive research days require:
- less driving fatigue
- easier parking
- flexible schedules
- nearby lodging
- organized research pacing
That context-awareness made the itinerary more realistic.
Limitations
AI planning is not perfect.
A few things still require human verification:
- hotel pricing
- room availability
- archive operating hours
- construction zones
- temporary road closures
- weather conditions
I would still recommend double-checking:
- genealogy library schedules
- courthouse access policies
- bridge or interstate construction
- hotel cancellation terms
AI works best as a planning assistant, not a final authority.
Overall Thoughts
Using AI for trip planning felt less like using a GPS and more like working with a travel coordinator.
The biggest value was not generating a single route.
The value came from:
- rapidly revising plans
- balancing multiple constraints
- preserving trip goals
- identifying practical tradeoffs
- organizing the itinerary logically
For genealogy travel especially, where schedules are often tied to archive hours, courthouse access, and research priorities, AI turned out to be much more useful than I expected.
If anyone else here has used AI for:
- road trip planning
- genealogy travel
- RV routing
- hotel optimization
- route refinement
- archive scheduling
…I’d be interested in hearing how well it worked for you.