Episode

AI in QGIS

Podcast
The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography
Published
Mar 5, 2026
Duration seconds
2960
Processing state
not_requested
Canonical source
https://mapscaping.podbean.com/e/ai-in-qgis/
Audio
https://mcdn.podbean.com/mf/web/2a6hqmnw4nvqmxh2/MapScaping_-_QGIS_and_AI9c14f.mp3
JSON
/v1/public/podcasts/the-mapscaping-podcast-gis-geospatial-remote-sensing-earth-observation-and-digital-geography-743634/episodes/ai-in-qgis
Markdown
/podcast/the-mapscaping-podcast-gis-geospatial-remote-sensing-earth-observation-and-digital-geography-743634/ai-in-qgis.md

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Summary

I've been playing around with a lot of large language models lately, and it is absolutely fascinating to watch them work. But what happens when you bring that directly into QGIS? Right now, AI in the geospatial industry is a lot like a fast, enthusiastic new intern, incredibly helpful, and sometimes completely wrong, but improving at a rate that no human can compete with. As we hand more of our geoprocessing tasks over to these algorithms, and computing becomes more pervasive, are our own GIS skills becoming obsolete? Or are we just unlocking radically different opportunities to rethink our careers?