How AI Is Reshaping GEOINT Career Pathways

Introduction

For decades, the GEOINT profession has relied on a pipeline: bright graduates trained in GIS, remote sensing, and spatial analysis entered entry-level roles where they refined their skills, learned the tradecraft, and progressed into experienced professionals. But artificial intelligence (AI) may be changing this traditional structure.

A recent article by Ellis and Bindley (2025) in The Wall Street Journal (WSJ) highlights how AI is rapidly undermining entry-level hiring. The WSJ piece details how AI is displacing many routine tasks that once served as training grounds for new employees. As companies turn to AI tools instead of entry-level hires, the long-standing bridge between education and employment is weakening. The article highlights that while some organizations are experimenting with mentoring and onboarding programs, many young professionals are being shut out altogether. The job market is in what the WSJ calls a “messy transition,” where higher expectations collide with shrinking opportunities.

Since GEOINT is a hybrid of automation and human effort, it may be among the hardest-hit fields.

Learning the Tradecraft

Years ago, an Esri regional manager told me, “Your students are well educated, but we can’t use them until they’ve learned how to function in the real world.” My reply was that “education only provides the foundation, but you teach the tradecraft of the workplace.”

This may need to change.

Entry-level professionals have historically taken on tedious but formative tasks like geocoding, data cleaning, and imagery review. These tasks, though unglamorous, are fundamental to learning the tradecraft. Increasingly, AI systems are taking them over—object recognition being just one example—threatening to remove the first rung of the GEOINT career ladder.

Like white-collar jobs in the business sector, GEOINT may well be facing a shift in how tradecraft is learned. Many of the routine duties that AI now performs—data annotation, building databases, and scanning mountains of imagery—once served as the training ground for new professionals. These tasks offered space to make mistakes, improve, and learn workflows in context. If AI takes over this space, where will new professionals build those skills?

Old Programs, New World

Universities continue to graduate students trained in cartography, statistics, and scripting. But the bar has moved. As Ellis and Bindley (2025) observe, “the system hasn’t caught up.” GEOINT employers now need professionals who can supervise AI/ML pipelines and work in near-real-time ISR environments. Graduates are left holding degrees that don’t match the job landscape. Further, GEOINT still requires human judgment—but that judgment only develops through experience. If the entry-level disappears, the professionals of tomorrow won’t have a path to get there.

Building a New Pathway

As Diamond (2006) noted, drawing on Schumpeter’s work, innovation often dismantles the very systems it is builds upon. AI’s impact on GEOINT is no exception. Yet AI still struggles with ambiguity, surprise, and complex context—the very foundation of sound GEOINT analytic insights. Tasks such as briefing commanders or supporting disaster response demand human judgment in ways AI cannot replicate. Unfortunately, the depth of thought required for these roles has traditionally been built on the experience gained in entry-level positions.

Some aspiring GEOINT professionals gain experience through military service, startups, or competitions. Forward-thinking businesses are adapting by emphasizing mentoring and structured onboarding to replace the loss of traditional entry-level functions. GEOINT needs similar approaches. I have long believed education could help fill this gap through a six-month GEOINT practicum—one designed to provide entry-level experience, initiate the security clearance process, and operate within a highly mentored joint program spanning government, business, and academia. A model already exists in NGA’s Moonshot Labs, an unclassified, collaborative innovation hub at the T-REX center in St. Louis that brings together government, industry, and academic partners to advance geospatial technology.

The Way Forward

AI is here to stay, and it is not the enemy. But it is reshaping the entry-level job, which is the foundation of workforce development. If the GEOINT profession fails to address the loss of entry-level roles, we risk creating a hollowed-out profession with the forfeiture of human discovery, critical thinking, communication, and judgment. These traits are learned, and that learning starts with doing. Instead of just asking, “What can AI do?” GEOINT leaders need to also ask, “What should humans excel at where AI is implemented, and where do we teach that now?”

What do you think? Share your thoughts and join in the discussion around data centricity and literacy in GEOINT at the 22nd annual DGI conference in London from Feb 23-25, 2026.

References and Acknowledgment:

Diamond, A. M. (2006). Schumpeter's Creative Destruction: A Review of the Evidence. The Journal of Private Enterprise, 22(1), 120–146.

Ellis, L., & Bindley, K. (2025, July 29). AI Is Wrecking an Already Fragile Job Market for College Graduates. The Wall Street Journal. https://www.wsj.com/lifestyle/careers/ai-entry-level-jobs-graduates-b224d624

Morison, E. E. (1966). Men, Machines, and Modern Times. M.I.T. Press.