Research or develop geospatial technologies. May produce databases, perform applications programming, or coordinate projects. May specialize in areas such as agriculture, mining, health care, retail trade, urban planning, or military intelligence.
24 of 24 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Produce data layers, maps, tables, or reports, using spatial analysis procedures or Geographic Information Systems (GIS) technology, equipment, or systems.
AI: Fully automatable - AI and modern GIS tools can automatically generate data layers, maps, tables, and reports from spatial datasets and workflows, enabling routine spatial analysis and map production to be fully automated.
Perform integrated or computerized Geographic Information Systems (GIS) analyses to address scientific problems.
AI: Fully automatable - By 2025 AI systems can execute integrated/computerized GIS analyses (including spatial statistics, remote-sensing classification, and modeling) end-to-end given data and specifications with routine human oversight.
Create, analyze, report, convert, or transfer data, using specialized applications program software.
AI: Fully automatable - Routine creation, conversion, transfer, analysis, and reporting of data using specialized applications are highly automatable with robust scripts and AI-driven ETL and reporting pipelines.
Develop specialized computer software routines, internet-based Geographic Information Systems (GIS) databases, or business applications to customize geographic information.
AI: Fully automatable - By 2025 AI systems can reliably produce specialized GIS routines, web GIS databases and customized business applications end-to-end using code generation, testing and deployment tooling.
Assist users in formulating Geographic Information Systems (GIS) requirements or understanding the implications of alternatives.
AI: Fully automatable - Conversational AI and requirements-generation tools can effectively elicit GIS requirements, model alternatives and explain trade-offs, enabling comprehensive user assistance.
Create visual representations of geospatial data, using complex procedures such as analytical modeling, three-dimensional renderings, or plot creation.
AI: Fully automatable - Automated pipelines and AI visualization tools can produce complex geospatial analyses, 3D renderings and publication-quality plots from data with little human intervention.
Prepare training materials for, or make presentations to, Geographic Information Systems (GIS) users.
AI: Fully automatable - AI can author training materials, create slide decks and scripted presentations and even generate narrated walkthroughs, covering preparation and delivery for most training needs.
Provide technical support for computer-based Geographic Information Systems (GIS) mapping software.
AI: Fully automatable - AI-driven support agents, diagnostic tools and automation can resolve the majority of GIS software issues and guide users through fixes, enabling largely automated technical support.
Provide technical expertise in Geographic Information Systems (GIS) technology to clients or users.
AI: Partial - AI can provide technical GIS guidance, tutorials, and scripted support to clients, but nuanced expert consulting, stakeholder engagement, and context-specific recommendations generally require human specialists.
Perform computer programming, data analysis, or software development for Geographic Information Systems (GIS) applications, including the maintenance of existing systems or research and development for future enhancements.
AI: Partial - AI-assisted programming and data-analysis tools can perform much GIS development and maintenance, yet end-to-end software architecture decisions, complex integrations, and novel R&D still depend on human engineers.
Read current literature, talk with colleagues, continue education, or participate in professional organizations or conferences to keep abreast of developments in Geographic Information Systems (GIS) technology, equipment, or systems.
AI: Partial - AI can automatically read and summarize literature and surface relevant conferences or courses, but human networking, judgment about career priorities, and active participation remain necessary.
Lead, train, or supervise technicians or related staff in the conduct of Geographic Information Systems (GIS) analytical procedures.
AI: Partial - AI can generate training materials, monitor routine task performance, and suggest supervision actions, but leading and managing people requires human social judgment and authority.
Collect, compile, or integrate Geographic Information Systems (GIS) data, such as remote sensing or cartographic data for inclusion in map manuscripts.
AI: Partial - AI can ingest, preprocess, and integrate remote sensing and cartographic datasets automatically, but field data collection and some contextual quality-control decisions still need humans.
Conduct or coordinate research, data analysis, systems design, or support for software such as Geographic Information Systems (GIS) or Global Positioning Systems (GPS) mapping software.
AI: Partial - AI can perform large parts of data analysis and provide design and software support, but coordinating research programs and higher-level systems design require human leadership and domain coordination.
Create, edit, or analyze geospatial data, using Global Positioning Systems (GPS) or digitizing techniques.
AI: Partial - AI can edit, clean, and analyze GPS and digitized geospatial data and assist semi-automated digitizing, but physically collecting GPS points and certain digitizing judgement calls often need humans.
Meet with clients to discuss topics such as technical specifications, customized solutions, or operational problems.
AI: Partial - AI can prepare materials, draft proposals, and even participate in client meetings, but nuanced relationship building, negotiation, and responsibility for decisions generally require a human lead.
Document, design, code, or test Geographic Information Systems (GIS) models, internet mapping solutions, or other applications.
AI: Partial - AI tools by 2025 can generate documentation, code, and tests for GIS applications and prototypes, but end-to-end design, architecture choices, and final validation require human oversight.
Develop new applications for geospatial technology in areas such as farmland preservation, pollution measurement, or utilities operations management.
AI: Partial - AI can rapidly prototype and suggest novel geospatial applications and analyses, but fully developing, deploying, and validating new domain-specific applications with stakeholder alignment still needs humans.
Coordinate the development or administration of Geographic Information Systems (GIS) projects, including the development of technical priorities, client reporting and interface, or coordination and review of schedules and budgets.
AI: Partial - Project coordination, prioritization, client reporting and budget/schedule review require stakeholder negotiation, authority and contextual management that AI can assist with but not fully replace.
Design, program, or model Geographic Information Systems (GIS) applications or procedures.
AI: Partial - AI can generate GIS code, prototypes and modeling workflows and accelerate design, but full-system design requires domain judgment and integration oversight from humans.
Make recommendations regarding upgrades, considering implications of new or revised Geographic Information Systems (GIS) software, equipment, or applications.
AI: Partial - AI can analyze releases, compatibility and performance implications to make upgrade recommendations, but strategic and organizational implications typically need human decision-making.
Coordinate or direct research or publication activities of technicians or related staff.
AI: Partial - AI can support literature searches, drafting and coordination tasks, but directing research and publication activities requires leadership, mentorship and ethical oversight that remain human responsibilities.
Conduct feasibility studies or identify system, time, equipment, or cost requirements for projects.
AI: Partial - AI can model system, time, equipment and cost scenarios and produce feasibility analyses, but final feasibility judgments need stakeholder input, local validation and managerial decision-making.
Apply three-dimensional (3D) or four-dimensional (4D) technologies to geospatial data to allow for new or different analyses or applications.
AI: Partial - AI systems can generate and implement 3D/4D models and propose analyses, but sensor integration, domain-specific decisions, and validation for novel applications still require human expertise.