The World Geospatial Industry Council (WGIC), a Geo Week partner, has released Data to Decisions, a report on rebuilding trust in decision-grade geospatial data. Its central argument is that the industry is shifting from measurement-based trust, where maps were believed because people knew how they were made, to model-based trust, where data is inferred, synthesized and generated at scale by AI systems whose workings are hard to inspect. The report points to silent errors, untraceable lineage and blurred accountability as the new risks that come with that shift.
The report defines decision-grade data as geospatial data that is demonstrably fit for a specified decision. That means traceable origins, documented transformations, appropriate accuracy and currency, communicated uncertainty, lawful usage rights and identifiable accountability. Fitness is always relative to the decision, use case, jurisdiction, timeframe and consequence level.
Four foundations and three priority actions
The report argues that trust has to be rebuilt on provenance, governance, metadata and accountability. It pairs those foundations with three priority actions for the industry: embed provenance and machine-readable metadata now, convene an industry-wide governance umbrella, and define contractual liability across the data chain.
The report is careful about what trust controls can and cannot do. Authenticity, integrity and provenance each answer a different question, and none of them proves that the original measurement was accurate or that the data suits the decision at hand. A cryptographic hash, for example, shows that data has not changed since it was hashed, not that it was right to begin with.
It also follows a single flood map from measurement through to use, showing how each stage adds capability and a new way for trust to break. Temporary floodwater misclassified as permanent water and navigation data that sends vehicles onto roads that no longer exist are among the scenarios it uses to make the risks concrete.
On the regulatory side, the report covers Article 50 of the EU AI Act, whose transparency obligations have applied since August. It notes a limited grace period (until December 2026) for marking and detection obligations on certain systems already on the market, which is directly relevant to GeoAI providers assessing their timelines.
The report also looks ahead to geospatial foundation models trained on imagery, lidar, SAR and other sources. It makes the case that governance has to be built into the model architecture from the start, with audit running through every layer rather than applied to the output alone.
Read the full report
These highlights only scratch the surface. The full report includes practical recommendations by role, a guide to which standards do which job, a three-horizon roadmap and a short maturity checklist for assessing where your own organization stands. Download Data to Decisions from the WGIC website.
