This appendix is the book's account of where its numbers come from and what was done to them. Every chart in the book is drawn from a file in the repository's data/ directory, every file is traceable to a public address and a retrieval date, and every number in the prose can be found in one of those files at the precision the book prints it. The appendix explains how the sources are graded and marked, how the fourteen questions of the test were built, where a measured answer could be set beside a published survey and where it could not, under which licences the figures are reproduced, what was derived rather than read, how the figures are produced, and, dataset by dataset, who published what, when it was retrieved and what the publisher warns about. The last part is generated from the SOURCE.md file of every dataset, so that it cannot drift from the files the charts read.
Rosling could draw on demographic series that statistical offices and international agencies had kept for generations, and he could put his questions to representative samples in fourteen countries and report how people answered (8, Rosling et al., 2018) (16, Gapminder Foundation, 2017). The data on this landscape differ from his in three honest ways, and the chapters say so figure by figure rather than once here.
They are younger. Eurostat's survey module on artificial intelligence in enterprises has been run in 2021, 2023, 2024 and 2025, four points, and the list of technologies it asks about gained an eighth type in 2025, so the latest aggregate rests on a longer list than the earlier ones (9, Eurostat, 2026). Eurostat's question to individuals about generative AI tools was asked for the first time in 2025, so it has one point and no series (14, Eurostat, 2026). The cloud module runs every second year and changed its list of services and its classification in 2021 (10, Eurostat, 2026). The AI Incident Database revises the counts of earlier years as reports arrive, so that the total for one year differs between snapshots (35, Responsible AI Collaborative, 2026). The law that the landscape sits under was amended in 2026 before its main obligations had applied (40, European Union, 2026).
Primary topics explored
- How the book treats data
- The method of the test
- Matching perception to measurement
- Vendor surveys and self-selected samples
- Licences and what may be reproduced
- What was estimated
About Landscape
Landscape is a companion to The Transformed Architecture. It examines what happens when artificial intelligence takes the manager's chair: algorithmic management of direction, evaluation, consequence, development and care, the effects on people, the management of AI agents, Europe's legal answer, and how to design an accountable AI boss, for European enterprises and public authorities.
It builds on the conclusions of Architecture as Code, AI Governance, AI Platform and Security, AI Red Team, AI Threat and The Transformed Security Architect.
Executives, line managers, HR and people leaders, works councils and trade unions, public employers, architects and AI governance leads, data protection and legal officers, procurement and programme leaders, and risk, compliance and audit.
Gunnar Nordqvist
Conceived, directed and published the books of The Transformed Architecture.
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Appendix C: Appendix C: Data Sources and Methods in Landscape gives the detailed explanations, practical examples and implementation patterns behind this summary.
This whitepaper belongs to “Appendices” and is one of 26 drawn from the manuscript.