Every year the European Commission's Digital Decade dashboard does something few forecasters do in public. It takes the share of EU enterprises using at least one AI technology, lays a line through the observed points, carries the line to 2030 and publishes where it lands; the next year it does it again, with one more point, and leaves the old line beside the new one. Computed in 2023, the baseline reached 20.29 per cent in 2030. Computed in 2024, 16.76. In 2025, 35.92. In 2026, 54.28 (15, European Commission, 2026). Four projections by the same office, each superseded within a year, each labelled a projection. A reader who wants to know how wrong the 2023 line was about 2025 can look it up: it had the share at 12.35 per cent, and the survey found 19.95 (15, European Commission, 2026).
I open the last chapter with that dashboard because it is the model for what the chapter does. AI Governance, Chapter 22, sets the practice: state each trend, classify its evidence, assign it a horizon and set a review date, so that an outlook can be wrong in a reviewable way (2, Nordqvist, 2026). The earlier chapters describe the measured picture and, where they look ahead, say whose projection it is. My own guesses go in one section of this chapter, marked as mine and nowhere else, written so that the reader can see what would show them wrong. Before it, three sections sort the next years under the three labels the book has used throughout: what is observable now, what is expected within five years and on what evidence, and what is speculation. After it, the test and the stance return, and the two organisations are drawn one last time.
Observable, in the sense AI Governance, Chapter 22, gives the word, means already visible in adopted legislation, published guidance, cited standards or production systems, and here in a published dataset as well (2, Nordqvist, 2026). Everything in this section is observable, and none of it is a forecast.
Primary topics explored
- Observable
- Expected
- Speculation
- The author's projections
- The test, again
- A reasonable hope
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.
Continue with the full chapter
Chapter 20: The Next Years, and a Conclusion in Landscape gives the detailed explanations, practical examples and implementation patterns behind this summary.
This whitepaper belongs to “Seeing Clearly” and is one of 26 drawn from the manuscript.