The AI technology stack of European large organizations

Free Content Report European Digital Tech Watch Technologies April 2026 27 pages pdf

What you will learn

The report, produced by European Digital Tech Watch – a think tank of the Polytechnic University of Milan, European Digital Tech Watch, focuses on analyzing the perspective of European end-user organizations by examining the current configuration of their AI technology stack, assessing how it is built today across applications, data, infrastructure, and governance. The objective
is to understand their level of maturity, structural gaps, and readiness to scale AI in a competitive and sustainable manner. In addition, the report provides an informed commentary on how the initiatives undertaken or planned within the AI Continent framework can support the further development of this technology stack. In doing so, it also highlights what additional actions may be required on the policy side to better align European initiatives with the concrete needs of end-user organizations, particularly in terms of competitiveness, technological sovereignty, and long-term strategic autonomy.

Table of Contents

1
Introduction
2
The AI technology stack of the European end-user organization
3
The AI technology stack framework
4
The AI Continent initiative and its role for the development of the European end-user organization
5
Conclusion and future research directions
6
Methodological Note
7
Research & Working Group
8
European Digital Tech Watch
9
Digital Innovation Observatories
10
POLIMI School of Management of Politecnico di Milano

Index of Graphs

1
The AI technology stack of the end-user organization
2
The percentage of business-critical data managed in the cloud
3
Data governance and data valorization initiatives in large European organizations
4
AI Adoption in large European organizations

You will know how to answer these key questions

How is the AI technology stack of European end-user organizations currently structured across applications, data, infrastructure, and governance?
What are the main structural gaps that hinder the development and scalability of AI?
How can the initiatives within the AI Continent framework support the evolution of the AI technology stack?
What additional policy actions are needed to better align European initiatives with the concrete needs of end-user organizations, particularly in terms of competitiveness, technological sovereignty, and long-term strategic autonomy?

The methodology used in this Report

The study analyzes where European end-user organizations stand in terms of AI adoption, identifying the key assets needed to leverage digital innovation. The research focuses on companies adopting AI solutions, assessing their level of maturity across four dimensions: applications, data, infrastructure, and governance. The empirical analysis is based on a 2024 quantitative CAWI survey administered to 1,021 large enterprises in eight European countries, involving strategic decision-makers and covering various economic sectors. The data collected on technology adoption, organizational capabilities, and use cases were supplemented by an expert focus group to validate and refine the analytical framework. The results were interpreted through a framework based on the five pillars of the EU’s AI Continent Plan, with the aim of supporting the development of recommendations for European digital policies.

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