Testing AI
in Smart Cities and

CitCom.ai TEF Market Report: Mapping the AI trends in EU


The four TEFs aim to enhance AI innovation by providing a testing environment that closely resembles real-world settings. The primary objective is to accelerate the digital transformation of urban areas across the EU by allowing rigorous testing and improvement of new AI systems. 

The insights in this first market report are drawn from scholarly and grey literature, as well as reports from past EU-funded projects related to AI and smart cities and communities.

First, the analysis examines relevant legislative initiatives, funding programs, and past projects in the EU. These initiatives are categorized into six areas: Identity and access, privacy and security, platforms, interoperability, data, and AI. Additionally, the Digital Europe Programme (DEP), Horizon Europe, and other financing mechanisms supporting digital transformation, AI, and smart cities are highlighted.

Second, the focus shifts to European cities and communities as stakeholders in the AI Testing and Experimentation Facilities (TEFs). These cities exhibit varying digital maturity levels. Larger metropolitan regions often demonstrate more strategic planning and integrated data-driven services. Technical departments tend to adopt new technologies more effectively. Challenges related to skills, resources, data silos, and leadership are addressed through recommendations such as skills transfer, nurturing ecosystems, and intelligent procurement.

Third, the report delves into the EU AI industry. Key points include:

  • In 2020, the EU had approximately 5,776 players in the AI industry.
  • Globally, the AI industry is projected to grow from $450 billion in 2022 to over $2.6 trillion by 2032.
  • European AI investment is expected to increase by 29.6% annually from 2021 to 2026, reaching over $70 billion in 2026.
  • Germany and France lead in the number of AI businesses, followed by Spain, Italy, the Netherlands, and Sweden.

Areas of focus include natural language processing, computer vision, machine learning (ML), robotics, automation, connected cars, and AI services.

Challenges faced by AI innovators include limited data access, navigating complex legal environments, inadequate computing resources, cross-domain integration issues, scaling solutions, and privacy/security concerns.

Last, the report focuses on three CitCom.ai application domains:

Nordic Supernode ‘POWER’: Concentrates on energy, environmental solutions, and cybersecurity within the energy sector. Challenges include data access limitations, data quality issues, interoperability, and data protection concerns. AI systems can aid in managing traffic and implementing predictive maintenance for large-scale heat pumps.

Central Supernode ‘MOVE’: Emphasizes urban transportation, including smart urban mobility, electromobility, and autonomous driving. Challenges involve high data volumes, infrastructure gaps, sensor accuracy, regulatory uncertainties, and business models. Opportunities lie in improved traffic flow and reduced emissions.

Southern Supernode ‘CONNECT’: Addresses (noise) pollution management, urban development, water management, integrated facility management, drone deliveries, and tourism. Challenges span data quality, platform interoperability, skills gaps, and regulatory complexity. AI applications can optimize resource usage and enhance sustainability, particularly in climate-related areas.

In summary, this market analysis identifies key actors, trends, and challenges to guide the development and impact of AI Testing and Experimentation Facilities (TEFs). Regular updates will be crucial to capture emerging developments in this dynamic field.

Explore the report (link below) - and feel free to share it with your network!

Read also the three news articles (links below), regarding the report: