Europe’s growing emphasis on achieving independence in artificial intelligence (AI) is creating a fertile landscape for investors like Brookfield. This focus on AI sovereignty is not just about reducing reliance on external technologies, particularly from the US and China, but also about fostering a robust, self-sustaining AI ecosystem that can compete globally. This strategic shift is opening new doors for Brookfield, positioning it as a key player in Europe’s AI infrastructure development. Below, we expand on how Europe’s pursuit of AI independence is creating opportunities for Brookfield, detailing the economic, policy, and strategic factors at play.
Background on Europe’s AI Independence Efforts
Europe’s focus on AI independence has gained momentum in recent years, driven by the recognition that AI is a critical infrastructure for the global economy, comparable to electricity or the internet. The European Union (EU) has launched several initiatives to strengthen its AI capabilities, aiming to reduce dependence on foreign technologies and foster innovation within its borders. A key development is the InvestAI initiative, announced on February 11, 2025, at the Artificial Intelligence (AI) Action Summit in Paris, which seeks to mobilize €200 billion for AI investment . This includes a new European fund of €20 billion for AI gigafactories, large-scale facilities designed to develop complex AI models and produce AI chips, essential for Europe’s AI ambitions.
Additionally, the EU’s AI Act, adopted in 2024, sets standards for trustworthy AI, creating a regulatory framework that balances innovation with ethical considerations. The AI Continent Action Plan, launched in April 2025, further aims to make Europe a global leader in AI by focusing on infrastructure, talent, and collaboration. National efforts, such as the UK’s AI Opportunities Action Plan, introduce measures like „AI growth zones“ to fast-track data center construction and facilitate access to energy grids . These initiatives collectively signal Europe’s commitment to building a sovereign AI ecosystem, creating a conducive environment for private investment.
Opportunities for Brookfield in Europe’s AI Infrastructure
1. Increased Demand for AI Infrastructure
As Europe pushes for AI sovereignty, there is a growing need for data centers, computing power, and energy resources to support AI applications. The InvestAI initiative’s €20 billion allocation for AI gigafactories highlights this demand, focusing on infrastructure to develop sophisticated AI models and produce over 100,000 AI chips . Brookfield, with its recent investments in Sweden and France, is well-positioned to meet this demand. As Europe’s AI ecosystem grows, the market for AI-related infrastructure will expand, creating opportunities for Brookfield to undertake new projects and expand existing ones.
2. Government Support and Public-Private Partnerships
Europe’s AI independence efforts are backed by significant government support, which creates an attractive environment for private investors. The InvestAI initiative is structured as a public-private partnership, with the EU contributing €50 billion and expecting the remaining €150 billion from private investors. This model, likened to a „CERN for AI,“ invites companies like Brookfield to collaborate with governments and other entities to build critical AI infrastructure . National governments, such as France and Sweden, have welcomed Brookfield’s investments, with leaders like French President Emmanuel Macron and Swedish Prime Minister Ulf Kristersson emphasizing their strategic importance. This political backing reduces investment risks and provides access to funding, making Europe an appealing destination for Brookfield.
3. Favorable Policy and Regulatory Environment
Europe’s regulatory framework, including the AI Act and national plans like the UK’s AI Opportunities Action Plan, creates a stable and predictable environment for investment. The AI Act sets standards for trustworthy AI, ensuring ethical development, which aligns with global trends and could attract investors who value sustainability and transparency. Policies like „AI growth zones“ in the UK fast-track data center construction, simplifying the investment process and reducing barriers for Brookfield. This regulatory support enhances the attractiveness of Europe’s AI market, potentially leading to more partnerships and projects for the company.
4. Strategic Positioning and Market Growth
By emphasizing its strengths—such as a skilled workforce, strong industrial base, and commitment to ethical AI—Europe is carving out a unique niche in the global AI landscape. While the US and China currently lead in private AI investment, Europe is rapidly scaling up its startups and infrastructure, aiming to bridge the gap . Brookfield, as an early mover, can establish itself as a leader in Europe’s AI infrastructure landscape, benefiting from cross-border collaboration and unifying AI talent, research, and resources. The economic growth driven by AI infrastructure development, including job creation (e.g., over 1,000 permanent jobs in Sweden), will stimulate local economies and attract further investment, creating a ripple effect that benefits Brookfield.
Potential Challenges and Considerations
While the opportunities are promising, there are challenges that Brookfield must navigate. Europe’s AI landscape is fragmented, with varying levels of investment and policy support across member states. Competition with the US and China, which currently lead in private AI investment, could pose risks. Additionally, the execution of large-scale projects like AI gigafactories requires significant coordination and may face delays due to regulatory or logistical hurdles. However, Brookfield’s early mover advantage, global expertise, and existing European presence position it well to address these challenges and capitalize on the opportunities.
Brookfield’s Recent Investments and Alignment with Europe’s Goals
Brookfield has made significant strides in 2025 to bolster Europe’s artificial intelligence (AI) infrastructure through two major investments: one in Sweden and another in France. These initiatives, announced earlier this year, underscore Brookfield’s commitment to the AI value chain and align with the strategic goals of both nations to become leaders in AI innovation. This report provides a detailed examination of these investments, their impacts, and their broader implications for Europe’s AI landscape.
Investment Details
Sweden: A New AI Hub in Strängnäs
On June 4, 2025, Brookfield announced an investment of up to SEK 95 billion ($10 billion) to develop AI infrastructure in Sweden, as detailed in their press release . This investment centers on building a new large AI center in Strängnäs, which is set to be one of the first of its kind in Sweden and among the first in Europe. The project includes a land allocation agreement for approximately 350,000 square meters, enabling the data center site to more than double its capacity from 300 MW to 750 MW. This expansion is crucial for supporting the growing demand for AI computing resources, particularly in data transfer, chip storage, and energy generation.
France: A €20 Billion Leap into AI Leadership
Earlier, on February 10, 2025, Brookfield unveiled a €20 billion infrastructure investment program in France to support AI deployment, as outlined in their press release . This program includes up to €15 billion for data centers, led by Data4, Brookfield’s portfolio company headquartered in Paris, and €5 billion for associated AI infrastructure such as data transfer networks, chip storage, and energy generation, with a target completion by 2030. Data4 currently plans to build over 500 MW of data center capacity across several regions in France, with ambitions to triple this by 2030, making France its largest market in Europe.
Economic and Job Creation Impacts
The Strängnäs project is expected to have a significant economic impact, particularly in job creation. Official statements indicate it will create over 1,000 new permanent jobs and an additional 2,000 jobs during the 10-15 year construction period. This job creation is particularly notable given Strängnäs’s proximity to Stockholm and other university towns like Eskilstuna, Västerås, Linköping, and Uppsala, which could further enhance regional development. The economic benefits extend beyond job creation, likely stimulating local businesses, improving infrastructure, and attracting further investment in the AI sector.
While specific job creation numbers for the France investment are not publicly disclosed, the scale of the €20 billion program suggests it will generate numerous jobs in construction, operation, and maintenance. Brookfield already employs over 7,000 people in France through various operations, including residential decarbonization, student housing, hospitality, logistics, and digital and renewable energy infrastructure. The AI infrastructure investment is likely to expand this workforce, contributing to economic growth in the regions where data centers are built.
Strategic Alignment with National AI Strategies
Sweden has a well-defined national AI strategy, initially released in May 2018 and further developed through initiatives like the AI Commission and AI Sweden. The strategy emphasizes substantial investment to generate and spread benefits across sectors and society, aiming to ensure significant value, contribute to a prosperous democratic society, strengthen national security, and enable global impact while navigating risks. Brookfield’s investment aligns with these objectives by providing critical infrastructure to support AI adoption and development. The AI center in Strängnäs is intended to bolster Sweden’s sovereign compute capabilities for both public services and private enterprises in Europe, supporting its goal to rank among the top 10 in the Global AI Index by 2025.
France’s national AI strategy, launched in 2018 as “AI for Humanity” and continued under the “France 2030” plan adopted in November 2021, aims to enhance AI skills, establish France as a leader in embedded and trustworthy AI, and accelerate AI integration into the economy. Key initiatives include IA-Cluster, transforming French training and research centers into global AI hubs, and IA-Booster, supporting SMEs in digital transformation. Brookfield’s €20 billion investment directly supports these goals by providing the necessary data centers and infrastructure, aligning with France’s ambition to double the number of AI specialists by 2030 and elevate its institutions in global AI rankings.
Energy Needs for AI Infrastructure
The rapid expansion of AI infrastructure, particularly data centers, has significantly increased energy demand, especially for electricity. AI applications, such as training large language models, processing vast datasets, and running generative AI systems, require substantial computational power. According to the International Energy Agency (IEA), global electricity demand from data centers is projected to more than double by 2030, reaching around 945 terawatt-hours (TWh), slightly more than the entire electricity consumption of Japan today . This surge is primarily driven by AI, with electricity demand from AI-optimized data centers expected to more than quadruple by 2030. In the United States, power consumption by data centers is on course to account for almost half of the growth in electricity demand between now and 2030, with AI use potentially consuming more electricity in 2030 for data processing than for manufacturing energy-intensive goods like aluminum, steel, cement, and chemicals combined .
This energy demand extends beyond electricity to include water for cooling, with generative AI systems using millions of gallons of fresh water daily to manage the heat generated by high-performance computing equipment. This is particularly evident in data centers, where cooling systems are essential to prevent overheating of servers and GPUs . The need for energy infrastructure, therefore, encompasses not only power generation but also transmission lines, distribution systems, and advanced cooling technologies to support AI’s operational requirements.
Challenges in Meeting Energy Demands for AI Infrastructure
The surge in energy requirements for AI infrastructure presents several significant challenges:
- Scale of Energy Demand: The energy needs of AI infrastructure are staggering. For instance, OpenAI’s Stargate initiative, announced in collaboration with President Donald Trump, aims to spend $500 billion to build up to 10 data centers, each requiring five gigawatts of power—more than the total electricity demand of the state of New Hampshire . This scale necessitates a massive expansion of energy capacity, which current infrastructure may not support without significant upgrades.
- Time Constraints in Energy Infrastructure Development: Building new energy infrastructure, particularly large-scale projects like nuclear power plants, is a slow process. Companies like Meta and Microsoft are working to fire up new nuclear power plants to meet AI’s energy needs, but such projects can take years to plan, permit, and construct . The IEA notes that energy supply can be a bottleneck, especially for large-scale nuclear plants, which could delay the deployment of AI infrastructure .
- Environmental and Sustainability Concerns: The environmental footprint of AI infrastructure is significant, particularly in terms of water usage and carbon emissions. Data centers consume millions of gallons of fresh water for cooling, raising concerns about water scarcity, especially in regions with limited resources . Additionally, reliance on non-renewable energy sources for AI could exacerbate carbon emissions, conflicting with global climate goals and net-zero targets set by many companies .
- Grid Modernization and Integration: Existing energy grids in many regions are not equipped to handle the increased load from AI infrastructure. Upgrading grids to support higher demand, integrate renewable energy sources, and ensure reliability is a complex and costly endeavor. The MIT Technology Review suggests a “Grid New Deal” is needed, leveraging public and private capital to rebuild the electricity system with enough capacity and intelligence for decarbonization, including fast-tracking connections for data centers bringing clean electricity .
Effect on Investment Pace
The need for more energy infrastructure directly impacts the pace of AI infrastructure investment:
- Potential Delays: If energy infrastructure cannot keep pace with AI demand, it could slow down the deployment of new AI facilities. Data center developers may face delays in connecting to the grid or securing reliable power sources, which could hinder the expansion of AI capabilities. For example, the IEA highlights that energy supply can be a bottleneck, especially for large-scale projects, potentially delaying investment timelines .
- Increased Costs: The need for new energy infrastructure could raise the overall cost of AI projects. Developers may need to invest in on-site power generation, such as renewable energy or backup systems, to ensure uninterrupted operations. This could increase capital expenditure, potentially slowing the pace of investment as companies weigh the financial implications.
- Opportunities for Innovation: On the positive side, the energy challenge could accelerate innovation in energy efficiency and renewable energy integration. For instance, companies are exploring advanced cooling solutions like liquid cooling and direct-to-chip cold plates to reduce energy consumption in data centers, which could mitigate some of the energy demands . Additionally, public-private partnerships, such as the U.S. Department of Energy (DOE)’s initiative to co-locate data centers with new energy infrastructure on DOE lands, aim to fast-track development, potentially accelerating investment pace .
Impact on Brookfield: Challenge or Opportunity?
For Brookfield, the need for more energy infrastructure to support AI is both a challenge and a significant opportunity, given their existing expertise and strategic focus:
- Existing Expertise in Energy Infrastructure: Brookfield is one of the world’s largest infrastructure investors, with a portfolio that includes transport, data, utilities, and midstream sectors. Their Renewable Power & Transition business has invested in renewable energy, nuclear power, and other energy infrastructure, positioning them to meet the growing demand for AI-related energy needs . For example, Brookfield has a history of investing in renewable power, including a landmark deal with Microsoft for renewable energy supply and a $30 billion partnership with Intel for semiconductor manufacturing, both of which highlight their capability in energy infrastructure .
- AI Infrastructure Investments: Brookfield’s recent investments in AI infrastructure explicitly include components for energy generation and associated infrastructure. In Sweden, their SEK 95 billion investment for a new AI center in Strängnäs includes energy generation as part of the broader infrastructure, aiming to double data center capacity from 300 MW to 750 MW . Similarly, in France, their €20 billion program includes €5 billion for associated AI infrastructure such as data transfer, chip storage, and energy generation, demonstrating their proactive approach to addressing energy needs .
- Opportunity for Expansion: The growing demand for energy infrastructure to support AI creates additional investment opportunities for Brookfield. As AI continues to drive electricity demand, Brookfield can leverage its expertise in renewable power, nuclear energy, and grid modernization to invest in the necessary energy infrastructure. This aligns with Brookfield’s strategy of investing in the AI value chain, where they have already committed over €100 billion globally across digital infrastructure, renewable power, and semiconductor manufacturing . Their focus on sustainable and ethical investments, such as renewable energy, aligns with Europe’s goals, potentially opening doors to integrated projects that combine AI with energy infrastructure.
- Strategic Positioning: Brookfield’s early mover advantage in both AI and energy infrastructure positions them to benefit from public-private partnerships and government initiatives aimed at accelerating AI development. For example, the U.S. DOE’s initiative to co-locate data centers with new energy infrastructure on DOE lands could provide Brookfield with opportunities to expand its portfolio while supporting national AI goals . Additionally, Brookfield’s existing presence in Europe, including operations in renewable power and digital infrastructure, enhances their ability to navigate regulatory and logistical challenges.
- Challenges for Brookfield: While opportunities abound, challenges like construction delays for energy infrastructure, regulatory hurdles, and environmental concerns could affect investment timelines and costs. For instance, building new nuclear plants or upgrading grids requires significant coordination and may face opposition from local communities or environmental groups, potentially slowing down projects . However, Brookfield’s experience in managing large-scale infrastructure projects positions them to mitigate these risks.
Conclusion
Brookfield’s investments in Sweden and France are pivotal for Europe’s AI infrastructure, driving economic growth and aligning with national AI strategies. However, the energy demands of AI present significant challenges that could impact the pace of investment. Brookfield, with its expertise in both AI and energy infrastructure, is uniquely positioned to turn these challenges into opportunities. By integrating energy solutions into its AI projects and leveraging strategic partnerships, Brookfield can not only meet the energy needs of AI but also expand its investment portfolio, ensuring a sustainable and prosperous future in Europe’s AI ecosystem.
