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BlackRock, Microsoft AI Partnership Raises $12.5 Billion So Far
BlackRock Inc. has raised $12.5 billion as part of a partnership with Microsoft Corp. to bankroll data centers and energy infrastructure, advancing its efforts to cash in on the artificial intelligence boom. The fundraise brings BlackRock closer to a $30 billion money-raising goal laid out when it announced the partnership in 2024. That AI partnership "continues to attract significant capital," BlackRock CEO Larry Fink said on the asset manager's call Thursday with analysts after it reported its fourth-quarter results. The venture includes BlackRock's Global Infrastructure Partners, the United Arab Emirates' MGX investment vehicle, Nvidia Corp. and xAI. With leverage, the $30 billion goal could eventually finance $100 billion of investments.
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BlackRock Says AI Partnership Raises $12.5 Billion Toward $30 Billion Goal | PYMNTS.com
By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. The investment management firm and the tech giant joined forces in 2024 to fund data centers behind the AI boom and are now closer to their $30 billion goal, the report said. The partnership also includes Nvidia, xAi and United Arab Emirates-affiliated MGX investment group. The effort "continues to attract significant capital," BlackRock CEO Larry Fink told analysts during the call, per the report. The partnership is aiming to pull in $30 billion of private equity capital and then mobilize up to $100 billion in investment potential, including debt financing for infrastructure projects, PYMNTS reported in September 2024. "We are committed to ensuring AI helps advance innovation and drives growth across every sector of the economy," Microsoft Chairman and CEO Satya Nadella said at the time. "The Global AI Infrastructure Investment Partnership will help us deliver on this vision, as we bring together financial and industry leaders to build the infrastructure of the future and power it in a sustainable way." The group made a $40 billion deal in October to acquire Aligned Data Centers from Macquarie Asset Management, which called it the largest data center acquisition in history. Meanwhile, new research suggests that AI may no longer need massive data centers to scale. A study from Switzerland-based tech university EPFL found that while frontier model training is still computationally intensive, many operational AI systems can be deployed without requiring centralized hyperscale facilities. Instead, these systems can distribute workloads across existing machines, regional servers or edge environments, cutting back on the reliance on large, centralized clusters. "The research highlights a growing mismatch between AI infrastructure and real-world enterprise use cases," PYMNTS reported Friday (Jan. 9). "These systems often rely on smaller models, repeated inference and localized data rather than continuous access to massive, centralized models." Nvidia found that small language models could carry out 70% to 80% of enterprise tasks, leaving the most complex reasoning to large-scale systems, a structure that is becoming the most cost-effective way to operationalize AI.
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BlackRock and Microsoft have raised $12.5 billion toward their $30 billion goal to bankroll data centers and energy infrastructure for the growing artificial intelligence sector. The Global AI Infrastructure Investment Partnership includes Nvidia, xAI, and UAE's MGX, with plans to mobilize up to $100 billion in total investment potential through debt financing.
The BlackRock Microsoft partnership has successfully raised $12.5 billion as part of an ambitious initiative to bankroll data centers and energy infrastructure supporting the AI boom
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. The fundraise marks significant progress toward the partnership's $30 billion goal, which was announced when the collaboration launched in 20241
.BlackRock CEO Larry Fink confirmed during the asset manager's fourth-quarter earnings call that the AI infrastructure venture "continues to attract significant capital"
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. The Global AI Infrastructure Investment Partnership brings together major players including BlackRock's Global Infrastructure Partners, Nvidia Corp., xAI, and the United Arab Emirates' MGX investment vehicle1
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Source: PYMNTS
The partnership's strategy extends beyond the initial $30 billion goal in private equity capital. With leverage, the consortium could eventually finance up to $100 billion of investments in infrastructure projects
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. This approach allows the group to amplify its impact on the growing artificial intelligence sector through debt financing mechanisms.Microsoft Chairman and CEO Satya Nadella emphasized the partnership's mission when it launched: "We are committed to ensuring AI helps advance innovation and drives growth across every sector of the economy. The Global AI Infrastructure Investment Partnership will help us deliver on this vision, as we bring together financial and industry leaders to build the infrastructure of the future and power it in a sustainable way"
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Source: Bloomberg
The group demonstrated its commitment to investment in data centers through a landmark $40 billion deal in October to acquire Aligned Data Centers from Macquarie Asset Management, described as the largest data center acquisition in history
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. This acquisition underscores how data centers crucial for the AI boom are commanding premium valuations as demand intensifies.Related Stories
While the partnership focuses on building massive infrastructure, new research from Switzerland-based tech university EPFL suggests the AI landscape may be evolving. The study found that many operational AI systems can be deployed without requiring centralized hyperscale facilities, instead distributing workloads across existing machines, regional servers, or edge environments
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.Nvidia Corp. research indicates that smaller models could handle 70% to 80% of enterprise tasks, leaving only the most complex reasoning to large-scale systems
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. This distributed infrastructure approach may represent the most cost-effective way to operationalize AI for many businesses, creating a potential divergence between frontier model training needs and everyday enterprise applications. The tension between centralized and distributed approaches will likely shape how capital flows into AI infrastructure over the coming years.Summarized by
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