The adoption of artificial intelligence (AI) across various sectors can be a pivotal force in the creation of a flourishing future for all. It is now obvious that AI offers unprecedented opportunities to address complex global challenges, enhance efficiency, boost productivity, and improve operations. However, it is essential that we collectively ensure its deployment with ethical and environmental concerns in mind. Through their presence across sectors and throughout the AI value chain, long-term asset managers must play a critical role in ensuring the safe, secure, and environmentally sustainable development of AI in our economies.

Artificial intelligence has already demonstrated its potential in various domains, from health care and finance to more efficient industrial processes. Yet, the underlying infrastructure and hardware enabling AI needs to be deployed with environmental constraints in mind. This includes data centers, high-performance computing systems, and communication networks that support the deployment of cloud platforms and AI applications. Long-term asset managers must drive the development of AI infrastructures that put environmental sustainability on an equal footing with operational efficiency. Indeed, with a long-term investment horizon, asset managers are uniquely placed to drive the underlying megatrends of AI and energy transition, which are both profoundly changing our economies without being swayed by short-term fluctuations in public valuations.

What can asset managers do? Let’s take the example of data centers. Data centers are now recognized as critical infrastructure in many countries for their fundamental role in connectivity, storage, and AI deployment. Yet, they consume exponential amounts of energy and, therefore, indirectly contribute to a substantial increase in carbon emissions. According to the International Energy Agency, after globally consuming an estimated 460 terawatt-hours (TWh) in 2022, data centers’ total electricity consumption could reach more than 1,000 TWh in 2026. This more than doubling of electricity consumption from data centers in just a few years comes from several factors, such as the increasing demand for AI applications throughout economic sectors and exponential power intensity of graphic processing unit chips to support ever-more data-hungry fundamental models.

Asset managers are uniquely placed to drive the underlying megatrends of AI and energy transition.

Long-term asset managers can prioritize investing in companies that aim at minimizing environmental impact. For example, this includes prioritizing locations with access to low-carbon energy (renewables and nuclear), designing data centers with, in mind, optimized energy use, and implementing waste reduction strategies, such as heat reuse, into district heating networks. Such strategies are also directly creating value for asset managers. Indeed, data centers with higher energy efficiency and access to low-carbon energy—which tends to be cheaper—are also more attractive for clients who bear the costs of energy passed through.

This should be coupled with larger investments in low-carbon, renewable energy. It is expected that 7.5 terawatts of additional electricity capacity will be needed globally to supply increasing energy demand by 2030. Here again, asset managers with a long-term investment horizon can finance this increase in capacity while benefitting from a sector that has proven to offer attractive risk-adjusted returns.

AI is also an incredible opportunity for asset managers themselves if they succeed to include AI in their own operations. It is thus likely to drive consolidation of the market, with asset managers who will have succeeded in the inclusion of AI into their operations being the winners. Scale will also be of the utmost importance to benefit from larger proprietary databases, driving additional insights on markets and being able to invest more into AI.

The role of long-term asset managers is, therefore, pivotal in the development of AI infrastructure that can both drive more innovation in our economies and be environmentally sustainable. Their investment decisions and strategic focus on environmentally respectful practices can significantly influence the trajectory of AI development, ensuring that it contributes positively to economic growth while controlling negative externalities. Asset managers should thus help build a future where technology and sustainability go hand in hand to create long-term value for their investors.