As artificial intelligence (AI) technologies evolve, they have become a cornerstone of modern industry, fuelling innovations across diverse sectors. However, this rapid development comes with a significant downside: the energy consumption required to sustain AI applications is monumental. The increasing computational power needed to execute complex machine learning algorithms and proces large datasets highlights an urgent need for investment in power generation. This creates a unique intersection where energy and AI converge, leading to both challenges and opportunities for investors.
Multiple factors underscore the significance of power generation as a critical investment theme. Data centers, which serve as the backbone for AI operations, are among the largest consumers of electricity. As adoption of AI escalates, the energy requirements associated with expanding data center infrastructure are expected to surge. Thus, tapping into power generation investments is not just prudent; it’s essential for supporting the burgeoning AI ecosystem.
Nuclear energy has garnered attention as a potential solution to tackle the escalating energy needs of the AI sector. A notable arrangement between Microsoft and the recently decommissioned Three Mile Island nuclear plant exemplifies a proactive approach to sourcing clean energy for AI initiatives. Moreover, innovations such as small modular reactors (SMRs) are entering the discussion, promising a reliable and low-carbon means of power generation that could be harnessed to meet AI’s energy requirements.
These SMRs represent a shift towards a more flexible, safer, and efficient nuclear energy model. As renewable energy sources gain traction, a balance between sustainability and the high energy demands of AI will likely become increasingly pertinent. The integration of nuclear power can contribute to a diversified energy portfolio capable of supporting AI technologies sustainably.
Beyond traditional utilities and power generators, several other industries are poised to benefit from the anticipated infrastructure build-out. Notably, engineering, procurement, and construction (EPC) firms stand to play a vital role in the development of energy solutions for AI. Companies like Bechtel, KBR, and Fluor Corporation exemplify key players in this realm.
Fluor, founded in 1912 and headquartered in Irving, Texas, is one of the world’s largest publicly traded EPC firms. Its diverse portfolio spans various sectors, including energy, chemicals, and government services. This wide-ranging expertise makes Fluor uniquely positioned to capitalize on the power generation needs tied to AI’s growth. In particular, Fluor specializes in designing, constructing, and maintaining power generation facilities, from gas and coal to renewable sources such as wind and solar, as well as nuclear power.
A noteworthy chapter in Fluor’s narrative is its publicly traded subsidiary, NuScale Power, which is pioneering small modular reactor technology. This innovative approach to nuclear energy offers a promising avenue for investment owing to its adaptability and potential cost-effectiveness. However, it’s essential to recognize that NuScale itself operates as a startup with an enterprise value of $2.5 billion but has only generated about $13 million in revenue to date. This level of volatility indicates that investing directly in Fluor may serve as a more stable and diversified strategy.
The prospect of SMRs revolutionizing nuclear energy is complemented by Fluor’s vast experience in project management, engineering, and maintenance. By participating in the development and deployment of these advanced nuclear facilities, Fluor can help shape a more sustainable energy landscape capable of supporting AI’s demand.
From an investment perspective, Fluor presents an intriguing case. Currently valued at approximately 16.3 times projected earnings, it trades at a discount compared to the overall market and is aligned with its historical earnings multiples. This valuation reflects potential for growth as the demand for energy surges. Considering that Fluor’s next earnings report is expected in the first week of November, there may be lower volatility leading up to this date, likely making it a strategic time to explore options trading strategies.
For example, one could consider selling an October put option while buying longer-dated calls and offsetting shorter-dated call sales to manage decay. This hybrid approach can mitigate risks while allowing investors to capitalize on potential growth in Fluor’s stock as the demand for energy solutions soars.
As AI technology demands more electricity, investments in power generation have become a critical theme for the future. Companies like Fluor Corporation are positioned to lead the charge in developing sustainable, high-capacity energy solutions necessary to support this growth. Investors keen on navigating the intersection of energy and AI must consider the strategic potential within the realm of power generation and EPC services, ensuring they are well-prepared to seize the opportunities that lie ahead.