The U.S. Department of Energy (DOE) has unveiled an ambitious new plan aimed at achieving the long-held goal of generating energy through nuclear fusion. This initiative outlines a strategy to bolster research and development and foster collaborations between the public and private sectors to make fusion power plants a reality.

Central to this roadmap is the role of artificial intelligence (AI), which is seen both as a catalyst for breakthroughs in fusion technology and as a driver for creating new energy sources to meet the increasing power demands of data centers. The DOE envisions AI not only as a key tool in advancing fusion research but also as a significant factor in the future energy landscape.

Despite the bold aspirations, the DOE acknowledges the challenges ahead. The timeline for achieving commercial fusion energy is notably ambitious, yet the plan lacks specific details on how to overcome the scientific hurdles that have stymied progress for decades. Moreover, while there is a growing network of startups and researchers eager to push the boundaries of fusion technology, the DOE admits that it currently lacks the necessary funding to fully support these efforts.

The complexity of this endeavor stems from the fundamental differences between current nuclear fission technology and proposed fusion methods. While fission involves splitting atoms to release energy, fusion seeks to combine atoms in a controlled manner to produce energy, akin to the process powering the sun. The advantage of fusion is its potential to generate energy without the hazardous radioactive waste associated with fission and without relying on fossil fuels, offering a cleaner, sustainable energy solution if successfully harnessed.

Why is this such a large task? Today’s nuclear fission plants split atoms apart to release energy. Nuclear fusion plants, in contrast, would fuse atoms together to generate energy in a controlled way. (You get a hydrogen bomb when this is done in an uncontrolled way.) The upside to achieving fusion would be that it doesn’t produce the same radioactive waste as fission, nor does the process rely on polluting fossil fuels.

Fusion essentially mimics the way stars produce their own light and heat. While this could be an abundant carbon-free energy source, it also takes a tremendous amount of heat and pressure to fuse atoms together. As a result, it’s been extraordinarily difficult to achieve a fusion reaction that results in a net energy gain (something called “ignition” in industry-speak). Scientists accomplished this for the first time in 2022 using lasers. Researchers developing fusion technologies are working to re-create that feat and figure out how to sustain the reaction longer.

There have been some other significant changes in recent years that have fed into all the current buzz around fusion. The generative AI boom has left big tech companies scrambling to get enough electricity to power more data centers. Sam Altman, Bill Gates, and Jeff Bezos have all backed fusion startups developing their own plant designs. Both Google and Microsoft have announced plans to purchase electricity from forthcoming fusion power plants that are supposed to be online by the late 2020s or 2030s. More than $9 billion in private investments have flowed into fusion demonstrations and prototype reactors, the DOE says.

There are other big gaps to fill, which is where the DOE says it can step in. The roadmap emphasizes bringing together the public and private sectors to build out the “critical infrastructure” needed to make fusion commercially viable, such as producing and recycling fusion fuels (typically hydrogen isotopes called tritium and deuterium). Another “core challenge area” the document highlights is the need to develop structural materials strong enough to withstand the extreme conditions at a fusion plant. (Remember, you’re sort of replicating the environment within a star.)

It also mentions the development of regional hubs for fusion innovation, where DOE laboratories might work with universities, local and state governments, and private companies to build up a workforce for these new technologies. One hub would be a collaboration between Nvidia, IBM, and the Princeton Plasma Physics Laboratory, and the DOE to “establish an AI-optimized fusion-centric supercomputing cluster” called Stellar-AI.

The DOE dedicates an entire section of the roadmap to AI, which it calls a “transformative tool for fusion energy.” Researchers can use AI models to construct “digital twins” to more quickly study how experimental facilities would perform, the roadmap says as an example.

The document also comes with a big disclaimer. Written at the top, above the executive summary, it says: “This Roadmap is not committing the Department of Energy to specific funding levels, and future funding will be subject to Congressional appropriations.” In other words, the DOE isn’t ready to throw any money at this plan just yet.

And while the Trump administration has folded fossil fuels, nuclear fission, and fusion into its ambitions for so-called “energy dominance,” the president has clawed back funding for solar and wind energy projects that are already much faster and typically cheaper to deploy to meet America’s growing electricity demand.