US midterms: less political risk, same AI question

The United States midterm elections may have reduced political risk, but the underlying question about AI stock valuations remains unchanged. The decisive outcome of the elections, free of prolonged legal battles or unrest, makes it harder for disputes over individual seats to alter Congress control. However, this political risk removal does not address the sustainability of earnings driving AI-related investments.

Divided government is likely to result in political noise and limited legislation from both parties. Trump could veto Democratic legislation, while Democrats block his agenda. Executive orders and court challenges are expected to persist for months or years. Despite this, businesses have more time to plan as the range of potential policy changes narrows. Nonetheless, congressional opposition can still hinder policy changes that might disrupt trade, investment, and business confidence.

There is a potential long-term benefit if increased oversight boosts confidence in consistent rules. Companies will be more inclined to commit capital when commercial outcomes depend on investment quality rather than political access. However, the argument that divided government always leads to lower spending is less convincing, as Democrats' healthcare and social support priorities, as well as Trump's spending appetite, may necessitate funding.

State governments also play a significant role in the economy, even when Washington is gridlocked. Changes in state spending, taxation, and regulation can impact the overall economic landscape. For AI investments, state and local decisions are crucial sooner than Washington's decisions.

Data centers, central to AI infrastructure, face various political concerns such as electricity availability, water use, land use, and surrounding community costs. Though opposition has limited effects on commercially viable projects, water requirements and grid connection restrictions might not be significant obstacles. Texas, a key area for data centre development, offers useful insights into the actual rules and projects affected by regulations.

In summary, the AI investment cycle's key question remains the origin of today's AI profits. Shortages can lead to higher prices for various businesses in the supply chain, including chipmakers, data centre operators, equipment suppliers, and power or site access providers. While some profits may reflect durable competitive advantages, others will diminish as supply expands.