Q2 2025 Insight

Elon Musk's Department of Government Efficiency (DOGE)

The Department of Government Efficiency led by Elon Musk has been tasked with reducing waste, fraud, and inefficiency. We view this as an interesting experiment to see whether entrepreneurs can run government better than the government can run itself. A way to think about how entrepreneurs are tackling the government deficit is very simply from a revenue and expenditure basis, viewing it as a profit and loss statement.

To put some numbers in context, at the moment the government is spending around $7 trillion a year and this is balanced by about $5 trillion in revenues. Now, a large part of this reflects the enormous increase in spending that was associated in the pandemic and the challenges in reducing that. But it is notable that Trump's targeted $2 trillion reduction in spending associated with the DOGE would be sufficient to close that gap. So, if DOGE can get expenditure back to where it was in 2019, keep the revenues as they are, there would be a fiscal budget surplus. That is very simply how the DOGE is trying to tackle the budget deficit.

The Elon Musk playbook is very similar to what he did at Twitter. Before he bought the company it had 7,500 employees, and then when Musk took over in 2022 the workforce was slashed to 1,500 employees, a pretty drastic cut.

He's using the same playbook for US government. So, for example, USAID had 10,000 employees and he's aiming to cut the employee headcount by 50%. That, of course, will take a knife to the USAID $50 billion budget, which it is today.

The Impact on Growth

What then is the impact going to be on growth and inflation? Well, we estimate that realistically the government might be able to achieve savings of approximately 250 billion a year in each of the next four years. That would amount to a total saving over Trump's administration of around a trillion dollars, which will be quite something. At the same time, Trump has talked about giving 20% of that back to tax paying consumers. So, the net amount might be something of the order of about 200 billion a year. At the same time, there's going to be an impact on the economy from the tariffs that Trump has imposed. We don’t know the full impact because we haven't heard yet the extent to which other countries will retaliate, nor do we have full details on the countries and the size of the tariffs that Trump is going to impose around the world. But the best guess at the moment is that the size of the drag on the economy be of the order of say, 150 to 200 billion per annum. Offsetting that, Trump's policies are seeking to encourage an increase in spending on technology, in particular on artificial intelligence. And so that might offer an offset also of the order of around 150 to 200 billion per annum.

So, overall we estimate there to be a net drag on the economy of around 0.2% per annum. The impact on inflation is expected to be around double that, and it depends on the size and the scale of the tariffs, and also what other countries do in response.

We put the scale of the impact on inflation around about 0.5% to 1% higher. There will be some offset, which will be based perhaps on policies such as Trump's ‘Drill Baby Drill’ strategy, which will seek to increase output of the energy sector. And at the same time, that could result in a reduction in prices. So, if for example, the price of oil were to go down by around $10, then we think that would take about 0.2% off inflation.

So, there's lots of moving parts here, but on average, we expect policies to result in a slight reduction in growth and a slight increase in inflation.

AI Boom

Turning in more detail to the AI theme, it is notable that there is a huge amount of expenditure expected from the large companies over the next few years, amounting probably to several hundred billion dollars., The combined capital spending of Microsoft, Alphabet, Amazon and Meta, for example, is estimated at US$320bn in 2025. We think it's convenient to split out the spending into different parts of the market and to think about the way that AI spending will evolve from hardware through to the end user.

The first part of how we view the AI value chain is hardware. Hardware is where the semiconductors, the networking equipment, the power consumptions needed to power AI. Remember, an AI search is roughly four times more power consumptive than a typical Google search. That is where the hardware layer sits. The second part of the value chain is around the infrastructure. So, these are the big server farms and the big hyperscalers that needed to power AI and across the chain as we move forward. The third part are the language models itself. We heard all about DeepSeek in Q1, and that has been interesting because it shows that China is not that far behind United States in terms of those large language models.

The next part of the value chain is around the software. All of those powerful statistics and numbers, being able to present it in a very easy form for a client or an investor to actually look at. And finally, the customers, the end customers themselves. They are probably the biggest beneficiary of all of this chain alongside AI and would provide the real value.

One thing that we takeaway from the value chain is that we expect that creativity will be valued much greater in the future.

Read our Outlook 2025 if you would like to discover more of our themes that we are monitoring for the year.

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