Stephen Kotkin, global geopolitical expert and Stanford academic, has warned that there is an “increasing governability challenge in high-income democracies” where government departments face declining capacity to perform core functions due to complex regulatory systems and bureaucratic tasks. 

This has enabled populist politicians – who “don’t want to fix the government” but “want to remove the institutional constraints on executive power” – to thrive, said Kotkin, a senior fellow at the Hoover Institution. 

“They don’t want governance to function. They want to disable those governance structures so that they have what they consider free reign,” he told the Top1000funds.com Fiduciary Investors Symposium.   

“This is a deep and fundamental problem that we don’t have a solution for.” 

Looking at historical data in the US and European Union countries, while the population and size of government have only increased marginally since 1979, the regulations and responsibilities government has to carry out have experienced an “exponential” jump, Kotkin said.  

“Each regulation has a kind of logic, but they just accumulate. Something happens in the world, whatever it might be, and people say ‘Do something. Don’t sit on your hands’. So they pass a rule, a regulation or maybe even a law through the parliament,” he said.  

“In a complex system, nothing interacts with the other things the way you expect. One regulation might be for environmental restrictions, to defend the environment, but then it becomes the principal instrument for not building any more housing. 

“It’s the tasks of government that we’ve put on them that they are not designed to do and can’t cope with. So when they mess up, the populists come along and say, ‘government is failing’.” 

US president Donald Trump’s Department of Government Efficiency (DOGE), previously headed by Elon Musk, is the most notable attempt recently made for the purpose of improving government performance. As of October, it claimed to have saved $206 billion in government spending on its website.  

However, Kotkin is of the view that reducing the number of federal employees is not ultimately about cost-cutting, but “political purging”.   

“The federal bureaucracy is predominantly leftist, and if you are a Republican, elected-by-the-people president, you face this again and again and again that the bureaucracy sabotages your programs,” he said. 

“It happened to Bush. It happened to Reagan. It happened to the first Bush. It happened to Nixon. It’s a long-standing problem.” 

DOGE is a failure because it failed to understand that the public sector does not function like a private company, but a big, interwoven system where few people understand its inner workings, he said.  

“My argument is not getting rid of the officials, it’s getting rid of the tasks that the officials are being imposed with. Because there’s too much that we expect them to do, that they cannot do, that they don’t have the bandwidth for if they’re not designed to do those things, and those things are now perversely used.” 

There is a difference between a policy’s intention and its outcome, and not every government official has grasped the idea. Kotkin noted that things like subsidies can look like a clever fix but often backfire. Subsidising ethanol, for example, could be considered support for a cleaner fuel alternative, yet its production depends on oil-powered farming of corns which props up the industry and its lobbyists.  

He suggested that politicians refocus on the real challenge when enacting new policies, which is not to come up with ideas, but to get the system to enact them.  

“And not the imaginary system at a [policymaking] seminar where you go for sherry when you’re done, but the actual system that you’re facing. 

“I agree that we could think about what those [government reforms] are, but I just want to know how I’m going to implement them with the system that I have, with the politicians that I have, with the incentive structures that I have and with the voters’ preferences that might change over time.” 

Norges Bank Investment Management is a lean organisation despite managing a $2.2 trillion portfolio. Across the fund’s four global offices, there are only 700 staff, or $3 billion per person, which is why it has made pursuing AI-driven efficiency a core organisation initiative – and a non-negotiable requirement for its employees. 

The momentum for change came from the top. At the Fiduciary Investors Symposium, Thomas Larsen, lead portfolio manager of external strategies at NBIM, recalled CEO Nicolai Tangen once told staff in a town hall that “this [AI] ship is sailing, get on board or find a new place to work”. 

“There’s not an awful lot of space for building out redundancies and building out big teams. We don’t want to be more people. We want to stay as nimble as we can,” Larsen told the symposium at Stanford University.  

“We are limited in number of people, this will allow you to 10x your output. This will allow us to do more targeted work and focus more on the things that you are good at.” 

NBIM has seven portfolio managers who can each spend up to a quarter each year on the road visiting external managers – a total of 110 people managing more than $100 billion. How AI can make these visits less overwhelming is by conducting preliminary analysis on manager reports and other performance data.  

The fund’s AI agent, Claude by Anthropic, is plugged into its database, which has daily trading data for every manager it has had since 1998. 

“If someone sends me a snapshot of the portfolio a couple of periods backwards, I just drop that in [to Claude]. Then I can see what all my other portfolios in the same market did at the same time,” Larsen said.  

But behind this progressive technological push, Larsen acknowledged that staff development is top of mind for team leaders. The fund is striving to find the balance between improving efficiency while leaving room for junior staff to make mistakes and learn.  

“With these new tools, a lot of what I’m asking AI to do now is exactly the tasks that my PMs asked me to do when I joined as an analyst 12 years ago,” he said. 

“I can ask those questions at 2am in the morning or from an airport in Singapore – I’m not beholden to what time my analyst is awake anymore, but it also means that I am at risk of destroying my own pipeline of talent. 

“We’re thinking a lot about how do we still curate a talent pool and a pipeline of people who are going to be the next guys making the decisions, when they don’t actually have the luxury of making the mistakes that everyone else makes in the first couple of years.” 

Another progressive use case of AI in NBIM’s investment process is a scoring system for internal and external portfolio managers that can pick up subtle behavioural biases when they are executing a trade.  

For example, portfolio managers who are good at timing trades would receive the suggestion from the AI system to “swing bigger” while placing trades, and those who have a tendency to destroy value when trading would receive the opposite advice, Larsen said.  

“[With external managers] we can see do they make money when they are putting contrarian bets, if they trade before or after earnings, if they trade into something with momentum, if they trade out of something that is downward revisions,” he said. 

“We took it out to some of the managers, and 10 out of 10 came back and said ‘can we have two hours with the team that built this? Because we wanted to understand more’.” 

Above all the experiments, Larsen said it is critical that the board and stakeholders are brought into the process early through advocacy and education about the technology.  

“Show them how it works, show them what it can do,” he said. 

“Make sure that you have compliance on board, you have all the people who can say no, that they are comfortable, and can also speak to it [the technology] in an intelligent way, because otherwise you are going to run into roadblocks.” 

Funds are operating in an extraordinary social and economic environment, with Scott Chan, chief investment officer of CalSTRS, saying he has never witnessed so many “large shifts stacked on top of the other” in his investment career. Amid the change, investors are increasingly shifting to a scenario and regime-based approach to asset allocation.  

At the Top1000funds.com Fiduciary Investors Symposium, Chan – who took over the top investment job at the $374 billion CalSTRS a little over a year ago – said the fund had moved to a more defensive position ahead of Liberation Day in April, expecting a higher probability of a recession in the US than what was priced in.  

“That meant increasing the more diversifying elements of our portfolio – fixed income and hedge funds – and raised cash. We felt pretty good as the market was going down. 

“I tell the team that this was actually a highlight of the year, because one of the things that’s unique to CalSTRS is we have about 44 per cent of our assets allocated to private markets and alternatives. So liquidity management is becoming very key to this environment. 

“To ballpark, we probably have to have something like $35 billion in liquidity if we go into a correction… we actually were in position in front of what we thought could have been a correction with enough liquidity.” 

However, Chan acknowledged the approach has its risks: the defensive position cost around one basis point of performance during the subsequent market recovery and the team needed to “trade up quickly”, he said. “But I’ll take that, because I think we were ready again in front of what we thought could be something way different, like a crisis might have ensued, or a recession.” 

Sentiment shifts 

Anna Langs, managing director of asset allocation, risk management and innovative solutions at San Francisco Employees’ Retirement System, said the fund has similarly been strengthening its liquidity management. Around half of the fund’s assets are allocated to private markets, but it also has close to a 10 per cent allocation to hedge funds, which Langs said provided both return and liquidity during COVID when the two traditionally liquid asset classes – equity and fixed income – failed to support the liquidity needs.  

Matilde Segarra, president and US chief executive of the $722 billion APG Asset Management, said the Dutch fund is also focusing more on regime analysis to inform more dynamic and nimble asset allocation.  

One big question the fund is grappling with now is how it approaches geographical diversification. Investors are rethinking their US exposure due to nervousness around debt and deficit, but Segarra pointed out that the problem is not unique to the world’s largest economy: “there are a lot of indebted governments around the world”, she said.  

What she is really worried about is whether investors’ sentiment towards a certain country is increasingly dominated by short-term events.  

“I am very worried about sentiment at the moment. What I mean by that is if I see the conversations that are going on in the company – again, I work for a firm that has offices across the world – I really see that the Europeans look at the United States right now with angst and scepticism,” she said. 

“And American colleagues that feel constantly attacked at the moment by the questions that they get from their European counterparts, are constantly pointing out that Europe isn’t growing enough and that Europe has an innovation problem. 

“I see almost that the polarisation that you see in society and in political systems across the world is also happening in my organisation on a small scale.  

“We’re supposed to be long-term investors, and I see that the conversations at even the highest level of the company, are conversations driven by sentiment and with a lot of short-term emotions dominating the dialogue…  at some point that is going to affect the quality of decision making.” 

Amid geopolitical and economic uncertainty, CalSTRS’ Chans said investors should always be ready to pivot their strategy as a “bulletproof” investment now could unravel very quickly should capital or ownership control policies get enacted in different countries. To do that, the fund is applying a total portfolio approach in its investment process so that it can “map the total risk exposures” better.  

“With the geopolitical risks and the issues around governments becoming more involved, as well as all the other risks we describe, we could be in for a lot more volatility.  

“So we have to have a team in a design where we can get more diversified or dynamic, but also be able to trade up quickly too, which I think is something that, if I looked over the past couple decades, wasn’t as necessary. 

“We have been exposed to growth investments, and that’s worked rather well. I don’t think you want to be out of growth… but I’m similarly worried about how quickly that might disrupt other industries. We’re looking through our portfolio and asking ourselves the question of what do we need to sell here? Alongside the question of what we’re buying?” 

Mark Horowitz, a leading computer scientist and electrical engineer at Stanford University, has declared that Moore’s Law is “basically over”, which will have significant ramifications for artificial intelligence investors who are counting on more computing power to feed into more complex models.  

It is a view shared by Nvidia CEO Jensen Huang, who pronounced the law “dead” in 2022 while justifying a hike in chip prices.  

The law refers to the observation that the number of transistors on an integrated circuit doubles every two years while the costs decrease. That’s an economic factor that has driven the semiconductor industry, said Horowitz, who is chair of the department of electrical engineering and professor of computer science at Stanford University. 

“If I have a product and I’m selling it in high volume, when I move to the next generation technology, it’ll become cheaper to produce, therefore I will make more money, or it will prevent my competition from underselling me. We can then create either the same parts we have now cheaper, or we can build even better parts at the same price point,” he told the Top1000funds.com Fiduciary Investors Symposium.  

“We still are scaling technology. We’re still building more advanced processing nodes. We’re cramming more transistors per square millimetre, but unfortunately, the transistors are not getting cheaper.” 

Machine learning scaling rules state that bigger models tend to mean better performance, which is why the dismantling of Moore’s Law and sluggish computing power growth could be a roadblock for AI development, Horowitz said. 

“This is a major disruption, because our expectation is that we can do more computing and we’re pushing more stuff to the cloud,” he said. 

“Now Moore’s law is actually flat, so all that [AI model] complexity is going to have to be done through sort of algorithms or applications… if we think about the economics, where is money going to be made?” 

Horowitz is of the view that most companies are losing money on their AI projects. “All the hyperscalers in the world [like Google, Meta, Amazon and Alibaba] are spending enormous amount of money trying to protect some of the business they have because they’re worried about losing it,” he said.  

He suggested the profitability of an AI application hinges on two things: the service cost and the liability cost. The latter would be increasingly pronounced as the world moves towards agentic AI applications as service providers will need to start taking responsibility for decisions and suggestions of their AI agents.  

Taking these costs into account, Horowitz said it is highly likely that profitable AI models or applications in the future will not be large, but small. 

“Both of those, to me, indicate that what you’re going to try to do is reduce the scope of the model to something in a particular area, so you can make it cheaper to serve and less likely to make a bad thing,” he explained. 

“If that’s true, then the people who are going to start making money are not the people who are using the really big models. It’s the people who have used the big models to create smaller models or more domain specific models.” 

These views are not pessimistic predictions for the AI space, Horowitz said, adding that he is optimistic about models which can find useful and specific applications.  

“I do think there’s going to be some big craters, because there’s been billions of dollars invested in a lot of companies, and I’m not sure they’re going to be the people who survive,” he said. 

“I have no doubt that machine learning is going to change the world. The world’s going to be very different. Who’s going to be the player there, I think, is still to be decided.” 

The size of the current infrastructure investment gap and the speed at which it is widening mean there is both a desire and a need for more public-private partnerships to unlock funding. Investors say that collaboration with local governments and raising public awareness of private investment benefits are crucial. 

From roads and airports to energy and water, the US is seeing a rapid deterioration in the condition of its critical infrastructure. Industry estimates suggest there is a $2.6 trillion investment gap to modernise these features before 2030, per the American Society of Civil Engineers.  

At the Top1000funds.com Fiduciary Investors Symposium, Janet Cowell, mayor of North Carolina’s capital city Raleigh and former state treasurer, said infrastructure investment is entering a “very fluid and dynamic” era but that it will take some time for some officials to realise private money needs to play a bigger part.  

“[When] people realise the money’s not flowing, they’re going to scramble for existing revenues,” she told the symposium at Stanford University.  

Raleigh is grappling with an explosion in not only the cost of building materials but also that of land, which went up as much as 70 per cent as the city became an attractive real estate investment destination post-COVID, Cowell said. The city had to abandon certain infrastructure projects as a result. 

“For example, we had a State General Assembly member who said, ‘you’re not funding our transportation enough, so I’m going to try to grab your food and beverage money and reallocate that and try to strong-arm the locals’,” she said.  

“People are going to find other goofy ways to try and do this [invest in infrastructure], and ultimately they’re going to have to come to more of a public-private [model]. I think we’re going to need some enabling legislation.” 

Mikael Limpalaer, head of Americas at AustralianSuper, the A$387 billion ($254 billion) Australian pension fund which has over A$40 billion ($26 billion) in global real assets, said people are “much more amenable” to private or semi-private infrastructure funding when they can see that it is directly linked to the growth of their retirement savings.  

There also needs to be more awareness from the public that, in the absence of a large private infrastructure investor, the alternative funding methods could be much less desirable.  

“Is it going to be more taxes? More debt for the state or the municipality? That’s a very large part of the educational work local and state politicians need to do with their constituents to make that [public-private] mix work,” he said.  

“Then you’ve got the existing, more traditional road networks, airports, water system and energy grids, which are in need of maintenance and upgrade, and particularly in the US, the governance and the ownership structures are not designed or built to accommodate, in most cases, public-private partnerships. 

“We’re meeting with lots of governors and municipal authorities that are keen to engage with investors in the space.” 

There are around 500 passenger airports in the US and only one is run by a private operator – the Luis Muñoz Marín International Airport in San Juan, Puerto Rico. Andrea Mody, IFM Investors head of North America clients and strategy, said that number is out of pace with other countries.  

“In Australia alone, we’ve invested in eight airports. We’ve invested in four airports in Europe. And that is not an asset class that’s even really available,” she said. 

Regulatory reasons are a part of that, Mody said.

“When airports were built in America, they were built with public money, and there were federal grants that states and municipalities took out, and some of the requirements for taking those grants were that you could never privatise your airport.” 

“The US also has a very well-developed municipal financing market… but obviously states and municipalities are capped at what additional debt they can issue in 2025 and beyond.” 

The point with infrastructure investments is not to build cheaply, but build well, Mody said. It’s a delicate balancing act between capital expenditure and affordability for the infrastructure’s end consumers, which Mody said the public sector could control via mechanisms like pricing caps and maintenance standards.  

Many critical moments of US growth in its history have been driven by traditional infrastructure – periods like the Gilded Age, where the railroads and energy contributed to economic prosperity, and the establishment of the Interstate Highway System post-World War II. 

“We’re thinking a lot about data and digital and AI, and that’s a really important part of our growth trajectory, but the movements of people and stuff are still going to need to be there in a large way if we’re going to continue to grow,” Mody said. 

“And it’s going to take a real [public-private] partnership and a different way of thinking about how we did it in the past versus how we’re going to do it in the future.” 

Stanford president Jonathan Levin said the university’s top priority is maintaining the partnership with the federal government while safeguarding its operational freedom, as the institution balances financial reliance on Washington and political scrutiny from the Trump administration. 

The university has been swept up in US president Donald Trump’s crackdown on the nation’s higher education institutions, which he has repeatedly criticised as “liberal” and “woke” with an “anti-American” or antisemitic bias, using the reduction of federal funding as powerful leverage. This August, Stanford made 363 staff redundant, citing budget reductions.  

But at the Top1000funds.com Fiduciary Investors Symposium hosted on the Stanford campus, Levin said some recent criticisms directed at American universities are not new and are, in fact, fair. 

“The US is a country that has become more and more politically divided over the last however many years, and university faculty and student populations are, by and large, on one side of that political divide,” said Levin, who is also an economist and Bing Presidential Professor at the university.  

“We should learn a lesson from that and make sure that, going forward, universities are not so enmeshed institutionally in politics. The students and the faculty can be involved and that’s their freedom to do that, but the institutions shouldn’t.” 

Levin said that at the heart of American universities’ excellence is their ability to operate freely and independently, including in setting curriculum and pursuing research projects. That freedom stems from the post-World War II framework for federal support of science established by Vannevar Bush, an engineer and the head of the US Office of Scientific Research and Development at the time. 

The framework established the federal government’s responsibility to fund research and development as industry support would lack appropriate scale, and emphasised a peer-reviewed, merit-based allocation of grants. 

“Stanford – probably more than any other university – was a beneficiary of that. Stanford was founded in 1891 and coming out of World War II, we were a regional university of fairly modest calibre,” Levin said. 

“We were in financial difficulty at the time too, because the endowment hadn’t been that well managed, and folks leading Stanford at the time saw there would be an opportunity with federal funding for science to build up a research enterprise.” 

The university built up its engineering and science departments, and later complemented them with humanities, history and other arts departments. It also lent land to technology companies such as Fairchild and Varian, which cemented Stanford’s leadership in the early development of Silicon Valley. 

“That really all came out of the federal-university partnership that led to the US having this extraordinary innovation economy. It’s a great story, and it’s still the best recipe that this country has to be the leader in innovation and to be at the frontiers of knowledge,” Levin said. 

“So a big focus for us right now is how do we sustain that great partnership that universities have enjoyed with the federal government, and get back to a place where the American people support us enough to fund us, and give us the freedom that allows our universities to be exceptional, respected and contributing to the country and to the world.”