Please find an excerpt from our March 2026 Newsletter below.

Let’s Talk about AI, Jobs and the Stock Market

There continues to be a lot of predictions about how AI is going to impact the economy, jobs, the stock markets and every aspect of life. It feels like mentions about AI in the media even outweigh the mentions of President Trump; some are not sure which is scarier. Is the impact of AI something to be scared of or to embrace, or maybe just an awareness is sufficient. In addition to the AI that most of us understand as a chat bot where we ask questions and get answers or create or analyse documents or other media, there is a lot of talk about AI “agents”. 

An AI agent is a piece of software that can perceive information, make decisions, and take actions autonomously in order to achieve a goal. It seems that agentic AI, the use cases of which there are many, is where businesses are speculating that jobs may be most at threat; or looked at another way, where productivity gains may be the highest.

Below are links to four of the many articles I have read recently on AI, each has a different take on some potential outcomes for the future, they are all worth reading, I will provide a very brief summary below and then continue with some of my own thoughts:

“Tech Has Never Caused a Job Apocalypse. Don’t Bet on It Now” in the WSJ Feb 27, by Greg Ip

The article argues that fears of an AI-driven “job apocalypse” are likely overstated because history shows that technological advances typically reshape employment rather than destroy it. New technologies do eliminate some jobs—especially those where tasks can be easily automated—but they also raise productivity, create new industries, and lower costs, which boosts consumer spending and ultimately generates new employment opportunities elsewhere in the economy. Evidence so far does not show widespread AI displacement; for example, jobs in fields often considered vulnerable, such as software development, have continued to grow, with developer employment rising about 5% year over year, broadly in line with long-term trends.

The article concludes that even if AI eventually replaces more workers than it creates, the broader economy would likely adjust: savings from automation would be spent or reinvested, supporting new businesses and jobs. Past shocks—from automation in manufacturing to globalization—caused painful sectoral losses but did not produce sustained economy-wide unemployment. The bigger risks, Ip suggests, are not mass joblessness but economic cycles triggered by overinvestment in AI or temporary layoffs during a downturn, rather than a structural collapse of the labor market

“Altman, Amodei and Musk fight dirty for the biggest prize in business” in the Economist on March 12th.

The article describes an intense rivalry between three leaders at the center of the AI boom—Sam Altman of OpenAI, Dario Amodei of Anthropic, and Elon Musk, whose SpaceX has merged its AI ambitions with xAI. The author(s) argues that the race to build powerful AI systems has become the largest and most aggressive capital-raising contest in tech history, with the three companies pursuing enormous valuations and potential IPOs. OpenAI is reportedly targeting a valuation around $1 trillion, Anthropic more than $500 billion, and the Musk-linked entity roughly $1.5 trillion, meaning the combined fundraising could rival the total value of U.S. IPOs over many of the last several years.

Beyond the money, the article emphasizes the personal and strategic rivalry between the three leaders, whose companies are competing to dominate the next generation AI models and the enormous economic value they may create. The competition has become increasingly combative—through lawsuits, public criticism, talent poaching, and strategic alliances—because the stakes are so high: whoever leads in advanced AI could control the most valuable technology platform of the coming decades. In short, the article portrays the AI race not just as a technological contest but as a high-stakes power struggle among a few tech titans vying for what may become the most valuable industry in the world

“AI companies will fail. We can salvage something from the wreckage”. In the Guardian, January 18th by Cory Doctorow.

The AI section of the article argues that the current boom in generative AI may resemble earlier tech bubbles: massive investment and hype are built on the promise that AI will replace large amounts of human labor, but the technology often cannot reliably do so. Instead of creating “centaurs” (humans enhanced by machines), the author argues that many workplaces are producing “reverse centaurs”—situations where humans spend their time supervising, correcting, and taking responsibility for the mistakes of imperfect AI systems. In this model, workers remain essential but become subordinate to automated tools that generate flawed output, increasing surveillance and workload rather than eliminating jobs.

The article concludes that if the speculative AI boom eventually cools, many companies built on unrealistic expectations may fail. However, useful parts of the technology could survive the crash—much like the internet infrastructure that remained after the dot-com bubble. The key challenge will be shifting away from hype-driven investment and instead developing AI systems that genuinely augment human work and create real value, rather than simply promising to replace workers or inflate tech valuations.

“Will AI take your job? This chart in an economic study by Anthropic may give you a hint. But the answer is complicated.” In Fortune, March 10th.

The article highlights a key disconnect between AI’s theoretical capability and its actual use in the economy today. According to the economic study it cites, jobs involving areas like computing and mathematics are about 94% exposed to AI, meaning the technology could potentially perform many of those tasks. However, in reality, only around one-third of those tasks are currently being automated, suggesting that adoption is still far behind capability. The main takeaway is that while AI is powerful, companies are moving more cautiously—due to costs, reliability issues, integration challenges, and the continued need for human oversight.

The broader conclusion is that AI’s impact on jobs is likely to be gradual and uneven rather than immediate and disruptive. Even in highly exposed professions, workers are not being fully replaced; instead, AI is being used selectively to assist with certain tasks. This creates a more nuanced outcome: some roles may shrink or change, but widespread job loss has not yet materialized. In other words, the technology is advancing faster than its real-world deployment, which suggests that the biggest labor-market effects of AI are still ahead, not already here.

*The italicized summaries above were generated by Chat GPT and lightly edited by me.

By the time AI models and agents are as integrated as much into companies’ workflows as Microsoft Office and Enterprise Systems are today, not only will a lot of time gone by, but there will have been a tremendous amount of change at all levels of the economy. Like past technological cycles, for some people, companies, and industries, this will be highly disruptive, for others, they may barely notice that the world has changed.

Since ~1990, the technology sector of the world’s stock market has continued to grow in both size and profits at a much larger rate than more traditional industries. Even though many traditional companies have profited from the implementation of technology, it seems an outsized share of the profits are ending up in a highly concentrated group of companies. However, not all technology companies that show promise or are pioneers will survive, many will go bankrupt, merge or be acquired; and like most large industries, in the end, AI services will likely be dominated by a handful of companies at most.

While today OpenAI, Anthropic, and Space X / xAI will be fighting to raise hundreds of billions from public markets; I would say that Google is already well ahead all three of them in the race and today is the best positioned to profit from their AI investments. Will the other three companies all exist ten years from now? Probably not? Are their current valuations likely to create or destroy value for initial investors over the next decade? It is hard to tell.

One thing is for certain; I know that being a stock picker is hard (even Warren Buffet will tell you he was more lucky than good at picking winners); as index investors, we will probably end up owning all of them in some proportion as they come to market. Now, a more interesting question is what if all three of these newly minted companies end up in the major indexes (and some of our index funds), and are not yet profitable (as they are not today); how concerned should we be? There will be a lot of hurdles to get into the S&P 500, but much lower bars to get into some index funds, so parsing out the risk will be possible. We are likely to see a number of new indexes, new funds, and perhaps even a re-constitution of the S&P 500 at some point. It is too early to tell.

Besides impacts for us as investors, we are also going to see impacts in many other ways. I am sure many jobs will change, many new tools will evolve, and some companies will profit immensely from finding new ways to do work more efficiently, others may go out of business; this is all part of the normal business cycle. Technology, and especially software has been a big deflationary force, I expect that will come about again, once all of the investment in AI starts to mature and move into higher levels of adaptation and implementation. Despite inflation staying persistent, especially in the US, and the shocks that come from wars in and around major oil and gas producing areas, these are likely to be short-lived.

For all of us who are knowledge workers and more than a couple of years away from retirement, learning to be a user of AI is going to be as important a skill for many as using MS Office or using the internet. Eventually it will feel “normal” but there will be a learning curve. For the superstars of any profession, to achieve or maintain this status, many will find new and more efficient ways to work with the help of AI. While AI implementation will pose many threats, it will also pose many opportunities:

“The best way to predict the future is to invent it.” — Alan Kay, computer scientist

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