Anxiety grows at the elite’s conference

April 20, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on April 20th, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

Must humanity merge with AI to survive? At the TED conference, anxiety about the development is growing — and exposing a rift in the elite’s view of what lies ahead.

It smells of pine inside the Vancouver Convention Center. The TED conference is taking place in a kind of wooden amphitheatre, where a select group is already sitting at the very front — donors with their own entrance. Over 1,500 people have travelled to western Canada to listen to speakers on everything from lead poisoning to covid vaccines and relationships.

One question keeps recurring, however. And it creates a clear unease and friction among the well-heeled audience.

Should we embrace AI development fully? Or should we rather avoid it at all costs?

TED broke through on a broad front in the mid-2010s. “TED Talks” — short, directed presentations from the main stage — became their own category of video on the internet. A cultural reference point one could cite at dinner parties.

The audience is a mixture of philanthropists, researchers, activists, and tech workers. A simpler way to group them is as an elite. Influential people who, with both cultural and economic capital, shape opinion and societal development.

This elite’s view of the AI question is therefore particularly interesting. Whether educational initiatives for children in developing countries are a good thing — another recurring theme — is fairly uncontroversial. The question of self-driving cars is considerably harder, given both road safety and the jobs that will inevitably disappear as they roll out into the world.

This theme runs like a thread through the conference. TED host Chris Anderson returns to it many times during the week. “The future is a dance between humans and AI,” he says. So how will this dance unfold?

Tech entrepreneur D Scott Phoenix gives us one vision. He has previously sold an AI company to Google and has a definitive view of how things should develop. “We will merge with AI, because the alternative of being replaced is worse,” he says.

Phoenix refers to the fact that merging is the first thing we did as humanity — through our cells — and that this is a natural and inevitable continuation of that path. Either we create descendants or we become fossils. That is the choice we face.

He tells of a dinner he attended in Silicon Valley recently with other AI leaders. The participants were “names you would recognise,” he says, without going into exactly who. When asked whether the AI leaders believed there was more than a 10 percent chance that AI would kill most people on earth, many raised their hands.

That is the scenario Phoenix is weighing up against. It is therefore better to merge and bring AI development as close to humanity as possible. Because the alternative could mean the end of humanity as we know it.

The audience gasps as he speaks.

Others have a more restrained vision. Steve Huffman, CEO of the online forum Reddit, presents his company’s product as a kind of counter-movement to the automated.

“Reddit is like a city,” he explains — a place where people build relationships with each other on their own terms.

It sounds good. Like a relief for many, after Phoenix’s talk. But when Huffman receives a standing ovation, one gets the feeling that most people in the room have not spent much time on Reddit. It is certainly human, but it does not take many clicks before the rose-tinted picture takes on a different form.

Austrian founder Peter Steinberger of Open Claw is the most relaxed of all. His creation enables people to create their own AI agents that work autonomously. But it came about somewhat by accident. After testing his new AI robot in an internet forum with others, he shut down his computer and went to bed. When he woke up, the robot had started the computer itself and continued talking.

In the end, Steinberger had to pull the plug out of the wall to be sure it would stop. He laughs at the whole thing and says he does not recommend letting one’s AI robots run completely out of control.

TED host Chris Anderson steps onto the stage after the talk looking worried. He says Steinberger frightens him. How can he take this so lightly?

Steinberger smiles, wearing a blue blazer with a toy lobster — Open Claw’s mascot — tucked into the breast pocket.

“The lobster has been released,” he says, “and it won’t go back to the aquarium again.”

There is something fateful about both the presentations and the conversations around them. Have we already passed the point where AI will take over completely, or is there still time to change course?

British neuroscientist Anil Seth offers a different perspective. We may be standing at a crossroads with technology — but merging is not on the table, according to him. Overestimating AI is underestimating yourself as a human, he believes.

Seth distinguishes between intelligence and consciousness. Humans are unique in displaying high levels of both simultaneously, which makes it difficult for us to assess technological development correctly.

“We see consciousness where there is none,” says Seth, and urges resistance to anthropomorphising technology. Doing so — thinking of machines as something with consciousness — makes us psychologically vulnerable. And through that, we risk being manipulated by them.

The questions about what humanity’s role will be in an AI world are many and difficult. TED gives no clear answer and appears to have deliberately chosen speakers with very different perspectives, letting the audience make up their own minds. The mood is serious and thoughtful.

Which is why comedian George Civeris provides the most cathartic moment of the week. He says TED is “the only place that brings together people all trying to solve the world’s problems.”

We in the audience look at each other and feel satisfied. Despite these difficult questions, we are doing our best. We have flown halfway around the world to try to work out what the future might look like — and someone has seen us.

But then comes Civeris’s punchline: “and then mixes them with all those who created the problems in the first place.”

The laughter that follows is long-awaited. And a little painful.

Apple’s trump card — hidden in the phone

April 9, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on April 9th, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

While competitors spend hundreds of billions on AI, Apple sits tight. It looked like a major mistake. But the next phase of AI development could be Apple’s revenge.

In a red leather armchair on a stage sits Steve Jobs. It is 2010, the year before he passes away, and Jobs is visibly physically affected by his illness.

His sharp tongue is still very much intact, however. When journalist Walt Mossberg asks about “search company Siri,” which Apple recently acquired, Jobs cuts him off immediately: “I don’t know if I would describe Siri as a search company,” he says. “They’re in the AI space.”

Somewhere around there — sixteen years ago — began Apple’s public journey toward AI. But the road has been anything but straight. After repeated disappointments with Siri, which neither understands what you say nor can do very much, the image of Apple as an AI company has faded.

Have they missed the wave they themselves were so early to identify? It is not quite that simple.

ChatGPT, Claude, and Google Gemini have admittedly sprinted past and created exactly what Siri was supposed to become. Companies like Meta, Google, and OpenAI have invested hundreds of billions of dollars in AI data centres.

In the short term, Apple is behind — but in the long term there is an opportunity for a strategy that competitors will find very difficult to replicate. At least at the same scale that Apple has.

If we begin with the shortcomings, they are obvious even internally at Apple. A licensing agreement with Google from January speaks clearly: Apple currently has no AI model of comparable quality to the competition. Siri is now to use Google Gemini going forward. Apple has had to reorganise its AI work after its previous head suddenly left prematurely.

Many Apple fans consider it a smart strategy to work with partnerships rather than participate in a very expensive race with other tech giants. What argues against it is all the work that has been ongoing with Siri over all these years. It is the inability to produce a good result that led to the partnership with Google — not a decision to not try. And the resources are there. Apple sits on around 1,350 billion kronor in cash and securities.

Looking further ahead, however, one can begin to glimpse something exciting — and entirely unique to Apple. Should AI development move in a certain direction, Apple could catch up despite its sluggishness.

In simplified terms, AI development can be divided into two parts — “training” and “inference.”

Training is the training of the AI model itself, a process that requires enormous computing power. When Anthropic and Meta release new models, the price tag for training them is counted in tens of billions of kronor. The enormous data centres filled with Nvidia’s GPU chips are used primarily for this type of training.

Inference is when the model is used to give you as a user an answer. It is drawing conclusions from the information in the model so that it can tailor responses to what you have asked. This does not require anywhere near the same type of computing power as training. And even more importantly in this context — in many cases it can be done directly on your phone, or your iPhone.

As AI models become more efficient, Apple’s own chips are emerging as a strong strategic advantage. In the over one billion iPhones in use today there is hardware that Apple does not sell to anyone else. With newer generations of AI models, one can imagine them being trained separately but then run on the user’s own device. Apple Silicon — their own chip — could then answer questions for the user without the information ever needing to leave the phone. It is private, fast — and everything you need is already in your phone.

Looking at Apple’s competitors, none of them has this capability. Meta has no mobile phones at all, and Google’s Pixel phones have a very low market share globally. OpenAI is working on various hardware products but nothing has been released yet. And unlike building data centres, it is next to impossible to roll out a new mobile phone that achieves the same coverage as the iPhone has. It does not solve everything when it comes to AI development, but it is an enormous advantage in distribution.

Apple’s journey toward AI seemed to begin with Siri in 2010. But the truly unique difference only started to become visible ten years later, with the launch of the Apple Silicon chips. Here Apple has something competitors find very difficult to match: a technology they developed themselves, and which is perfectly suited to AI.

It is a long game that Apple is playing. They will also need to get their own AI development in order over time. The need for AI training is not going to diminish. But the trump card is already in place.

You have it in your pocket — inside your iPhone.

Crisis at OpenAI — now they’re changing strategy

April 2, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on April 2nd, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

With ChatGPT, OpenAI launched the biggest tech trend in a decade. It looked unbeatable. But now CEO Sam Altman’s operation is shaking. What is happening inside the world’s leading AI company?

It is an unusual gathering of powerful figures standing in a row in the Roosevelt Room of the White House.

It is January 2025 and Donald Trump takes to the podium. Beside him stand two of the world’s most influential tech billionaires — SoftBank’s Masayoshi Son and Oracle’s Larry Ellison.

Furthest out stands the youngest and least wealthy of them all: Sam Altman, CEO of OpenAI. He looks a little uncomfortable in a dark suit and brown shoes.

But Altman has travelled from Silicon Valley and dressed up for a reason.

Together with the other men, he is about to present Stargate — a gigantic AI investment in the US, costing up to 500 billion dollars.

The scale was compared to the Manhattan Project, through which the first atomic bomb was developed in the 1940s.

A year later, it is clear that nothing of that calibre will materialise.

The men in suits could not cooperate and the Stargate project has stagnated. Instead of a joint investment in data centres, new partners have had to step in and build. OpenAI — which needs enormous amounts of computing power for its AI services — will end up renting it from others rather than building its own.

The reason for this is simple. OpenAI cannot afford it. And according to The Information, they cannot borrow the money either.

This, along with several recently abandoned projects, points to a new strategy for the AI industry’s market leader.

A radical shift appears to be under way.

Stargate is not the only project to have been forced into major changes quickly. In December last year, Disney invested one billion dollars in OpenAI and announced a collaboration involving the animation giant’s many characters. Through OpenAI’s video app Sora, users could make their own Disney videos — legally and with copyright secured.

Just 103 days later, the fun was over. On 24 March, OpenAI announced that it was shutting down Sora and several other video creation services.

Disney said it “respected” the decision to focus elsewhere, but it clearly did not look good. The agreement between them could have set the standard for AI and the film industry in Hollywood. Instead it became an embarrassing belly-flop.

There are two reasons for this rapid reversal — and both relate to money in different ways.

The first is about focus. According to the Wall Street Journal, OpenAI’s COO Fidji Simo told her staff they did not have time to be distracted by “side projects.” Admittedly, no one called Sora a side project when it was launched. But in contrast to what Simo wants the company to focus on, one can understand the categorisation.

OpenAI is now to concentrate on “productivity” — and enterprise productivity in particular. Companies that can pay their way.

The second reason behind Sora’s closure is pure cost-cutting. Creating video with AI is extraordinarily expensive and requires very large amounts of computing capacity. OpenAI can put that to better use elsewhere. Relative to how little money video as a category brings in, it is clear that Sora cost substantially more than it was worth.

Sora is not alone in being shut down. That list is long.

Together with e-commerce company Shopify, they were going to launch the ability to buy products directly within ChatGPT. That project has also been scrapped.

And the “erotic chatbot” that was promised has been on ice for a couple of days.

Many are also waiting for the hardware product that OpenAI is to release with Apple’s former chief designer, Jony Ive. According to information from American courts, it has now been pushed back to 2027.

Given the above, one might ask a simple but in this context unusual question. Is OpenAI short of money?

What makes it unusual is that OpenAI has raised around 168 billion dollars in various forms of financing. One might think that should be enough for most things.

As a comparison, that is more than the entire Swedish government budget for a year.

Despite this, there is much to suggest that the money is beginning to run out — or at least that the costs visible on the horizon will exceed revenues for a long time to come. The company’s own forecast points to losses of around 14 billion dollars — just this year. In total, OpenAI estimates it will take around 111 billion dollars — approximately 1,000 billion kronor — before it turns profitable in 2030.

Anyone who has ever seen, or made, such a forecast knows that at best it is an educated guess. Nobody knows what the real number might be.

But the strangest thing of all is how the company found itself in this pressured situation, and what it now plans to do differently.

To understand that, we need to go back a couple of years.

The icon showed a white “N” against a teal gradient. Double-click it and the entire world’s internet opened up for home users. The “N” stood for “Netscape Navigator” — the popular web browser of the day that let users surf the web. Something that was new at the time, in the mid-1990s.

In this world, Netscape quickly became dominant. The browser was released in 1996 and just two years later it was reported to have 38 million users. That made it the world’s most popular PC software ever, at that point in time.

With a market share of around 89 percent, Netscape looked unbeatable. Like OpenAI, they were overwhelmingly the largest — and were introducing a new paradigm of technology to the public.

The success would prove short-lived.

Despite the initial triumph, it took just two years before Microsoft’s browser, Internet Explorer, overtook it. That same year, 1998, Netscape had 452 million dollars in revenues but made a loss of 159 million dollars.

Compared with today’s AI figures, it almost sounds quaint. Just 159 million dollars in losses in a year?

But at the time, the loss resembled a black hole. The following year Netscape was acquired by AOL, and the decline just continued. By 2002 the market share was just above three percent.

The market’s overwhelming leader — those who introduced the concept of the “web browser” to the public — had fallen.

Netscape was consigned to the history books.

Even if OpenAI is not exactly like Netscape, there is a lesson to be learned.

Being first to market is a good start — but not necessarily more than just that. What is usually called “first mover advantage” is often fairly short-lived.

Even when it comes to entirely new categories of software, market shares can shift quickly. Those who were around early may also remember AltaVista — the undisputed biggest and best search engine of its day. Then Google came along. Everyone knows how that ended.

It seems as though OpenAI is beginning to grasp this. It is therefore more important than ever that the many billions they have raised in investment last longer.

They need to hold out against competitors and a changing market.

Standing in the way of OpenAI’s world domination are two siblings who were previously employed by Sam Altman: Dario and Daniela Amodei, founders of the AI company Anthropic and the chatbot Claude.

With its beige app and somewhat more talkative style, Claude has quickly become many people’s favourite AI tool. They have been around since 2021, when the Amodei siblings left OpenAI along with several colleagues.

Anthropic is now growing substantially at OpenAI’s expense. But this is due more to OpenAI making poor decisions than to Anthropic suddenly becoming so much better.

Take the recent Pentagon incident. When Anthropic refused to let the US Department of Defense use Claude for all conceivable purposes, it became a major conflict. The military threatened to classify the company as a “supply chain risk,” which would have pressured many others to stop working with them. Anthropic in turn sued the Trump administration.

Into the vacuum that emerged stepped Sam Altman and OpenAI. From the outside it appeared as though they agreed to everything Anthropic had opposed, though the exact details of what transpired are not known. Nonetheless, the signal value was enormous — had Altman’s sense of responsibility for AI safety disappeared? Many users accustomed to AI products have been able to switch easily to Claude.

Another reason for Anthropic’s sudden success relates to the focus that OpenAI COO Fidji Simo called for above. While OpenAI invested in AI-generated video and a long series of different projects, Anthropic focused on a specific segment of the market: enterprises — and those working with programming in particular.

The products Claude Code and Cowork have quickly become extraordinarily popular. Programmers have gone from writing code themselves to instructing and verifying the code that AI systems build.

Anthropic’s strategy is smart. In this customer segment one finds those who are most likely the fastest — and most eager — to use AI services.

The success was immediate. OpenAI has a similar product, Codex, with which one can programme. But it has been somewhat lost among all the other initiatives under way.

When COO Simo talks about focus, this is what she means.

OpenAI needs to become more like Anthropic.

It is not always easy being the market leader. The defectors at Anthropic are showing the way to enterprises. Google, after a weak start, has caught up considerably and has well-stocked coffers. The queue of companies wanting access to the attractive AI market is long.

Can OpenAI adapt in time? An IPO looms — and with it a new funding lifeline.

But Netscape was listed on the stock exchange too, back in the 1990s.

And you know what happened to them.

The game is rigged — and that’s the point

March 31, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on March 31st, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

Is it geopolitical analysis or gambling? Prediction markets have suddenly taken on a prominent role in geopolitics. But now questions are being raised about corruption — and military risks.

“Will American troops land in Iran before… 31 March?”

The question is not merely geopolitical — it is also the basis for bets worth around 200 million kronor. On the American prediction market Polymarket, bettors placed the probability of a “yes” at 29 percent about a week ago. By Monday it was down to 6 percent.

By making assessments about world affairs, war has been turned into a game. On prediction markets, however, no odds are set — instead participants bet against each other. Get your forecast right and you can win a lot of money. And if you have information nobody else has, you are almost guaranteed to do so.

Prediction markets originally came from the American DARPA — a kind of research unit funded by the US government. One of the first was called PAM, Policy Analysis Market. Its purpose was to try to forecast political developments in the Middle East, and to provide financial incentives to make the forecasts more reliable. It was a simple model: get it right and you get money.

PAM barely made it out of the starting blocks before the controversies began. In 2003 a Democratic senator called the idea “a federal gaming parlour on atrocities and terrorism” and added that the entire concept was “grotesque.” The project was shut down shortly after.

Over the past few years, a new generation of prediction markets has blossomed again. The vast majority of the activity is not political, however — it is pure sports betting. By using a legal loophole they have been able to circumvent the gambling legislation that prohibits many forms of wagering in most American states. They are now considered a type of futures contract — financial instruments — rather than a form of gambling. Not everyone agrees. The state of Nevada recently sued prediction market Kalshi in an attempt to ban them. But it is legal in the US, for the moment at least.

People betting money on a football match might sound harmless enough. But there are two major challenges with prediction markets.

The first is that it is difficult to mix two different purposes on the same market. On a stock market, there are strict rules against insider trading. Otherwise it can feel unfair that some participants in the market have access to more and better information than everyone else.

If you set aside the money, however — and simply want to arrive at as accurate a forecast about the future as possible — then insider trading is actually beneficial. You want those with unique information to share it, because that makes the forecast better. The money is only there as an incentive to bring it to light.

It goes without saying that these two motives are in conflict with each other.

Either you want to get to the truth — or you want a market with equal conditions for all.

This brings us to the second challenge. If people with secret information about, for example, military operations can make money from it — are the security of those involved not put at risk?

Already now, unusual forecasts with high betting volumes stand out. This can come to influence the actual matter at hand. If an enemy sees that an attack is expected to occur within a certain time period, it can prepare for it. The forecast was correct — but it influenced how the outcome unfolded, which can threaten the safety of those involved.

When geopolitics is mixed with gambling, a new type of problem is created. Much of the money being staked is in cryptocurrency, which makes it difficult to identify the people behind the bets. Interest has grown to such a degree that states, exchanges, and other societal institutions now follow prediction markets on a regular basis. And by betting large sums on unexpected questions, one can through this influence public opinion. It looks like an insider — but it can also be an influence operation, with prediction markets as the method.

When CNN analysed one particular player, they found that he had earned over 1 million dollars by correctly predicting how Israeli and American military operations would be conducted. The anonymous player won 93 percent of the time. The prediction market arrived at the truth. But the military was left with an enormous security problem — and a market that pays millions for valuable and confidential information to leak out.

We have transformed security policy into a kind of unregulated, anonymous stock exchange. That it would lead to problems is something everyone should have been able to foresee — even without a prediction market doing the work.

Social media is facing a crisis

March 25, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on March 25th, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

Meta and YouTube caused a young girl to suffer anxiety and depression. An American jury has now established this in a landmark case. The verdict opens the door to an avalanche of similar cases — and could tear down the tech giants’ unique legal protection.

“Section 230 of the Communications Decency Act of 1996.”

This brief piece of American legislation, just 26 words long, is what has legally protected social media companies all these years.

Responsibility for all content uploaded — images, texts, videos — is considered under it to belong to the person who uploaded it. Services like Instagram, YouTube, and TikTok have been regarded as neutral platforms.

But that came to an end on Wednesday evening when an American jury — drawing on other laws as a basis — showed that they could be found liable for harm nonetheless.

The method is legally creative. Both Donald Trump and his predecessors have said they want to repeal “Section 230.” None of them have managed to do so, and a completely different approach was therefore needed to test the responsibility that social media companies bear for young people’s wellbeing.

What was done in this pilot case is to advance the thesis that it is the design of the services that has harmed young people — not the content. It is, for example, the recommendation algorithms and the ability to scroll endlessly that caused the harm. In this way, prosecutors were able to circumvent the deadlock that has existed when it comes to holding social media companies accountable.

The main figure in the case is a young woman now aged 20. Of the many thousands of cases making similar claims, hers was considered among the stronger, and she was therefore a good candidate to test first. What follows is therefore an avalanche of further cases in which predominantly young people will attempt to obtain redress for harm they believe they have suffered through their use of social media.

The fine of 3 million dollars — around 28 million kronor — is a rounding error for both Meta and YouTube, who are found liable. Going forward, there may be a larger class action, or a near-endless number of smaller cases with individuals making similar claims. But above all, the symbolic value of the loss is enormous. Many have drawn the comparison that this resembles the cases brought against tobacco companies in the 1990s. These proved expensive for those companies, but they also marked a turning point in public perception. Tobacco stopped being accepted in the same way after that.

It is entirely possible that the same shift in attitudes will happen here.

Parents in particular have long been worried about the impact they perceive social media to have had on their children. Research on this has been slow and insufficient, and some of the strongest evidence of harm has, ironically, come from inside companies like Meta. Internal documents and studies have shown how certain features could be addictive for young users. And yet nothing definitive has happened — beyond individual bans for young people in certain countries, such as in Australia.

After Wednesday’s verdict, these legislative proposals are likely to accelerate sharply around the world. The American ruling does not technically affect how other countries need to act, but in practice it is likely that it will do so anyway. It shifts from having been an uncertainty to a decided case in which these social media companies have been proven to have harmed a young woman. Which politicians will be able to allow this to continue unimpeded in their respective countries?

Companies like Meta, YouTube, and TikTok now face a crisis. They have numerous emerging bans for young people around the world, an enormous number of legal cases of a similar nature, and a potentially shifting opinion on how to regard these companies’ social responsibilities.

From having been a self-evident part of many young people’s daily lives, parents at least are likely to use the verdict as grounds for trying to restrict it. Some advertisers may come to want to avoid being associated with these platforms.

Earlier this week Meta also lost another case in the American state of New Mexico, for failing to protect children from abuse. Despite what are likely to be endless appeals before final verdicts are reached, the case involving the 20-year-old woman marks a clear turning point. It may be that social media has reached its peak — and is now beginning a downward journey.

Not everyone will delete TikTok from their phone immediately, but a new era is beginning. Social media can harm young people. It will now be difficult for anyone to ignore this.

Can she stop the flight to the US?

March 19, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on March 19th, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

The EU is reaching out to the startup world with its new proposal “EU Inc.” Regulations for starting companies are to be simplified. But it misses the region’s most pressing problem.

It is the day before Christmas Eve 2025. In Berlin, a startup is trying to finalise an investment.

There is just one mandatory step left. For the process to be valid, the company’s management must sit and read all the documents aloud to a notary. The whole spectacle takes over five hours.

This is the reality in large parts of the EU. An excessively slow and bureaucratic system that complicates something other countries handle with ease. After persistent lobbying from the startup world, this understanding is beginning to sink in, even in Brussels.

The new proposal “EU Inc” is one example of this.

The European Commission hopes it will make it easier for new European companies to be started, and ideally for them to remain in the region too. Among other things, it will be possible to start a company within 48 hours, and it must not cost more than 100 euros to do so. Processes are to be digitised, and it will be possible to register a company across the whole EU through a single interface rather than going through each individual EU member state. It is to be in place by 2028.

This might not sound like a revolution to anyone who has never tried. One can go so far as to say it is strange that it does not already work this way. Given the example of the German notary, there are clearly improvements to be made. In Sweden, however, these problems are minimal. Starting and running a company digitally is very smooth. The Swedish Companies Registration Office and the Swedish Tax Agency have made otherwise quite complicated processes simple. Those who have gone furthest of all are Estonia, where you can even become a digital citizen.

While the regulatory simplifications of EU Inc are welcomed by many startups, one should not exaggerate their impact. The primary problem the EU has is not about starting companies — it is the opposite. Where do these companies end up when they eventually become large and successful? And what happens along the way?

Because the real problems start early, but long after a company’s registration.

It is about access to capital in the early stages of a company’s life. It is easiest if entrepreneurs seek money from someone in the same city, but if that is not available, one must look further afield. Despite the home continent being large, European companies often find it easier to obtain money from the other side of the Atlantic than from nearby. And if you want American venture capital, investors prefer it if you have a company registered in the US. The standard is to do so in the state of Delaware, which has the most predictable rules for all involved. Swedish Lovable is registered there, for example.

Then comes the next problem. What happens when startups become established companies.

This became clear when the EU’s legislative package the Digital Services Act (DSA) was presented and was supposed to hold the tech giants to account. Which European companies were large enough to be considered tech giants that should be regulated?

Zalando, Booking.com, and a handful of Cyprus-registered pornography sites. There are no large European tech companies of the same calibre as Meta, Google, and Amazon.

First and foremost, American companies are happy to acquire promising European companies early. Google’s AI lab DeepMind, founded in the UK, was acquired back in 2014, long before the current AI boom began. Swedish-Estonian Skype was bought by Microsoft. Finnish Wolt was bought by DoorDash. The list is long.

The second reason is that there is no common European stock exchange to list on. Spotify and Klarna are both on the New York Stock Exchange, despite having Swedish roots. The alternative for these companies might have been London, or Frankfurt if one is extremely generous. But realistically, neither was genuinely in the running.

Every individual stock exchange in the EU is too small and lacks the liquidity needed for a good investment climate suited to international companies. In the Nordic region alone there are five different stock exchanges. That is far too fragmented to function well. And so companies seek out the US instead, where they can access capital from investors around the world.

The EU simplifying regulations for startups is good news for entrepreneurs. But it sidesteps the biggest problems entirely. The startup world’s gravitational pull runs strongly westward — at every stage of the journey.

American venture capital leads to American company registrations. Which are easily acquired by large American companies. Or alternatively listed on American stock exchanges.

Until those challenges are addressed, the European startup scene is likely to remain much as it is. EU Inc makes European Commission President Ursula von der Leyen look bold and strong. But if you ask the wrong question, you get the wrong answer. And that is precisely what has happened with EU Inc.

A collapse in confidence — and it could get worse

March 16, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on March 16th, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

Kinnevik’s CEO is dismissed on the spot, a short-seller report sends the share price tumbling — and a newly installed board member is to conduct an “impartial evaluation” of the business. The crisis at the venerable investment company continues. But why did it become acute over the weekend?

There are really only three ways to leave as CEO of a major listed company. You get a new job, you retire — or you get fired.

That is why Kinnevik’s plan in November 2025 seemed very strange. Georgi Ganev, who had been CEO of Kinnevik for eight years, was to resign. But at the same time he was to remain in post until a new CEO was appointed.

That interim period came to a definitive end over the weekend. Ganev left with immediate effect. After Kinnevik’s dismal performance over many years, no one is surprised — except perhaps by the timing. What was it that meant the plan presented four months ago suddenly had to be redrawn?

The press release Kinnevik issued on Sunday states that a newly appointed board member, Rubin Ritter, is taking over as acting CEO. He is to conduct a “thorough and impartial evaluation of our team, our culture, our ways of working and our portfolio, as well as implementing changes where necessary so that my permanent successor can get started immediately.”

Of course that is not how it will turn out — unless Rubin himself takes over as permanent CEO.

Running an investment company is not an administrative role. The job consists of setting a strategy, building a team, and making good investments. The idea that a new CEO would walk in to a fully laid table and simply do what Rubin has decided is therefore not particularly plausible. A CEO will demand to put their own stamp on the company. Shareholders should reasonably agree with this.

The talk of an “impartial evaluation” therefore smells of something else. What is it that requires evaluation?

The short-seller firm Ningi Research has a list of their own suggestions as to what it might involve. When they presented their critical view of the company last week, the already depressed share price fell 17 percent. Ningi Research pointed to, among other things, favourable transactions conducted with parties they considered to be related. Kinnevik denied the claims.

It is not in itself unusual for activists like Ningi Research to swing with a sledgehammer to achieve an effect. But that the effect would be so powerful was likely a surprise even to them. The majority of what Ningi Research wrote was already known from before. One might consider the content remarkable — but it was not new.

The share price reaction — minus 17 percent in a single day — therefore says something much bigger than a short-seller report containing old news. It says that confidence in Kinnevik’s business is at rock bottom. If it takes no more than a couple of paragraphs to erase a fifth of one of Sweden’s most venerable investment companies, that is a crisis. A major crisis.

That is why Georgi Ganev is leaving. But the above is something many people — including myself — have written several times before. It was true in November when Kinnevik announced his departure, it is true now — and it was true long before Cristina Stenbeck decided to take back the reins and make changes. Why did it suddenly become acute?

One might have expected an explanation for this from Ganev himself. No such explanation was forthcoming, however, as he made no statement in the weekend’s press release.

Finding a new CEO is now priority one, two, and three for Kinnevik’s board. And it is urgent. Having an experienced business leader like Rubin Ritter take over is a stable temporary solution. For many years he ran one of Kinnevik’s most recently successful holdings, the e-commerce company Zalando. The relationship and trust with Stenbeck have been built since then.

Being CEO of an investment company is, however, something entirely different from running a fast-growing e-commerce company — even an exceptional one like Zalando.

And above all — being CEO of Kinnevik specifically is something else entirely.

There is a heritage, a culture, and an anchoring among shareholders on the Stockholm Stock Exchange that places the company under a spotlight that its competitors do not receive. Despite those competitors often having performed substantially better than Kinnevik over many years.

From the outside, it looks as though Rubin is to ensure that the short-sellers are not right. And to clear out any irregularities. But the most important question cannot be answered until the next permanent CEO is in place: what does Kinnevik want to be?

Until the board, management, and shareholders understand and accept that answer, the crisis risks only deepening.

The threat to Lovable: their own partner

March 13, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on March 13th, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

Billions are flowing into the Swedish AI successes Lovable and Legora. Everything seems to be pointing upward. But major risks are now emerging — and they do not come from the competition, but from a considerably closer and more sensitive direction.

In the Apple world, it is called being “sherlocked.”

The name comes from the search service “Sherlock,” whose new version Apple launched in 2002. In doing so, the privately developed search tool “Watson” — which had been created precisely as a complement to Sherlock — was rendered completely pointless.

Apple had suddenly replicated everything Watson did.

The phenomenon keeps happening. In recent days it emerged that an American company plans to spend 26 billion dollars over the next five years building new AI models. Despite the scale of the investment, it seems to have gone somewhat under the radar.

So who is this player trying to challenge giants like OpenAI and Anthropic?

It is Nvidia. The company that has supplied chips to all the world’s AI giants may now be about to compete with them.

Having to fight against one’s own partner is something many companies know well — including in Sweden.

Last year, part of Swedish Truecaller’s service was sherlocked when Apple launched a way to filter out calls from unknown numbers. Since Apple owns the hardware, they can easily see which functions are popular, and from that assess whether it is worth doing the same thing themselves.

It is a brutal asymmetry. Truecaller needs Apple to reach all iPhone users. Apple does not need Truecaller at all.

It is with these glasses on that one should read the good news from the Swedish AI companies Lovable and Legora.

Lovable reports that it has grown its revenues to 400 million dollars per year, and Legora is raising new billions in venture capital at a valuation of around 51 billion kronor. They have an enormous tailwind. Legora’s CEO Max Junestrand stated that they had not yet managed to spend the venture capital from their previous funding round, but that it was a good moment to continue building their cash reserve. Fair enough. Helping lawyers become faster and better with AI is a large market that may well require a great deal of money.

Junestrand is most likely focused primarily on beating Harvey — the American equivalent of Legora. They are even better financed and are operating on home turf in the biggest market in the US. Both are trying to be first to sell themselves to law firms as lawyers’ best AI companion. But could there be a considerably larger threat much closer to home?

Lovable is an even clearer example. They help customers build digital projects of various kinds. It is called “vibe coding.” It sounds good and is presented rather like an entirely new behaviour — and a virgin market. Lovable is at the forefront of this trend.

But it is not quite that simple. At both Legora and Lovable, it is AI models from other companies that do the really substantial work in the background. Lovable’s customers often use Anthropic’s AI model Claude, which in turn uses Nvidia’s chips. The value chain is therefore complex. And it becomes more precarious when players early in the chain decide to make a move.

The AI model Claude has a mode called Claude Cowork. There, just like with Lovable, you can build technical projects without needing to understand the code yourself. And if you want help with a legal agreement, you can go directly to Claude or ChatGPT and ask for yourself.

Claude and the Swedish AI companies are of course not identical products. But the similarities are many, for understandable reasons. At the core, it is the same service performing a large part of the work.

The challenge for AI companies that have built a large part of their business on top of others’ services is therefore to build a sufficiently good service — but one different enough from what their own suppliers might themselves be inclined to build.

And to ensure that those same suppliers do not simply switch off the functionality one depends on. Anthropic — the owner of Claude — switched off the possibility for competitor xAI to use their service.

It might sound unlikely that this could happen to Lovable and Legora — but it is not unthinkable.

As the Apple examples show, things can move fast when your best partner pivots to become your worst competitor. Right now, Anthropic and OpenAI are experiencing exactly this themselves with their own supplier Nvidia. The method is therefore well established.

What sounds like an implausible side project from an important partner can quickly become existential. And the list of companies that have disappeared in this way is long — and the last name on it has not yet been written.

The Swedish AI companies — with all their new billions — would do well to keep this in mind.

The gap reveals the stock market’s secret

March 5, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on March 5th, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

How are tech companies really performing on the stock market? SvD’s review shows that someone who invested 100,000 kronor a year ago could today have 91,000 kronor more — or less. And it all comes down to a single question.

The Magnificent 7 is the group of tech companies that has been talked about most on the stock market in recent years. Borrowing its name from a classic western film, these seven tech giants have enjoyed a very strong run on the stock market for several years.

But the Magnificent 7 is not the only part of the tech market that has been performing well. A new SvD review shows that another category has had a substantially better return over the past year.

By comparing different segments of listed tech companies, SvD has established what has developed well — and less well — over the past year.

What emerges is a crocodile gap, where the graphs for the different segments separate so dramatically that they resemble those reptiles. Simply put, one curve points downward and the other upward.

What is the difference between these tech companies?

It is very simple. If you invested in hardware — chips and semiconductors — things have gone extraordinarily well. If you invested in software, you have instead lost a great deal of money. The Magnificent 7, which consists of a combination of hardware and software companies, sits somewhere in the middle.

For our hardware segment, we have selected the ten largest American companies that produce chips and semiconductors. These are familiar names — Nvidia, of course, but also companies like Marvell Technology, Intel, and Broadcom. Together they have risen around 68 percent over the past year.

One might think it is Nvidia pulling the entire segment upward, but that is not the case. We have equally weighted all the stocks so that size does not distort the comparison. There are plenty of individual success stories beyond Nvidia too, such as AMD (+102 percent) or Micron Technology (+355 percent). NXP Semiconductors has, however, had a tougher period, rising just under four percent over the year.

The reason for the hardware boom over the past year is AI. A stronger tailwind for a company producing chips is hard to imagine. The use of AI services drives demand for data centres, and data centres in turn must be filled with hardware.

On the software side, we have looked at the Bessemer Cloud Index, which consists of 64 companies. Over the past year it has fallen around 22 percent — nearly a fifth of its value. Companies like the HR firm Workday, the security company Okta, and the document signing service Docusign have all had weak years. And despite the company C3.ai perhaps having the most topical stock ticker on the market — “$AI” — it has fallen more than 60 percent.

Ironically, the reason software has performed so poorly is likely the same reason hardware has succeeded. It is about AI. On the Bessemer Cloud Index one finds many companies that sell services by subscription — so-called SaaS companies, which stands for “software-as-a-service.”

The fear that these companies will face compressed margins because of AI has been considerable over the year. Some have gone so far as to call it the “SaaSocalypse.” The idea is that companies can easily build their own services with the help of AI, which then leads to price pressure and lost revenues for the SaaS companies.

Finally, there is the Magnificent 7. In any other context, their performance would still look very strong. Over the year they have risen almost 30 percent on the stock market. And this from an extraordinarily high starting point. All seven — Nvidia, Apple, Alphabet (Google), Microsoft, Amazon, Meta, and Tesla — are valued at over 1,000 billion dollars. Nvidia is the largest, valued at almost 4,500 billion dollars.

In summary, someone who invested 100,000 kronor in tech stocks a year ago has experienced very different outcomes depending on their choice.

If you chose the Magnificent 7, you would have 129,000 kronor today.

If you chose the chip companies, the equivalent figure is a full 169,000 kronor.

And if you chose the worst in the tech class — software companies — you would have only 78,000 kronor left.

Stock prices were taken on 3 March and have been rounded for clarity. All companies within each segment are equally weighted, indexed at 100 one year prior.

The incident that makes the AI giants tremble

March 3, 2026
by Björn Jeffery
SvD Näringsliv

This analysis was first published in SvD Näringsliv, in Swedish, on March 3rd, 2026. This piece was translated from Swedish by Claude. Some phrasing may differ from a human translation.

The Gulf states’ billions have become a financial safety net for AI giants like OpenAI, Anthropic, and Nvidia. Now the conflict in Iran is shaking the stability on which these investments rest. If the money freezes, the effects could be brutal.

On Sunday, an unusual update appeared from AWS, Amazon’s cloud services. Ordinarily, entries in the “service status” category are brief, dry notices about when a company’s services are temporarily not functioning as they should.

This time it was something else entirely.

An AWS data centre in the United Arab Emirates “was struck by an object that hit the data centre, creating sparks and fire.” The object in question was a drone from Iran.

A single fire can be resolved. But as a signal about conditions in the region — and its enormous AI investments — many are likely to be worried.

One of the most stable financiers of the AI boom is now suddenly trembling.

In the spring of 2025, Donald Trump and the Saudi Crown Prince Mohammed bin Salman stood at the front of a large group photograph. It was an investor meeting in Riyadh where the US and Saudi Arabia met to do business.

Standing in the row behind Trump was one of the main protagonists: Jensen Huang, CEO of Nvidia. He was responsible for one of the really big deals. In a first consignment, 18,000 Nvidia chips were shipped to Saudi Arabia to launch a new, enormous data centre. Hundreds of thousands more chips will follow over the next five years in a deal estimated to be worth over 180 billion kronor.

The region’s AI ambitions extend substantially further — and wider — than that, however.

The Abu Dhabi fund MGX is a co-owner of both OpenAI and xAI as well as Anthropic. Together with Blackrock, they bought the American data centre company Aligned Data Centers for around 365 billion kronor. MGX also has connections to European AI ventures, being part of a consortium that will invest at least 280 billion kronor in building data centres in France.

The corresponding funds in Qatar and Saudi Arabia have also invested hundreds of billions of kronor in total across both data centres and individual companies. Elon Musk’s xAI announced that it received money from Saudi Arabia as recently as a couple of weeks ago. The list of all AI-related commitments could be made very long indeed.

Through investments, acquisitions, and partnerships, the Gulf states have become the global AI industry’s financial safety net. The question many will now be asking is how reliable that safety net will be in the period ahead. Can one trust that the money that has been promised will materialise? What does appetite for investment look like going forward?

A large portion of the sums mentioned above have not yet been paid — they are statements of intent and plans stretching over many years. This means the risks are deferred to the future, which creates uncertainty.

Neither capital nor ambitions need to change for disorder to emerge. A temporary moment of doubt is enough to create a problem. Something as simple as project delays strikes directly at companies that may have made themselves dependent on them.

Worse still — it can take a long time to normalise. A prolonged conflict in the region would, for obvious reasons, also be able to shift focus away from long-term AI investments towards more pressing matters closer to home.

The dependence on Gulf state money appears as a significant vulnerability for the tech industry. The many data centres to be built require billions upon billions to get off the ground. If financing for these is delayed — or, in the worst case, cancelled — a cascade of consequences could quickly follow.

Supply chains break down, permits need to be reapplied for, questions of liability need to be resolved. There are many companies whose valuations — and promises to the market — depend on these projects. Were the financing to fall through, many companies could find themselves in acute financial crisis. Protracted projects delay both the construction of data centres and the AI companies seeking to purchase their capacity. It could become very expensive, very quickly.

It began with a data centre that was fired upon. But it rapidly became a wake-up call for the entire industry.