companies

Germany wanted to see if working four days a week was efficient. 70% of companies think so

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The four-day work week started in Germany as an experiment to search for the maximum productivity of companies without having an impact on an exhausted workforce and without the ability to reconcile family life. Two years after the start of this test, the data confirms that for the companies that participated it was not a simple test, but rather it has materialized in a change in the way of working that many companies have decided to consolidate. Now the monitoring report prepared by researchers from the University of Münster together with the consulting firm 4 Day Week Global. It analyzes what happened after the pilot test that began in 2024 and what subsequent effects it has had. The main conclusion is that around 70% of the companies that participated in that test continue to apply some model of reduction of working hours a year later. A known formula and a varied sample. The original four-day week project in Germany was built around to the 100-80-100 model: 100% of salary, 80% of time and 100% of productivity. This model of reduction of working hours is the same one that was carried out in Valencia in 2023, Portugal either United Kingdom. In the initial phase, 45 companies from different sectors participated, dedicated to manufacturing, insurance, technology, media, commerce or education. Furthermore, to be as representative as possible of the German industrial fabric, companies of different sizes were chosen: from micro-businesses with 1 to 9 employees, to large companies with more than 250 employees. The first data already gave clues. Researchers have been collecting data from participating companies and their employees since day one. A few months after starting the test, the companies were delighted with the results, to the point that in preliminary results73% said they would not return to the traditional five-day week. The new report provides the perspective that time gives and whether that initial impetus has been consolidated. Two years after the start of the test, seven out of ten companies that participated in the test not only maintain the four-day workdaybut they have integrated it into their normal operation. More than four days: flexible reduction of working time. One of the most interesting findings from the monitoring is that the four-day workweek model has evolved and every organization has implemented it adapting it to your needs. Not all companies have opted for a Monday to Thursday work week. Around 22% of the participating companies have adapted the initial scheme towards more flexible formulas: reduction of annual hours, alternate weeks or internal adjustments according to workload. The report itself speaks less of a “four-day week” and more of “reduction of work time“. The label matters less than the redesign of the work day and the elimination of superfluous tasks, fewer unnecessary meetings and greater autonomy of the teams. No impact on profits or productivity. In business terms, the German test has been a success since, despite having maintained 80% of the initial day, there have been no drops in either the level of profits or in productivity or slightly improved with respect to the starting point. That is, they have managed to do the same thing in less time. What it did have a strong impact on was the well-being of employees, where 90% reported improvements in the balance between personal and professional life. As a result of this improvement, employees reported feeling less stress and greater commitment to the company. 38% of companies indicated that sick leave and absenteeism of their employees had been reduced, while 56% claimed to have detected no changes. Lights and shadows in the reduction of working hours. Progress was also observed in job satisfaction and in the perception of the company as an attractive place to work. The study indicates that 87% of companies detected improvements in talent retention. For their part, 75% claimed that their companies now had a greater capacity to attract talent in selection processes. This, in a scenario of labor shortagerepresents a competitive advantage. However, as happened in other tests of the four-day work week, not all companies have followed the same evolution. About 30% stopped applying the initial scheme or returned to the traditional five-day week. The main reasons were operational, difficulties in coordinate with your clientswork peaks that are difficult to absorb or inflexible internal structures. In Xataka | Employees in Spain clear up doubts: working fewer days is better than working fewer hours, according to a survey In Xataka | Spain already has its first municipality with a four-day work week. It is not in Madrid or Barcelona, ​​but in a corner of Cádiz Image | Unsplash (Gonzalo Leon Jasin, Josue Isai Ramos Figueroa)

Anthropic just accused DeepSeek and other Chinese companies of “distilling” Claude

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For months we have talked about the race between the United States and China to dominate artificial intelligence as if it were only a question of who trains the most powerful model or launches the next version first. But the pulse begins to move to another, more delicate area: that of the rules of the game. When one laboratory accuses another of extracting capabilities from its system to accelerate its own development, the discussion goes beyond the technical. That’s exactly what Anthropic just did by denounce “distillation” campaigns against his model Claude. The complaint. In a text published this Monday, the company claims to have detected “industrial-scale campaigns” aimed at extracting Claude’s capabilities. According to their version, the activities attributed to DeepSeekMoonshot and MiniMax reportedly involved more than 16 million queries, question and answer interactions, and were channeled through approximately 24,000 fraudulent accounts, in violation of their terms of service and regional access restrictions. The race and the suspicion. The announcement by the firm led by Darío Amodei occurs in a context of growing tension around the progress of Chinese AI. Let us remember that DeepSeek altered the Silicon Valley landscape a year ago with the launch of R1, a competitive model that was presented as Developed at a fraction of the cost of American alternatives. The impact was immediate on the markets and revived the political debate in Washington about the technological advantage over China. Distilling is not always cheating. Anthropic itself recognizes that distillation is a common technique in the sector. It consists, in simple terms, of training a less capable model using the responses generated by a more powerful one, something that large laboratories use to create smaller, cheaper versions of their own systems. The problem, according to the company, appears when this practice is used to “acquire powerful capabilities from other laboratories in a fraction of the time and at a fraction of the cost” that developing them independently would entail. In that case, distillation would cease to be an internal optimization and would become, always according to Anthropic, a way of taking advantage of the work of others. Recognizable pattern. The three laboratories would have used fraudulent accounts and proxy services to access Claude on a large scale while trying to avoid detection systems. The company details infrastructures, what it calls “hydra cluster”, extensive networks of accounts that distribute traffic between its API and third-party cloud platforms, so that when one account was blocked, another took its place. Anthropic maintains that what differentiated these activities from normal use was not an isolated query, but rather the massive and coordinated repetition of requests aimed at extracting very specific capabilities from the model. Three campaigns. Although Anthropic presents the campaigns as part of the same dynamic, it distinguishes relevant nuances. DeepSeek would have focused its more than 150,000 queries on extracting reasoning capabilities and generating safe alternatives to politically sensitive questions. Moonshot, with more than 3.4 million queries, would have been oriented towards the development of agents capable of using tools and manipulating computing environments. MiniMax would concentrate the largest volume, more than 13 million queries, and according to Anthropic’s account, it reacted in a matter of hours to the launch of a new system, redirecting its traffic to try to extract capabilities from its most recent system. A geopolitical issue. The company states that illicitly distilled models may lose safeguards that seek to prevent state or non-state actors from using AI for purposes such as the development of biological weapons or disinformation campaigns. It also argues that distillation undermines export controls by allowing foreign laboratories to close the gap in other ways, while at the same time recognizing that executing these large-scale extractions requires access to advanced chips, thus reinforcing the logic of restricting their availability while, at the same time, remembering that the risk would grow if these capabilities end up being integrated into military, intelligence or surveillance systems. Images | Xataka with Nano Banana Pro In Xataka | Seedance is the greatest brutality we have seen generating video. And it has an uncomfortable message: it has surpassed Sora and Veo without NVIDIA chips

Companies are not just letting go of their youngest workers. They are making them CEO

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The business fabric in the US is experiencing one of its most turbulent periods. Not only because of the coming to power of Donald Trump and his upstart tariff policiesbut because of the challenge in management and governance models that poses to AI. OK to what was published by The Wall Street Journalthe US is experiencing a generational change at the head of the main listed companies. In 2025 alone, one in nine CEOs at the 1,500 largest companies in the S&P 1500 will be replaced, the highest rate since records began in 2010. The demands of AI they are retiring the CEOs more experienced. Relay record at the top. According to data revealed by a study from the consulting firm Spencer Stuart, 168 people debuted as CEO in large listed companies. In more than 80% of these appointments, the new managers lacked previous experience leading companies of that category, although 60% of those appointments were promotions. Furthermore, two-thirds of these incorporations had also not served on boards of directors before. That is to say, its greatest value It was not his experience, but his youth. The trend continues strongly during the first two months of 2026. Top-tier companies such as Walmart, Procter & Gamble, Lululemon, Disney, PayPal and HP have made changes in his highest executive position. This pace marks a great experiment in leadership by large companies in the face of unstable markets, where the pressure to obtain immediate results accelerates the departures of veterans. Younger and younger leaders. The average age of new CEOs dropped to 54 years in 2025, which is almost two years less than the record in 2024, thus confirming that this is a trend that has been occurring for some years. Although only 3% of managers in large companies are under 40 years old, 64% are between 50 and 59 years old, and only 12% are over 60 years old. Some examples are found in recent replacements like disneyin which Josh D’Amaro, 55, took the replacement of Bob Iger 75 years old. This replacement reflects a commitment to fresh talent, but with a deep knowledge of the companies they are going to lead, but without experience in decision-making. The life cycle of a CEO. Spencer Stuart analysts found that CEOs of large companies have “a useful lifespan” at the helm. During the first year in office, the new CEO begins the “honeymoon effect” and his companies outperform the S&P 500 by 10% on average. However, in the second year of office, 73% experience a drop in returns of an average of 21%. Between the third and fifth years at the helm, a reinvention of leadership occurs, which precedes a stagnation between the sixth and ninth years. Beginning in the tenth year, stable leadership is established. The majority cannot taste that stability since, after the third year, 25% have already left the position. 50% do not reach the sixth year as CEO. The average duration of active CEOs is 7.1 years, and 86% of departures are voluntary and agreed upon with the board of directors. Only 9% of CEO changes in the S&P 500 group of companies have been forced removals. It should be noted that only 16% of new appointments to senior management positions they have been womenwhich represents a bittersweet historical record. In Xataka | The average salary of Ibex 35 managers has grown by 172% in two decades: the purchasing power of its employees, not so much Image | Unsplash (Bruce Mars)

China is clear about who should lead the advances of its best AI and robotics companies: Generation Z

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Those who now enter the labor market find themselves with a rival that is difficult to beat: they have no agreement or need for rest or fulfillment. In addition, it does the tasks of junior profiles quite well: artificial intelligence is limiting the landing of Generation Z in the offices. in the United States, we have seen it in the UK and also in the Big Four that make up the Madrid skyline. Replacing those who start working with AI has been revealed as the West’s formula to boost productivity… from the point of view of the bosses. If you have to fight with her and validate her, not so much anymore. But it is by no means the only way, nor does it happen to everyone. In fact, China is betting just the opposite: it is turning Generation Z and millennials into heads of areas as strategic as robotics or artificial intelligence itself. They are not just any young people: they are true galacticos, their best assets. Give me someone young. As collect TechAsiaa trend is emerging in China: that of hiring millennials and young people from generation Z for positions with high-level technical profiles in large AI and robotics companies. The best example is Vinces Yao Shunyu: at 28 years old he has already been at OpenAI. A couple of months ago he returned to his native China to become the chief scientist of Tencent. He now reports directly to the CEO. Shunyu’s is just the tip of the iceberg of this new organizational strategy of Chinese companies. There are other cases, such as that of Luo Jianlan, formerly of Google since a year the chief scientist of AgiBot. Or of Dong Haochief scientist at PrimeBot after earning his PhD at Imperial College. By the way, OpenAI and Meta have copied the recipe: the first with Polish Jakub Pachocki and the second, with the Chinese Zhao Shengjia. They are scientists, but they could just as well be professional footballers: none of them are over 35 years old. Why is it important. When thinking about a boss within a modern business structure of a certain size, it is inevitable that team management, meetings and bureaucracy come to mind. However, this strategy of Chinese big tech is deliberately different from what we have in the West and is based on three reasons that SMCP explains: Institutional separation of research vs. product. A chief scientist looks to the future, he does not manage human teams or budgets. Competitive advantage in a saturated market, allowing you to build your own technologies without depending on third parties. If you have the best at home, you don’t have to ask for permission or sign abroad. The top youth asset. AI is evolving by leaps and bounds and with this movement, China is ensuring that it has those who have been at ground zero of the great milestones of recent years: elite universities or laboratories of renowned institutions such as OpenAI, Google or Princeton. China is a world source of engineers. That China is a country of engineers is no secret: it is a plan that has been underway for 4o years. In fact, now he has opted to go one step further and accelerate doctorates. The Chinese labor market is already showing signs of some saturationwhich has also brought diversification, changing routes to avoid even setting foot in the university in its new bet on FP. In any case, having an army of almost six million engineering professionals gives you an advantage with AI. And it has more than enough: it has engineers to export. Without going any further, the vast majority of signings of the Meta superintelligence team from last year they are Chinese. But young engineers who stay at home have an opportunity beyond joining a leading company in the sector: leading it. Disclaimer: a chief scientist is not a CTO. It is worth remembering a difference between positions that are often confused: a chief scientist is not the director of technology. While the first profile investigates, explores and plans in the medium and long term without touching products or marketing, the second manages teams, designs architecture and meets business objectives. Confuse both profiles or mix them, as the SMCP remembers what Alibaba or Baidu did, ends up subordinating science to the urgency of the market. In any case, it is a fragile position in a company that is not clear why it is needed. In Xataka | China looks at VET: why more and more generation Z students prefer trades over university degrees In Xataka | If Spain wants to imitate China and be a “country of engineers”, this map reveals the extent to which it has a problem Cover | and Hyundai Motor Group and cottonbro studio

Spanish companies have hired again in 2026. The problem is that there is no one to hire

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Spanish companies start 2026 wanting to expand their workforce, but they face a big problem: they cannot find enough qualified candidates for your vacancies. According to the data of the ‘Labor Market Guide 2026‘ prepared by the consulting firm Hays, companies are ready to grow and hire more staff. However, the labor market has changed and professionals are already they don’t want to give up to their current jobs. Companies step up. The Hays study reflects that 81% of Spanish companies plan to increase their workforce during 2026. The economic growth trend drives the expansion objectives of Spanish companies and, to carry it out, new vacancies have been opened. This growth in job offers is especially noticeable in dynamic sectors such as technology, professional services and industry. However, the big obstacle quickly appears: there are not enough professionals with the necessary training to fill those vacancies. 93% of the companies consulted for the Hays study claim to have serious difficulties in find qualified profilesa percentage that reaches a historical record and is paralyzing many hiring plans. Talent shortage vs. little training. The lack of qualified professionals has become an insurmountable wall in the hiring processes for new vacancies. 85% of companies claim to have launched internal training programs to develop capabilities of its employees. Only 18% of participants openly admit that they are not investing enough in closing this skills gap that holds them back so much. From the employees’ side, the perception is different. Only 48% of employees are aware that training is being carried out in their company to improve their training. This disconnection between what companies promise and what workers see aggravates the situation, making it more difficult to attract and train talent. Qualified external talent is not found, but neither are resources allocated to train the talent that is already on staff. Less job rotation. Unlike what happened years ago, in 2026 professionals have prioritized stability and growth within their company, instead of jumping to another offer. This change in mentality represents a change with respect to the years 2022 and 2023 in which the labor market had high mobility and the workers they changed jobs frequently in search of better working conditions. Even so, 62% of workers feel that their salary does not reflect all the effort that they put in day by day, but that dissatisfaction is not enough to push them to movesince they value stability and personal balance more. Christopher Dottie, regional managing director of Hays for Southern and Western Europe, puts it in clear words: “companies continue to look for talent, while talent continues to look for stability.” Better salary and flexible working hours: keys to attracting talent. To break this inertia and attract available talent, 72% of companies plan salary increases in 2026, with increases of 7% in areas such as customer service, administration and finance, and 6% in the technology sector to meet salary expectations what candidates demand. Furthermore, the flexible days They are imposed as a key piece in attracting talent, although many companies still resist implementing them despite the fact that the vast majority of employees consider them essential for their well-being. In fact, this ability to adapt to demands for flexibility and offer teleworking options is what is tipping the balance. between the public and private sectors. In Xataka | The employment paradox in Spain: we have the highest unemployment in the EU and also the lowest number of job vacancies Image | Unsplash (Beatriz Cattel)

Tech companies don’t want new graduates because they believe that AI is going to annihilate them. IBM is hiring non-stop

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The business world is so terrified of AI that recent graduate hiring is in crisis. However, there is a company that is just going in the opposite direction: IBM not only has not frozen these hirings, but is tripling them. And his argument is powerful. IBM wants new graduates. “We are tripling our hiring of junior positions,” explained Nickle LaMoreaux, IBM’s top human resources officer, in a interview at Charter. In fact, he highlighted, those positions they are filling “are for software developers and for all those jobs that they tell us AI can do.” It is a surprising statement, especially considering that the market trend is just the opposite. Unemployment among recent graduates—and among young people—is at record levels in the last decade in the United States. Source: Federal Reserve Bank of New York. The problem of unemployment in Gen Z. The young people of the generation Z (Born between 1997-2012 approximately) face one of the most complex times when looking for a first job. In the United States, the unemployment rate for recent graduates is at 5.6%, the highest in the decade except for the time of the pandemic. Managers of technology companies have been warning for some time that AI is going to greatly impact work, and especially in the field of programming. Junior profiles with a new focuseither. While competitors appear to show growing interest in replacing entry-level positions with automation — 37% plan to do so according to Korn Ferry—, IBM is changing the mentality. Newbie software engineers won’t spend their days chipping away at routine code that an AI can generate. Instead, they will focus on interacting with clients and monitoring model results. AI no longer replaces the junior, but forces him to be more strategic from day one. IBM is not the only one to think this way. Although it seems that the trend towards automation is clear, IBM is not alone in this flight forward. Dropbox is doing the same, and its head of human resources, Melanie Rosenwasser, believes that Gen Z has a fundamental advantage: they are better prepared to work with AI than veterans. According to her, “it’s as if (the young people of Gen Z) were on their bikes in the Tour de France while the rest of us are on training wheels,” she said. on Bloomberg. But. IBM’s move is not without a certain cynicism. The company made this announcement a week after carry out a mass layoff to focus on growth areas. It is as if they have created a revolving door in which they have removed expensive seniority to let in cheaper youth. AI as an amplifier. Be that as it may, the CEO of IBM, Arvind Krishna, defends this strategy – logical – indicating that AI is not a substitute for human capacity, but rather an amplifier. The speech, whether we believe it or not, represents a unique commitment, especially now that companies seem to propose that they will do the same with many fewer employees. For IBM, the bet is on loyalty and knowledge cultivated from the base instead of subordinating everything to algorithms. “Developers, developers, developers!”. At the .NET event that Microsoft organized in 1999, the famous viral moment occurred in which an overexcited and sweaty Ballmer sang that from “Developers, developers, developers!” non-stop. The company was trying to attract talent again with that speech, but in reality that work had been intense years before. Hiring recent graduates worked very well for Microsoft. Steven Sinofsky, who led the development of Windows 7, told on Twitter how Microsoft became what it was thanks to its strategy of hiring recent graduates—even if they had not completed their degree. The development of Office, for example, was especially nourished by these young people, but that strategy was stopped. As Sinofsky explains, “The ‘dark times’ were accentuated by a forced pause in hiring recent graduates, and the consequences were felt five years later.” In Xataka | “They are much more daring”: Gen Z is overturning all labor consensus in its massive entry into work

The sun never set in the Spanish empire. AI is achieving that in some companies neither

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There was a time when the Spanish empire did not set the sun. Their domains ranged from the colonies in America, to Europe and Southeast Asia. In the 21st century, global technology startups are recovering that model to develop your AI-based products 24 hours a day. When a team in San Francisco is finishing its work shift, its work continues in Europe, and then moves on to Asia, ensuring that development does not stop. The “follow the sun” model is not new, but the combination of distributed remote work and the development of AI has turned it into a formula to stay ahead of the competition, without exhausting the workforce. The IBM empire in the 90s. In the 90s, IBM was an empire on which the sun did not set either. He IBM giant was one of the first to try the “follow the sun” model (Follow The Sun or FTS) with a team of five offices spread over different time slots to chain days and shorten software development times. This model is based on the concatenation of days. Each group works during its normal day. When this ends in an office, the day begins in the next time slot that collects the witness of the work of his colleagues. The process is repeated throughout the day, synchronizing the journey of the star through the sky with the different work days throughout the planet. Although in principle this model ran into some difficulties due to the poor performance of the connection networks of the time, IBM refined the process and managed to reduce projects by up to 67% by coordinating three offices in the United States, Australia and India. A model that makes sense with AI. Today, Silicon Valley has stepped on the accelerator pedal of AI and new startup founders technologies have embraced days “996” in which all hours of the day that are dedicated to product development they are few. As and as I pointed out analyst and software engineering expert Gergely Orosz, in the context of high competitiveness in the development of AI models experienced by the startup ecosystem on the west coast of the United States, more and more companies are choosing the “follow the sun” model to add normal days for teams in different countries. Thus, a model designed in Europe is tested on equipment in Asia at night and reviewed in California the next morning. The development machinery does not stop. Global clients, local attention. Likewise, the clients of these technology companies are spread all over the world, so offering a technical support service is complicated if it has to be done from a single location. According to data From Zendesk, 73% of customers switch to competitors due to bad experiences with support servicesso the distributed remote system allows the change of time slot so that the service adapts to the languages ​​and local culture of each region. The user who needs help always speaks to someone during their normal hours, no matter where they live. ​The push for AI and remote work. The rise of AI has improved the efficiency of the system at its most critical moment: shift change. This was one of the points that was most difficult for IBM managers to polish in the 90s. AI tools have helped unite shifts with chatbots that resolve doubts to employees, agents who summarize conversations with customers, prepare error reports or give solution ideas based on the context of the information that has been collected throughout the shifts, so as not to lose details when changing teams. Companies that have opted for this model in which the sun does not set highlight that products are developed faster, there are fewer unresolved cases by the support service and customers see the company as always available. Companies, especially technology companies, opted for elimination of teleworking and back to the office. However, no one said that this office should be on the same continent as that of their colleagues. A new evolution of remote work. In Xataka | Three Spanish companies tell us how they fared after implementing a work utopia: the four-day week Image | Unsplash (James Harrison)

The Government remains committed to ending telephone SPAM and is now targeting electricity companies. It’s still a shot in the air

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The Spanish Government’s crusade against SPAM calls continues. At the beginning of the week, the Ministry for the Ecological Transition and the Demographic Challenge approved the new General Regulations supply, marketing and aggregation of electrical energy. The main purpose of this is, according to the Government, to protect consumers through new measures. And one of them collides head-on with a recurring practice of marketers: SPAM calls. The measure. After the entry into force of the new regulation, telephone calls to advertise or contract services are prohibited, as long as “they have not been expressly requested by the consumer in advance or they are the one who calls the company.” It will not have immediate effect, companies will have four months to adapt to the regulations, under penalty of fines of between 600,000 and 6,000,000 euros if they fail to comply, according to the Law 24/2013, of the Electrical Sector. There is more. In addition to the prohibition of calls without express consent, the Royal Decree establishes the obligation to provide a completely free customer service number, as well as a maximum period of 15 days to respond to user claims and complaints. It is also prohibited to cut power to electro-dependent consumers on holidays and eves. Very nice, but. Although the Government has been trying to tackle the SPAM problem for more than a year, the reality is very different. According to the OCU, 99% of Spaniards (me among them, this week) continue to receive unwanted calls. Some companies continue to take advantage prior consent to send advertising communications, and others are providing their call centers with telephone numbers outside the traditional prefixes to continue with their practice, despite the fact that the law penalizes it. An endless war. The war against SPAM does not only affect Image | Xataka In Xataka | If you are tired of receiving spam calls every day, good news: MasOrange is tired too

The US spent $600 billion building its highway network. It’s less than what big tech companies are going to spend on AI this year

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The irruption of ChatGPT in the technological panorama in 2022 marked the starting signal in the AI ​​race; a race in which, year after year, large technology companies continue to increase their spending without stopping. 2026 has just begun and, far from letting it go, the big tech They have put their foot even further on the accelerator. All but one. walk or bust. We already know the planned capex for 2026 of the main technology companies, that is, what they plan to invest in capital expenditures. amazon: 200,000 million Alphabet: 175-185 billion Goal: 115-135 billion Microsoft: 140,000 million Apple: 13,000 million If we add it up taking the highest figures they have given, it is 673,000 million dollars, if we take the lowest figures it would be 643,000 million. In any case it is outrageous. In 2025 the figures were already dizzying and we are talking about an increase of around 60%. There has come a point where we have to stop and ask ourselves: How many zeros does that have? (yes twelve). Context of this madness. Here are a few comparisons to put this figure in context. It is superior to Sweden GDP in 2025 (662,000 million), that of Israel (610,000 million) and that of Singapore (574,000 million). As pointed out this user in Xexceeds what it cost to build the entire US interstate highway system (about 634,000 million) and is a quarter of the entire global military spending in a whole year. It’s like spending $1.2 million per minute for an entire year. It doesn’t make any sense. The market response. The fear of a bubble was noted after the announcements of the different companies, causing sharp falls in the stock market despite the fact that all of them have made profits (some breaking records). amazon fell 12% after announcing a capex of 200,000 millionmuch higher than forecasts Alphabet (Google) achieved record revenues, but it was not enough to convince the markets and its shares fell 10% in the following days Goal also announced record revenue and they had a 10% increase. However, days later things changed and they fell 8%. Microsoft fit the strongest blow, with a drop of 18%. Additionally, they revealed that 45% of their cloud business contracts are for OpenAI and the market does not reward dependency. Apple was the winner, with an increase of more than 7% since they announced results. The declines have been corrected in recent days and all companies have seen their value stabilize, but the message was clear: investors fear that this level of capex is far ahead of the ability of AI to generate profits in the short term. Where are they going to get the money from? It’s the big question. As stated in Financial Timescompanies must choose between reducing shareholder returns, using their cash reserves, or borrowing more money. In the case of Amazon, estimates point to a cash flow of 180 billion, Alphabet 195 billion and Meta 130 billion. The threat of free cash flow falling into negative territory is there, so we can expect them to issue more debt and stop share buybacks. Think different. Then we have Apple, which announced revenues of 144 billion in the last quarter, boosted by sales of the iPhone 17 during the Christmas campaign. Its capex is a fraction of what other companies have spent because Apple doesn’t build data centers, it outsources them. He agreement with Google to use Gemini can be interpreted as They have lost the AI ​​racebut in the context of a possible bubble it is a masterstroke: Google is the one who assumes the brutal spending on infrastructure and who is exposed to the bubble, while they benefit from their technology and see how the market rewards them for spending less. In Xataka | What have Apple and Google agreed on for the new Siri? Nobody knows because Google doesn’t even want to mention it. Image | Photo of Adam Nir in Unsplashedited

Companies are replacing junior workers with AI. Now it’s time to pay the consequences

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When artificial intelligence appeared on the horizon, the first thing we thought was that it was going to retire us. Later, he was going to retire the most senior profiles and now we know that it is just the opposite: is stopping job access to junior profiles. In the past, companies competed fiercely to attract young talent, but now Gen Z has found its great rival in AI. Beginners? No, thanks. This Revelio Labs job report reveals that entry-level hiring has fallen by 35% in the United States since 2023. And it is one of many studies: this other of job offers estimates the drop in junior offers between 11 and 20% in the last year. The phenomenon is not exclusive to the United States: in Spain these data from El Confidencial They report that the Big Four are going to reduce the hiring of people under 30 years of age by between 10 and 20%. In the UK, more of the same. AI boosts productivity… if you’re the boss. The business premise is that artificial intelligence can carry out these tasks of those people with a junior profile such as documentation, testing or writing basic code. It is not that these tasks have disappeared within the workflow, it is that they have been absorbed by higher levels in a twist of efficiency and productivity: senior profiles supervise what the AI ​​does. And if, AI screws up. To the question of how many hours of work per week does AI save you? from the consulting company Section collection in The Wall Street Journal There is a clear divergence between managers and staff: 40% of workers think that they are not saving anything because even if there is a quick response, there are errors and hallucinations. When you take into account the time spent going through everything, checking and redoing, the beads are not so round anymore: this Asana studio shows that employees spend 4.5 hours per week correcting AI work. The boomerang effect. That youth encounter yet another obstacle to having a full adult life is a real drama in terms of unemployment, but this paradigm shift in hiring is also a total threat to the stability of the technological infrastructure as we know it: The illusion of efficiency. AI chops code faster than anyone else, but that raw data is misleading because it doesn’t consider side effects like validation. Operational risk. If the AI ​​does not have human supervision at each step, it can make critical errors, serve as an example when half the internet went down for the total automation of Amazon servers. Of costs and responsibilities. If the AI ​​makes a mistake and it reaches the final chain of the process, that is, delivery to the customer, it is paid. Let them tell Deloitte, they had to reimburse the cost of a report prepared for the Australian Department of Employment and Industrial Relations because it contained hallucinations. A demographic bomb. All of the above is a toll that many companies seem willing to pay for the sake of that efficiency, but there is a devastating effect on a large scale in the medium and long term: the knowledge gap. When these senior profiles retire, there will be no one who can replace them simply because you have eliminated the training ground that is experience. The figures have spoken: between 2024 and 2032, 18.4 million professionals in the United States will retire according to this study from Georgetown University. However, only 13.8 million new workers will gain access. About to explode. Part of the work of senior profiles includes mentoring and all its intrinsic benefits: there are studies that confirm that increases motivation, promotes psychological well-being and even reduces exhaustion. In short: saturation of tasks, inability to delegate and the loss of that added bonus of teaching: there are many ingredients for the recipe for burnout. In Xataka | If AI is going to leave us without jobs, in the United Kingdom they are already seriously discussing the solution: a universal basic income In Xataka | We believed that the AI ​​talent war is about engineers and developers. Actually, it’s about plumbers and electricians.

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