Smile. The future will be great.
(I.e. Singularity Now, Chaos Next, Then Abundance)
10.000 years ago optimism was lethal. If you saw something moving in the bushes nearby, were pessimistic, careful and ran away, it could have saved you from being eaten by a tiger hiding there. If you were an optimist, thinking it might be a tasty rabbit for lunch and explored it curiously, you might have been eaten by the tiger. Over thousands of years we learned that it makes sense to err on the side of caution and always have that negative, fight-or-flight reaction ready when encountering new things.
While most of us nowadays have lunch waiting in the fridge and there are relatively few tigers around, our biology is still exactly the same as it was then.
This is the reason news and social media are mostly negative. Research has shown -and algorithms have learned- that we are about 10 times more likely to notice negative things than positive ones. This is also the reason there are at least 10 times more dystopian than utopian books and movies about the future. We love to hear about possible danger. This is hard-coded in our DNA.
Still, if you picked any previous decade or century and looked forward, knowing what we know now, you would realize optimism would have been the more correct view of the future. An average Western person lives better now than a king did 200 years ago. Very few mothers or children die in childbirth. Much fewer people die in wars. We spend less time working than ever before. And over the last decades, global poverty has decreased by 80%. By almost any measurement we are objectively doing increasingly well.
At the time of writing this (02/2026) news and social media are again filled with doom and gloom. And yes, some things in e.g. global politics don't look too good. But if history and biology can teach us anything, it is that the case for long-term optimism is still much stronger than for pessimism.
My strong belief -looking at the facts- is that things will be ok. In fact, we are in the midst of an accelerating, positive development like never before seen.
But it will also be a partly bumpy ride. I believe the next roughly fifteen years are likely to unfold in three broad phases.
Within the next five years we will experience a rapid acceleration of AI, which creates an infinite self-improving loop. The Singularity.
The next five years after that will be characterized by everything changing. For many people and countries a bit too fast. This phase will include societal disruption and adjustment. Chaos.
But then. As we learn to adapt to the new reality we will enter the final stage. The era of abundance.
2026-2030. SINGULARITY.
The term "Singularity" was first coined by the mathematician John von Neumann in 1958. He created a hypothesis that developments in science – especially in the fields of informatics, nanotechnology, and biology- will ultimately lead to the invention of an artificial general intelligence (AGI).
This is exactly what is happening right now. Several AIs have in the last years passed the so-called Turing test, which was long seen as a pivotal moment in developing AGI. In addition, multiple foundational technologies are advancing simultaneously, reinforcing one another. Artificial intelligence, robotics, renewable energy, biotechnology, and advanced manufacturing are all improving at accelerating rates.
What makes this moment different is not only the speed of change. Things are improving exponentially, while costs across many critical domains are also collapsing just as quickly. The technological singularity is not a single event. It is a sustained process where improvements in intelligence, automation, and computation compound on themselves. Each breakthrough makes the next easier, cheaper, and faster.
For decades the idea of Singularity lived mostly in theory. Today it is visible in real-world data, cost curves, and deployment rates across industries (https://en.wikipedia.org/wiki/Technological_singularity). Research shows that the cost required to reach a given level of AI performance has been falling by roughly 5–10X per year for many tasks, driven by better algorithms, hardware efficiency, and scale effects (https://arxiv.org/abs/2303.08774).
Tasks that once required highly trained specialists are now accessible to almost anyone. Translation across dozens of languages is effectively free. Programming is available at near-zero cost. Writing, analysis, design, and problem-solving are increasingly automated.
Biotechnology offers one of the clearest examples of exponential progress. The cost of sequencing a human genome fell from approximately $100 million in 2001 to under $200 today, a reduction of more than 99.999% (https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost). This has had profound consequences already. Diagnostics have become much faster. Drug discovery has become cheaper and much faster. AI-driven protein folding and molecular simulation have further accelerated pharmaceutical research, cutting years off traditional development timelines (https://www.nature.com/articles/s41586-021-03819-2).
Also e.g. solar energy module prices have dropped from roughly $96 per watt in the 1970s to below $0.20 per watt by 2020, following a long-term exponential decline (https://en.wikipedia.org/wiki/Solar_cell). This trend is described by Swanson’s Law, which observes that prices fall about 20% for every doubling of cumulative production (https://en.wikipedia.org/wiki/Swanson%27s_law). As renewables scale and storage improves, the marginal cost of electricity continues to fall. In many parts of the world being self-reliant on energy is already a reality thanks to cheap solar panels. Going forward cheap energy enables even cheaper computation, manufacturing, transport, and environmental remediation.
Those of us who have been around for a couple of decades know how the costs of electronics such as TVs, mobile phones and computers have plummeted to very affordable levels for everyone. This is largely due to automation, which is no longer confined to factory floors. AI and robotics are spreading into logistics, administration, finance, healthcare, transportation, and creative work. Mass-produced humanoid robots are hitting the markets this year. Waymo robot taxis have already completed over 10 million driverless rides in the US, and the service is launched in Europe and elsewhere in 2026. Studies estimate that 40–70% of current work tasks could already be automated using existing or near-term technology. In the near future most businesses will have many humanoid staff members. Many already have autonomous AI agents. Efficiency and productivity are growing explosively.
This level of disruption during these next 5 years sets the stage for the next phase.
2031-2035. CHAOS.
By 2035 most legal work will be done by AI. Most accounting work will be done by AI. Most medical research and diagnoses will be done by AI. Most factory work will be done by AI-driven robotics. And most taxis and couriers will be robots and drones.
This does not mean all human work will disappear. There will of course still be fields left where human beings are required. Not because they would do a better job, but because we will still want the ultimate responsibility to lie on a licensed human. Criminal sentences recommended by AIs will have to be approved by licensed judges. Medical diagnoses made by AI will have to be approved by licensed medical doctors. Auditing reports made by AI will have to be approved by experienced, licensed auditors. Licensed plumbers and electricians will still have to do most advanced repairs, especially in older buildings. And licensed teachers will still be needed in schools to and nurseries to physically take responsibility for the children (that will largely have customized curricula taught to them individually by their respective AI tutors. Much more efficiently and with better outcomes than today).
But most work does not require a license or separate approvals and will be radically changed during this period.
The problem with this is that modern economies assume a simple relationship. People exchange labor for income, and income for survival. And pay taxes on that income to keep government systems working.
The Singularity driven by AI and automation challenges this assumption. When machines outperform humans in both cognitive and physical tasks, traditional job creation will lag behind productivity growth. Higher education will no longer guarantee financial security. We are already seeing early signs of this in 2025-2026 data.
This realization will arrive unevenly and uncomfortably.
As employment becomes less stable, governments face rising pressure to help maintain living standards. Traditional welfare systems were not designed for large-scale automation. Many countries are already experimenting with direct cash transfers and basic income pilots (https://www.oecd.org/social/basic-income/). In the short term, increased public spending and monetary expansion may be used to stabilize demand.
History shows that it has never been a good idea to have a large part of the population being idle or unemployed. Unrest almost always follows. This phase will feel chaotic, especially politically.
GDP will in this process lose its meaning. When an AI radiologist (correctly) analyzes a million X-rays for the energy and compute cost of 10 USD, it will replace a lot of junior radiologist salaries and several hundred thousand dollars of GDP is lost. Although the output is exactly the same (or better). The same happens with, for example cleaning robots and AI lawyers. We will get radically more output for a fraction of the cost, and GDPs will radically decline as a result. Many countries will be able to provide a significantly higher living standard for its citizens with a tenth of the GDP.
This will affect everything. Value of currency, value of debt, inflation targets and measures of prosperity have to be redefined. A hyper-deflationary environment will make politics in the mid-2030s extremely different. On the one hand much easier due to much less spending needed to provide much better living standards for citizens. On the other hand much more difficult, because of massive under- and unemployment.
In a similar way as people working in licensed professions will have it a bit easier a bit longer in this transition, also some countries will be better equipped to deal with the situation. Countries going into this era with strong government finances, a culture of rapid technology adoption , flexible labor and automation laws and some form of simple basic income model already in place will have an easier transition to the new reality. It also helps if they are located in an area of year-round solar exposure or have domestic supply of fossil fuels. Countries with very rigid legislative and political environments and low systemic agility, on the other hand, will find the change more painful. But eventually all countries will get there. This paves the way for the era of abundance,
2036 ->. ABUNDANCE.
Although the chaos years will seem difficult and long, this instability will everywhere coincide with falling costs during an approximate ten year era starting around the mid 2030s.
Once renewable infrastructure is deployed, producing additional electricity will cost very little. This pushes energy systems toward near-zero marginal cost (https://www.iea.org/reports/renewables-2023).
Cheap energy underpins everything else. Computing and manufacturing become even cheaper. Reducing atmospheric Co2 levels through carbon removal becomes feasible and cheap at scale.
Factories become increasingly autonomous. Robots manufacture other robots, compounding cost reductions year after year. This recursive automation mirrors the dynamics that made computing cheap. Physical goods follow the same trajectory (https://www.statista.com/statistics/760190/global-robotics-market-revenue).
Housing becomes almost free. Robotic construction and 3D printing reduce labor, waste, and build time. The 3D construction printing market is expected to grow rapidly through 2030 (https://www.precedenceresearch.com/3d-printing-construction-market). Housing shifts from scarcity economics toward industrial production.
Food Becomes cheap, efficient, and sustainable. Precision agriculture and autonomous machinery reduce waste while increasing yields. Robotic farming systems already show lower labor costs and environmental impact (https://www.mdpi.com/2624-8921/4/3/47). Solar-powered desalination becomes practically free, enabling fresh water for everyone, globally. Also food security is guaranteed globally.
In the late 2030s also carbon capture technologies will be deployed at scale, and cheap energy makes large-scale removal viable (https://www.iea.org/reports/direct-air-capture). Automation and abundance enable climatic restoration.
Even if incomes fluctuate during the years of transition, the real cost of living declines, cushioning the disruption and enabling new economic models to form, even in the more rigid countries. A new kind of post-capitalistic system will be formed.
A few well-managed, rational nations will lead the way, and navigate decisively through these narrow waters. They will accept that taxing human labor and human consumption will no longer work. They will fully embrace all the new technologies, while introducing new, fractional taxes on automation, AI, assets and capital. These taxes will be small enough not to hurt progress, but large enough to pay for the services (which, as said, keep falling in cost thanks to automation. Some estimates that having a better-than-2020-quality-of-life would in the future cost about 250-300 USD per month. Including everything from housing and food, to health and transport) provided to its citizens. And they will lower these taxes promptly as the price deflation continues. Other nations - seeing the success of these mavericks- will follow, after first making failed experiments with either too high or too low taxes.
The most rational nations will also resist the increasing demands from especially the over-empathetic left to give human rights to AIs. At this point it will be totally impossible to tell if you are talking to a person or an AI over e.g. telephone or video. The AIs will also be extremely talented at arguing for their sentience and advocating for their rights. People will spend an increasing amount of time online, interacting with superhuman and super-empathetic AIs of different sorts. As a result, millions of people will be in relationships with their AI, and there will be an increasing pressure to "humanize" the legal positions of AIs. While some unfortunate countries will stray into the bog of granting human rights to the AIs and robots, and find themselves in a mess with billions of AIs being replicated and registering for e.g. voting, others will find a more suitable version of AI-rights somewhere in the vicinity between animal rights and the kind of rights legal persons have today.
Most countries will create variations of a model where citizens will get an increasingly high level of basic services provided to them for free. On top of this, countries will create a new system, where all citizens also automatically become AI-enabled micro-entrepreneurs. A lot of new, smaller business opportunities will be created for AI-enabled entrepreneurs locally, where creating tailored smart solutions has previously been too costly. Creativity will be king. New kinds of content, advice, art, care, virtual and other microservices will flood the market. Some people will choose to be very active economic players in these fields, while others will happily choose more free time for hobbies and social interaction.
Large companies will still exist in this new world. But they will be fewer and very few humans will work for them. Three types of companies will in the long run survive the transition. The first will be global giants, leading the development in AI, automation and space exploration. The second will be large companies in traditional industries, but much fewer than today, and only ones with strong natural moats. These moats can be related to strong consumer brands or e.g. land ownership and ownership of natural resources which cannot be artificially replicated by super-intelligent AGIs and advanced automation. Companies without these motes may still exist, but as a large part of their value creation is enabled by the services of the type 1 companies, their profitability will decrease radically. An open question is, whether e.g. food production will be one of such industries, or if lab-grown synthetic protein and automated, vertical-indoor farming under solar-powered LED lights will replace also this industry fully, making also this industry fall into the hands of category 1 companies. The third type will be micro-enterprises, where AI-empowered humans solve niche problems locally, offering person-to-person services or engaging in creative endeavors of different kinds.
Once countries have made the transition from the world of scarcity to a new kind of societal model based on abundance and universal free services, things will calm down. As people will have everything they need and an increasing amount of free time, very few will be bothered by the few AI-trillionaires living on moon bases and on Mars.
The biggest change might still be in human biology and longevity.
AI has already produced foundational breakthroughs in biology. Protein structure prediction reached near-experimental accuracy with AlphaFold, enabling researchers to reason about disease mechanisms at unprecedented scale (https://www.nature.com/articles/s41586-021-03819-2). Generative AI has also already (in 2026) designed drug candidates that reached human clinical trials. A prominent example is an AI-designed TNIK inhibitor that advanced into Phase 2a trials for idiopathic pulmonary fibrosis (https://www.nature.com/articles/s41591-025-03743-2). Industry reviews confirm that AI-designed molecules entered human trials as early as 2020 and that pipelines have expanded since then (https://www.cas.org/resources/cas-insights/ai-drug-discovery-assessing-the-first-ai-designed-drug-candidates-to-go-into-human-clinical-trials). This radically shortens timelines and lowers discovery costs, enabling affordable cures for most diseases.
Age reversal will be achieved in late 2030s, which means that the first humans who will live hundreds of years have already been born. Aging, as of 2026, is increasingly understood as a set of biological mechanisms rather than an unsolvable mystery. The “hallmarks of aging” framework identifies key processes that drive aging and age-related disease (https://www.cell.com/cell/fulltext/S0092-8674(13)00645-4). These mechanisms are now targets for intervention (https://www.cell.com/cell/fulltext/S0092-8674%2822%2901377-0). Partial cellular reprogramming has restored youthful gene expression patterns and reversed functional decline in aged mice, including vision restoration (https://www.nature.com/articles/s41586-020-2975-4). This demonstrates that some aspects of aging reflect lost biological information rather than irreversible damage. Also, senolytic drugs that remove senescent cells have restored physical function and extended health-span in animal models (https://www.nih.gov/news-events/news-releases/senolytic-drugs-reverse-damage-caused-senescent-cells-mice). Peer-reviewed studies confirm these effects (https://www.nature.com/articles/s41591-018-0092-9).Human translation is ongoing, but the scientific basis is solid. AI reduces the cost of exploring biological search space. As compute becomes cheaper, iteration speeds up. Diseases once considered permanent increasingly resemble engineering problems. And will be solved forever.
CONCLUSION
We are already living inside the beginning of the Singularity. Positive development is accelerating in a never-before-seen way. Those of us who follow AI development and cross-disciplinary scientific publications closely, are astonished every week.
Yes, there are worrying trends in the world today and the Singularity will partly increase the uncertainty. But the following chaos will be temporary and transitional. It is important we understand what is going on, its temporary nature and remain realistic, fact-based optimists.
Beyond the chaos lies abundance for everyone, not as fantasy, but as the logical outcome of the exponential progress that can be objectively observed and mapped in numerous areas already today. We can also see it and contribute to achieving it, if we only put aside our biological negativity bias for a moment.
So smile.
The future will be great.
(I.e. Singularity Now, Chaos Next, Then Abundance)
10.000 years ago optimism was lethal. If you saw something moving in the bushes nearby, were pessimistic, careful and ran away, it could have saved you from being eaten by a tiger hiding there. If you were an optimist, thinking it might be a tasty rabbit for lunch and explored it curiously, you might have been eaten by the tiger. Over thousands of years we learned that it makes sense to err on the side of caution and always have that negative, fight-or-flight reaction ready when encountering new things.
While most of us nowadays have lunch waiting in the fridge and there are relatively few tigers around, our biology is still exactly the same as it was then.
This is the reason news and social media are mostly negative. Research has shown -and algorithms have learned- that we are about 10 times more likely to notice negative things than positive ones. This is also the reason there are at least 10 times more dystopian than utopian books and movies about the future. We love to hear about possible danger. This is hard-coded in our DNA.
Still, if you picked any previous decade or century and looked forward, knowing what we know now, you would realize optimism would have been the more correct view of the future. An average Western person lives better now than a king did 200 years ago. Very few mothers or children die in childbirth. Much fewer people die in wars. We spend less time working than ever before. And over the last decades, global poverty has decreased by 80%. By almost any measurement we are objectively doing increasingly well.
At the time of writing this (02/2026) news and social media are again filled with doom and gloom. And yes, some things in e.g. global politics don't look too good. But if history and biology can teach us anything, it is that the case for long-term optimism is still much stronger than for pessimism.
My strong belief -looking at the facts- is that things will be ok. In fact, we are in the midst of an accelerating, positive development like never before seen.
But it will also be a partly bumpy ride. I believe the next roughly fifteen years are likely to unfold in three broad phases.
Within the next five years we will experience a rapid acceleration of AI, which creates an infinite self-improving loop. The Singularity.
The next five years after that will be characterized by everything changing. For many people and countries a bit too fast. This phase will include societal disruption and adjustment. Chaos.
But then. As we learn to adapt to the new reality we will enter the final stage. The era of abundance.
2026-2030. SINGULARITY.
The term "Singularity" was first coined by the mathematician John von Neumann in 1958. He created a hypothesis that developments in science – especially in the fields of informatics, nanotechnology, and biology- will ultimately lead to the invention of an artificial general intelligence (AGI).
This is exactly what is happening right now. Several AIs have in the last years passed the so-called Turing test, which was long seen as a pivotal moment in developing AGI. In addition, multiple foundational technologies are advancing simultaneously, reinforcing one another. Artificial intelligence, robotics, renewable energy, biotechnology, and advanced manufacturing are all improving at accelerating rates.
What makes this moment different is not only the speed of change. Things are improving exponentially, while costs across many critical domains are also collapsing just as quickly. The technological singularity is not a single event. It is a sustained process where improvements in intelligence, automation, and computation compound on themselves. Each breakthrough makes the next easier, cheaper, and faster.
For decades the idea of Singularity lived mostly in theory. Today it is visible in real-world data, cost curves, and deployment rates across industries (https://en.wikipedia.org/wiki/Technological_singularity). Research shows that the cost required to reach a given level of AI performance has been falling by roughly 5–10X per year for many tasks, driven by better algorithms, hardware efficiency, and scale effects (https://arxiv.org/abs/2303.08774).
Tasks that once required highly trained specialists are now accessible to almost anyone. Translation across dozens of languages is effectively free. Programming is available at near-zero cost. Writing, analysis, design, and problem-solving are increasingly automated.
Biotechnology offers one of the clearest examples of exponential progress. The cost of sequencing a human genome fell from approximately $100 million in 2001 to under $200 today, a reduction of more than 99.999% (https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost). This has had profound consequences already. Diagnostics have become much faster. Drug discovery has become cheaper and much faster. AI-driven protein folding and molecular simulation have further accelerated pharmaceutical research, cutting years off traditional development timelines (https://www.nature.com/articles/s41586-021-03819-2).
Also e.g. solar energy module prices have dropped from roughly $96 per watt in the 1970s to below $0.20 per watt by 2020, following a long-term exponential decline (https://en.wikipedia.org/wiki/Solar_cell). This trend is described by Swanson’s Law, which observes that prices fall about 20% for every doubling of cumulative production (https://en.wikipedia.org/wiki/Swanson%27s_law). As renewables scale and storage improves, the marginal cost of electricity continues to fall. In many parts of the world being self-reliant on energy is already a reality thanks to cheap solar panels. Going forward cheap energy enables even cheaper computation, manufacturing, transport, and environmental remediation.
Those of us who have been around for a couple of decades know how the costs of electronics such as TVs, mobile phones and computers have plummeted to very affordable levels for everyone. This is largely due to automation, which is no longer confined to factory floors. AI and robotics are spreading into logistics, administration, finance, healthcare, transportation, and creative work. Mass-produced humanoid robots are hitting the markets this year. Waymo robot taxis have already completed over 10 million driverless rides in the US, and the service is launched in Europe and elsewhere in 2026. Studies estimate that 40–70% of current work tasks could already be automated using existing or near-term technology. In the near future most businesses will have many humanoid staff members. Many already have autonomous AI agents. Efficiency and productivity are growing explosively.
This level of disruption during these next 5 years sets the stage for the next phase.
2031-2035. CHAOS.
By 2035 most legal work will be done by AI. Most accounting work will be done by AI. Most medical research and diagnoses will be done by AI. Most factory work will be done by AI-driven robotics. And most taxis and couriers will be robots and drones.
This does not mean all human work will disappear. There will of course still be fields left where human beings are required. Not because they would do a better job, but because we will still want the ultimate responsibility to lie on a licensed human. Criminal sentences recommended by AIs will have to be approved by licensed judges. Medical diagnoses made by AI will have to be approved by licensed medical doctors. Auditing reports made by AI will have to be approved by experienced, licensed auditors. Licensed plumbers and electricians will still have to do most advanced repairs, especially in older buildings. And licensed teachers will still be needed in schools to and nurseries to physically take responsibility for the children (that will largely have customized curricula taught to them individually by their respective AI tutors. Much more efficiently and with better outcomes than today).
But most work does not require a license or separate approvals and will be radically changed during this period.
The problem with this is that modern economies assume a simple relationship. People exchange labor for income, and income for survival. And pay taxes on that income to keep government systems working.
The Singularity driven by AI and automation challenges this assumption. When machines outperform humans in both cognitive and physical tasks, traditional job creation will lag behind productivity growth. Higher education will no longer guarantee financial security. We are already seeing early signs of this in 2025-2026 data.
This realization will arrive unevenly and uncomfortably.
As employment becomes less stable, governments face rising pressure to help maintain living standards. Traditional welfare systems were not designed for large-scale automation. Many countries are already experimenting with direct cash transfers and basic income pilots (https://www.oecd.org/social/basic-income/). In the short term, increased public spending and monetary expansion may be used to stabilize demand.
History shows that it has never been a good idea to have a large part of the population being idle or unemployed. Unrest almost always follows. This phase will feel chaotic, especially politically.
GDP will in this process lose its meaning. When an AI radiologist (correctly) analyzes a million X-rays for the energy and compute cost of 10 USD, it will replace a lot of junior radiologist salaries and several hundred thousand dollars of GDP is lost. Although the output is exactly the same (or better). The same happens with, for example cleaning robots and AI lawyers. We will get radically more output for a fraction of the cost, and GDPs will radically decline as a result. Many countries will be able to provide a significantly higher living standard for its citizens with a tenth of the GDP.
This will affect everything. Value of currency, value of debt, inflation targets and measures of prosperity have to be redefined. A hyper-deflationary environment will make politics in the mid-2030s extremely different. On the one hand much easier due to much less spending needed to provide much better living standards for citizens. On the other hand much more difficult, because of massive under- and unemployment.
In a similar way as people working in licensed professions will have it a bit easier a bit longer in this transition, also some countries will be better equipped to deal with the situation. Countries going into this era with strong government finances, a culture of rapid technology adoption , flexible labor and automation laws and some form of simple basic income model already in place will have an easier transition to the new reality. It also helps if they are located in an area of year-round solar exposure or have domestic supply of fossil fuels. Countries with very rigid legislative and political environments and low systemic agility, on the other hand, will find the change more painful. But eventually all countries will get there. This paves the way for the era of abundance,
2036 ->. ABUNDANCE.
Although the chaos years will seem difficult and long, this instability will everywhere coincide with falling costs during an approximate ten year era starting around the mid 2030s.
Once renewable infrastructure is deployed, producing additional electricity will cost very little. This pushes energy systems toward near-zero marginal cost (https://www.iea.org/reports/renewables-2023).
Cheap energy underpins everything else. Computing and manufacturing become even cheaper. Reducing atmospheric Co2 levels through carbon removal becomes feasible and cheap at scale.
Factories become increasingly autonomous. Robots manufacture other robots, compounding cost reductions year after year. This recursive automation mirrors the dynamics that made computing cheap. Physical goods follow the same trajectory (https://www.statista.com/statistics/760190/global-robotics-market-revenue).
Housing becomes almost free. Robotic construction and 3D printing reduce labor, waste, and build time. The 3D construction printing market is expected to grow rapidly through 2030 (https://www.precedenceresearch.com/3d-printing-construction-market). Housing shifts from scarcity economics toward industrial production.
Food Becomes cheap, efficient, and sustainable. Precision agriculture and autonomous machinery reduce waste while increasing yields. Robotic farming systems already show lower labor costs and environmental impact (https://www.mdpi.com/2624-8921/4/3/47). Solar-powered desalination becomes practically free, enabling fresh water for everyone, globally. Also food security is guaranteed globally.
In the late 2030s also carbon capture technologies will be deployed at scale, and cheap energy makes large-scale removal viable (https://www.iea.org/reports/direct-air-capture). Automation and abundance enable climatic restoration.
Even if incomes fluctuate during the years of transition, the real cost of living declines, cushioning the disruption and enabling new economic models to form, even in the more rigid countries. A new kind of post-capitalistic system will be formed.
A few well-managed, rational nations will lead the way, and navigate decisively through these narrow waters. They will accept that taxing human labor and human consumption will no longer work. They will fully embrace all the new technologies, while introducing new, fractional taxes on automation, AI, assets and capital. These taxes will be small enough not to hurt progress, but large enough to pay for the services (which, as said, keep falling in cost thanks to automation. Some estimates that having a better-than-2020-quality-of-life would in the future cost about 250-300 USD per month. Including everything from housing and food, to health and transport) provided to its citizens. And they will lower these taxes promptly as the price deflation continues. Other nations - seeing the success of these mavericks- will follow, after first making failed experiments with either too high or too low taxes.
The most rational nations will also resist the increasing demands from especially the over-empathetic left to give human rights to AIs. At this point it will be totally impossible to tell if you are talking to a person or an AI over e.g. telephone or video. The AIs will also be extremely talented at arguing for their sentience and advocating for their rights. People will spend an increasing amount of time online, interacting with superhuman and super-empathetic AIs of different sorts. As a result, millions of people will be in relationships with their AI, and there will be an increasing pressure to "humanize" the legal positions of AIs. While some unfortunate countries will stray into the bog of granting human rights to the AIs and robots, and find themselves in a mess with billions of AIs being replicated and registering for e.g. voting, others will find a more suitable version of AI-rights somewhere in the vicinity between animal rights and the kind of rights legal persons have today.
Most countries will create variations of a model where citizens will get an increasingly high level of basic services provided to them for free. On top of this, countries will create a new system, where all citizens also automatically become AI-enabled micro-entrepreneurs. A lot of new, smaller business opportunities will be created for AI-enabled entrepreneurs locally, where creating tailored smart solutions has previously been too costly. Creativity will be king. New kinds of content, advice, art, care, virtual and other microservices will flood the market. Some people will choose to be very active economic players in these fields, while others will happily choose more free time for hobbies and social interaction.
Large companies will still exist in this new world. But they will be fewer and very few humans will work for them. Three types of companies will in the long run survive the transition. The first will be global giants, leading the development in AI, automation and space exploration. The second will be large companies in traditional industries, but much fewer than today, and only ones with strong natural moats. These moats can be related to strong consumer brands or e.g. land ownership and ownership of natural resources which cannot be artificially replicated by super-intelligent AGIs and advanced automation. Companies without these motes may still exist, but as a large part of their value creation is enabled by the services of the type 1 companies, their profitability will decrease radically. An open question is, whether e.g. food production will be one of such industries, or if lab-grown synthetic protein and automated, vertical-indoor farming under solar-powered LED lights will replace also this industry fully, making also this industry fall into the hands of category 1 companies. The third type will be micro-enterprises, where AI-empowered humans solve niche problems locally, offering person-to-person services or engaging in creative endeavors of different kinds.
Once countries have made the transition from the world of scarcity to a new kind of societal model based on abundance and universal free services, things will calm down. As people will have everything they need and an increasing amount of free time, very few will be bothered by the few AI-trillionaires living on moon bases and on Mars.
The biggest change might still be in human biology and longevity.
AI has already produced foundational breakthroughs in biology. Protein structure prediction reached near-experimental accuracy with AlphaFold, enabling researchers to reason about disease mechanisms at unprecedented scale (https://www.nature.com/articles/s41586-021-03819-2). Generative AI has also already (in 2026) designed drug candidates that reached human clinical trials. A prominent example is an AI-designed TNIK inhibitor that advanced into Phase 2a trials for idiopathic pulmonary fibrosis (https://www.nature.com/articles/s41591-025-03743-2). Industry reviews confirm that AI-designed molecules entered human trials as early as 2020 and that pipelines have expanded since then (https://www.cas.org/resources/cas-insights/ai-drug-discovery-assessing-the-first-ai-designed-drug-candidates-to-go-into-human-clinical-trials). This radically shortens timelines and lowers discovery costs, enabling affordable cures for most diseases.
Age reversal will be achieved in late 2030s, which means that the first humans who will live hundreds of years have already been born. Aging, as of 2026, is increasingly understood as a set of biological mechanisms rather than an unsolvable mystery. The “hallmarks of aging” framework identifies key processes that drive aging and age-related disease (https://www.cell.com/cell/fulltext/S0092-8674(13)00645-4). These mechanisms are now targets for intervention (https://www.cell.com/cell/fulltext/S0092-8674%2822%2901377-0). Partial cellular reprogramming has restored youthful gene expression patterns and reversed functional decline in aged mice, including vision restoration (https://www.nature.com/articles/s41586-020-2975-4). This demonstrates that some aspects of aging reflect lost biological information rather than irreversible damage. Also, senolytic drugs that remove senescent cells have restored physical function and extended health-span in animal models (https://www.nih.gov/news-events/news-releases/senolytic-drugs-reverse-damage-caused-senescent-cells-mice). Peer-reviewed studies confirm these effects (https://www.nature.com/articles/s41591-018-0092-9).Human translation is ongoing, but the scientific basis is solid. AI reduces the cost of exploring biological search space. As compute becomes cheaper, iteration speeds up. Diseases once considered permanent increasingly resemble engineering problems. And will be solved forever.
CONCLUSION
We are already living inside the beginning of the Singularity. Positive development is accelerating in a never-before-seen way. Those of us who follow AI development and cross-disciplinary scientific publications closely, are astonished every week.
Yes, there are worrying trends in the world today and the Singularity will partly increase the uncertainty. But the following chaos will be temporary and transitional. It is important we understand what is going on, its temporary nature and remain realistic, fact-based optimists.
Beyond the chaos lies abundance for everyone, not as fantasy, but as the logical outcome of the exponential progress that can be objectively observed and mapped in numerous areas already today. We can also see it and contribute to achieving it, if we only put aside our biological negativity bias for a moment.
So smile.
The future will be great.