Key Themes for 2026 and Beyond

2025 has been another fascinating year for anyone interested in understanding future trends. With AI in the ascendancy, data has dominated discussions. Cyber remains critical in this debate, for data have no value unless they are secured. Pressure is also growing to provide the requisite infrastructure to power our increasingly digital societies. New energy inputs take time to build, while the grid is in urgent need of upgrading. Speed matters, especially with an ageing and increasingly unhealthy population that needs support. Robots might provide part of the solution.

As in our previous compendiums, we present below a summary of how and where we see the world changing most rapidly. Please note, this review is non-exhaustive; think of it rather as a series of interlinked high-level perspectives. Our stance remains that as diverse future trends overlap and intersect, they become mutually reinforcing.

Data

• Season Seven Blog posts: #9, #10, #14, #21, #23, #36
• Relevant theme pieces: 03/11, 10/12, 10/20, 06/25
• Key statistic: Total data creation in 2020 will constitute just 1% of the amount of data expected to be created in 2030 (IDC)

“The most important thing is digitising data. If you do not have data, no amount of AI can help you in any way. Most people skip that first step”

Hamid Moghadam, CEO and Co-Founder of Prologis

The amount of data produced and consumed is showing absolutely no sign of slowing down. Growth remains exponential, as we first highlighted almost 15 years ago. Even without AI, we remain in a data deluge. For context, data creation in 2020 will represent just 1% of the amount expected to be created by 2030. Or the amount of data created in the world is expected to grow at a 28% CAGR through to 2027, per IDC. The majority of this (c90%) will be unstructured – and hence can benefit from having it parsed by AI models.

Both consumers and corporates are being deluged by data. The average Gen-Z citizen spends 109 days a year looking at their screen, or 80% of their waking hours spent consuming information, up from 40% in 1980. We see 208 advertisements per hour, more than 10 times what our parents did at that age, according to work from New York University. ChatGPT may occupy the headlines, but Google still processes over 5tr searches annually. LLMs account for just 2% of all web-based search traffic currently, says Visual Capitalist.

No general-purpose technology ever develops in a linear fashion, as we noted in our introductory essay. Data centre demand, in practical terms, is currently being driven primarily by moving workloads into cloud environments. Andy Jassy, the Chief Executive of AWS, believes that over 80% of IT workloads and data remain on-premise, creating a huge potential opportunity. Gartner – perhaps optimistically – is of the opinion that more than 70% of workloads could run in the cloud by 2028.

Less than 3% of data centre space in North America is currently unoccupied (per Prologis). Capacity is often pre-leased, even before it is built, typically for 10-15 years forward. Given demand prospects, Apollo estimates that data centre capacity and associated infrastructure will require more than $2tr of cumulative investment over the next five years. Put another way, the US will need to double its data centre capacity by 2035, while European data centres will need to grow sixfold. No surprise then that semiconductor chips are generally regarded as the third most traded commodity in the world by value (after oil and cars).

Do not forget that 2.6bn people worldwide lack reliable internet access, according to the Internation Telecoms Union. Even in America, the government says 22% of households in rural areas cannot get a decent internet connection. As more people get (properly) online, data demand will continue to head only one way. We have written elsewhere about how the falling cost of sending anything into space is driving the commercialisation of the space economy. Low earth orbiting broadband satellites can help connect the unconnected. By 2040, space could become a $1tr industry (per Morgan Stanley) with over 200 use-cases, data provision perhaps being the most obvious.

Grid infrastructure

• Season Seven Blog posts: #35, #38
• Relevant theme pieces: 05/11, 09/15, 09/22
• Key statistic: The equivalent of 3 New York Cities of power demand will need to be added to the US grid by 2030 just to meet data centre demand (McKinsey)

“Companies are searching for power… like it’s Game of Thrones”

Tony Guzzi, Chief Executive of EMCOR Group

If data centres are the new factories for the 21^st century, then their success will be defined by their access to power. The energy demands of data centres in the US are forecast to grow from 5% of total US power consumption today to more than 10% by 2030, according to McKinsey. The International Energy Agency (IEA) is of the opinion that data centre demand will require $170bn of investment in new power generation capacity over this period.

These are big figures. To provide some context, consider that total annual power demand in New York City is ~6GW. The typical power need for the largest hyperscale data centres currently operational totals around 1GW. By 2030, this is expected to reach 18GW, according to McKinsey. In other words, there is a need to add three New York Cities to the US power grid by 2030. It is hard to disagree with Duke Austin, the Chief Executive of Quanta Services, a grid infrastructure solutions provider, when he says that “the need for transmission and generation has never been more prevalent.”

Part of the explanation for why the need for new grid infrastructure is so crucial can be explained by the fact that more than 70% of grid equipment in the US is over 25 years old. Europe’s grid infrastructure is even more obsolete, averaging 45-50 years in age (data from Bloomberg and Nexans respectively). Global grid infrastructure investment reached $400bn last year, but could expand to $600bn by 2030, according to the IEA. A more optimistic assessment (by Goldman Sachs) forecasts that when investments to modernise transmission and distribution grids are coupled with the need to meet rising demand, $1.7tr of investments in the power system will be required over the coming decade.

Alternative Energy

• Season Seven Blog posts: #18
• Relevant theme pieces: 03/18, 01/20, 09/23, 04/25
• Key statistic: More than 9 in 10 renewable power projects commissioned in 2024 were less expensive than their fossil fuel equivalent (United Nations)

“Decarbonisation is the challenge of our generation”

Jean-Pascale Tricoire, Chairman of Schneider Electric

The world is predominantly powered today by oil, coal and natural gas. Together, these account for 87% of grid inputs, according to the Energy Institute. More than $18bn worth of clean energy projects have been cancelled so far this year under the Trump administration based on figures reported in the Financial Times. Might this suggest that the future for renewables is not bright? Far from it. Even beyond the logic for decarbonisation, growing energy demands need to be fulfilled.

Despite geopolitical uncertainty, the IEA reports that energy spending will reach $3.3tr this year. $2.2tr of this will go into low-carbon solutions, double what’s being invested in oil, gas and coal. In advanced economies, renewable power to fossil fuel power investment is now almost a rounding error, at a 12:1 ratio. In 2024, solar added more than twice as much new global electricity generation as any other source. In the US alone, 32GW of US utility-scale solar was installed, equivalent to 32 nuclear reactors, 53 natural gas power blocks, or 427 small modular reactors (data from Ember Analytics and First Solar respectively).

There are two main explanations for this dynamic: cost and speed to market. More than 9 in 10 renewable power projects commissioned in 2024 were less expensive than their fossil fuel equivalent. Solar was 41% cheaper on average and land wind 53% cheaper, according to the United Nations. To build a new utility-scale solar farm might take 1-2 years. The equivalent for a combined cycle gas turbine plant is 4-5 years, while a small modular nuclear reactor might take a decade to construct.

Against this background, the world is putting up a gigawatt’s worth of solar panels, roughly the same as one coal-fired plant, every 15 hours (based on a report in The New Yorker covered in Fix the News). Bloomberg New Energy calculates that global investment in new renewable energy projects hit a record $386bn in the first half of 2025, up 10% from the previous year (BNEF). Look ahead and the IEA is of the opinion that solar will become Earth’s largest energy source by 2033.

Solar has the added benefit of helping to address the challenge of climate change. Last year’s global average temperatures were 1.6°C above preindustrial levels, confirming 2024 as the hottest on record. Global temperatures are rising twice as fast as in the 1980s, creating an urgent capital reallocation opportunity. Meeting climate goals may require over $4tr in annual investment by 2030, according to the United Nations.

The good news is that it is well-accepted that 80% of carbon emissions come from energy. Therefore, if you solve energy, you solve emissions – and this is achievable via electrification and decarbonisation. A Stanford University study shows that for 145 countries, a transition to 100% wind, water, solar and storage would pay for itself within six years and create 28m new jobs. 95% of the technologies needed are already fully commercial.

AI

• Season Seven Blog posts: #1, #3, #9, #12, #14, #17, #21, #25, #29, #35, #36
• Relevant theme pieces: 04/16, 03/23
• Key statistic: 97% of senior leaders whose organisations are investing in AI say that they are seeing positive ROI from AI across business functions (EY)

“AI is going to get better with scale, and that will lead to meaningful improvements to the lives of people around the world”

Sam Altman, Chief Executive of OpenAI

No one ever said AI would be cheap. Last year’s investments in AI were equivalent to 40 times more than the sums spent on the Apollo Project and over 70 times that accounted for by the Manhattan Project (according to Google). The major US hyperscalers will spend the equivalent of 1.4% of US GDP on their AI build out plans in 2025, more than double prior year levels (based on regulatory filings). For context, over 3.5% of American GDP was spent on railroads at peak, reports Bloomberg. Jensen Huang, NVIDIA’s CEO, estimates that over $4tr may be being spent on AI infrastructure globally by 2030.

AI’s advocates justify the investments (and the supporting energy infrastructure and inputs required to power it) since they believe that it will be “the most profound shift in our lifetimes.” Within a decade “perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today” (quotes from Google’s Sundar Pachai and OpenAI’s Sam Altman respectively). For context, GPT2 in 2019 had an 80% accuracy counting to 10. GPT3 in 2020 had an 80% accuracy in summing three-digit numbers. However, GPT4 in 2023 passed the California Bar exam. Each 100-fold increase in compute currently unlocks dramatically new capabilities.

It's perhaps not surprising then that in 2024 VC firms invested $132bn in AI startups, an increase of more than half from the previous year (Pitchbook). This year’s figure will almost certainly be higher. Meanwhile, a recent LinkedIn study showed that ‘artificial intelligence engineer’ is apparently the fastest growing job role in the US, followed by ‘artificial intelligence consultant.’

In the three years since ChatGPT was launched commercially, the technology has evolved significantly, and so correspondingly, have usage and adoption. First came chatbots – or AI with conversational language. Reasoners (human-level problem solving) followed. Now, agents – or systems that can act – are becoming increasingly prevalent. Project forward and innovation will become the new normal. Think of how AI may have the potential to aid innovation, and from there do the work of an organisation.

The trend seems clear – there are practical benefits attached to adopting and embracing AI. 97% of senior leaders whose organisations are investing in AI say that they are seeing positive ROI from AI across business functions – especially in customer support and IT efficiency, according to a recent report from EY. Satya Nadella, Chief Executive of Microsoft, says 30% of the company’s code is now being written by AI. At ServiceNow, over 80% of customer service cases for clients no longer require human involvement. AI does the work instead. JP Morgan’s CEO Jamie Dimon says that his company has over 450 use-cases for AI. Even Coca Cola noted that for the first time (in 2024), its Christmas ad was created with generative AI. According to the company, “combining emerging technology with human creativity… allowed us to produce the ad faster and at a lower cost.”

When these benefits are summed, AI advocates (such as IDC) estimate that the technology could help boost the global by a cumulative $19.9tr in 2030. If so, AI-related activity could account for 3.5% of global GDP by this date, justifying the current levels of infrastructure investment. Even if this forecast may appear optimistic and AI adoption is unlikely to be linear – cost, privacy, trust and cybersecurity issues are non-trivial – have no doubt, the technology is here to stay. Its impact will only be felt more profoundly going forward.

Robotics

• Season Seven Blog posts: #5, #16, #19, #31, #35, #36
• Relevant theme pieces: 07/12, 04/17, 02/25
• Key statistic: Roughly 1 robot is deployed for every two people present in Amazon’s warehouses (Amazon)

“The next wave of AI is physical AI. AI that understands the laws of physics, AI that can work among us… the era of robotics has started”

Jensen Huang, Chief Executive and Co-Founder of NVIDIA

Historically, the fields of robotics and AI have been separate. Their convergence is driving the real robot revolution. However, even today, robotic adoption is growing. Average robot density (or the ratio of robots per 10,000 human employees) reached a record level of 162 last year, more than double the figure of seven years prior, according to the International Federation of Robots. South Korea leads the way with a ~10% robotic penetration, with China next, a ~5% (using the same framework as above).

The US, at ~3% has some catching up to do. However, Amazon can be seen as a trailblazer. As of March 2025, it had some 750,000 robots encompassing a diverse set of form factors and purposes deployed in its warehouses. This is equivalent to 1 robot for roughly every 2 employees. Globally, the robot economy is worth $78bn and could reach $165bn in value in 2035, according to BCG.

We may well be the last generation to remember life without – or before – humanoids. Have no doubt, we need humanoid robots. By mid-century, the global population of people aged 60 years and older will double, topping 2.1bn. Furthermore, the number of persons aged 80 years or older is expected to triple, reaching 426m by 2050, according to data from the World Health Organisation. 29% of the US workforce is comprised of boomers (born between 1946 and 1964) that will soon retire. Goldman Sachs estimates that there is expected to be a 4% shortage in US manufacturing labour and a 2% shortfall in global elderly care provision by 2030. Robots can fill the gap. Humanoids will not only work in factories but also care for the elderly.

There may be 650m operational humanoids by 2030, according to Citi. If so, this would dwarf the current number deployed at Amazon by a factor of more than 800. Project further out and optimists suggest a $1tr market by 2050 (based on Morgan Stanley projections). Even without humanoids, a combination of current industrial robots and better deployment of technology – including AI – should see an upsurge in automation. The Chief Strategy Officer of GXO, a logistics systems integrator, believes that “we can automate the daylight out of certain processes…[and] take human interaction to zero”.

Healthcare

• Season Seven Blog posts: #36, #37
• Relevant theme pieces: 04/12, 11/12, 10/19, 04/24, 09/25
• Key statistic: Over 50% of the world's population are managing chronic health issues (World Health Organisation)

“We’re moving from being a pharmaceutical company to a data science company that makes medicines”

Dr Vasant Naraimhan, Chief Executive of Novartis

Healthcare represents one of the most important sectors where the world will see the practical application of both robotics and AI. Visit many hospitals and you may already observe robots capable of performing minimally invasive surgery. Intuitive’s systems can be found in ~50% of US hospitals and ~10% of hospitals worldwide, with almost 11,000 installed across ~70 countries.

Last year, a surgeon started a new procedure using an Intuitive system once every ~20 seconds somewhere in the world. However, fewer than ~10% of all surgeries performed globally use robotic assistance at present. As costs fall and use-cases grow, robot surgery is set only to increase. Already, the market is worth $14bn, according to Oliver Wyman. Beyond the operating theatre, a predicted 4.5m nurse shortage by 2030 (per the United Nations) reinforces the logic for more humanoids in hospitals.

The bigger prize, however, may be how technology allows for enhanced drug discovery and – by extension – improved human healthspan. From 2012-2022, adjusting for inflation, spending on pharma R&D increased by almost half to ~$250bn, yet drug approvals remained broadly flat. Drug trials from Phase 1 to launch still take a decade, on average, and even then, only 1 in 10 succeeds. Each new drug can take up to $2bn to develop (data from Bernstein, McKinsey and Thermo Fisher respectively). AI can help.

AI could be used throughout all stages of pharmaceutical development including preliminary screening of cellular images, mapping medical histories, increasing the speed of experimentation, and boosting production efficiency. McKinsey predicts that AI could lead to a 3-5% increase in global revenue in the pharmaceuticals and medical products market, equivalent to an annual increase for the industry of over $110bn. Other research (from PWC) suggests that pharma companies utilising AI could double their operating profits by 2030. Pitchbook notes that over $3bn of VC funding went to digital AI healthcare start-ups last year.

Project forward and many in the industry believe that the human body is just another piece of hardware to be hacked, optimised and upgraded. This matters since there are multiple pressing healthcare challenges that need to be addressed. Shifting the healthcare paradigm from reaction to pre-emption is important, as is fully leveraging technology. Wearable monitoring devices are already having some impact. Some 50% of Americans and 40% of Chinese use these (per Cleveland Clinic and Statista). Wearables combined with remote monitoring are already saving $200bn annually in hospital costs, based on McKinsey estimates.

More critically, over 50% of the world's population are managing chronic health issues. In the US, six in ten Americans have at least one chronic disease; four in ten have more (figures from the WHO and the Atlantic respectively). When it comes to weight, 43% of US adults are classified as overweight or obese. This figure rises to 50% in China, per the World Obesity Federation. The global cost of obesity currently sits at $2tr and is expected to double by 2035, based on Morgan Stanley calculations.

No surprise then that “much work needs to be done regarding unmet diabetes and obesity needs,” according to Maziar Mike Doustdar, the Chief Executive of Novo Nordisk. He clearly has a vested interest in saying so, but a 5% reduction in weight can cut an obese person’s medical costs by $2,000 per year. A full transition from obesity to healthy weight saves nearly $30,000 in annual medical costs (per Digital Native on Substack). 2m Americans use such drugs currently and the world is already spending $15bn on weight loss drugs. By 2030, Jefferies estimates that figure could reach over $90bn.

If managing weight is currently a significant challenge, then consider Alzheimer’s as the final healthcare frontier, a topic we discussed in more detail last year. Consider that in the last 30 years, over $40bn has been spent on Alzheimer's research, but more than 140 trials failed to yield a single drug capable of slowing the disease. More encouragingly, there are 182 clinical trials for Alzheimer's underway in 2025 (up 11% year-on-year), testing 138 different drugs, of which 12 are likely to complete their final Phase 3 trials this year. This matters since new US cases of dementia will likely double by 2060 from 2020 levels, reaching over 1m (all figures from Nature). The importance of finding a solution has never mattered more.

Cybersecurity

• Season Seven Blog posts: #8, #21, #29, #39
• Relevant theme pieces: 04/14, 09/17, 09/24
• Key statistic: 88% of security incidents still stem from human error (ISACA)

“The attack surface is fundamentally exploding, and we’re not done…the tables are badly stacked. The bad actor has to be right only once; we have to be right 100% of the time”

Nikesh Arora, Chief Executive of Palo Alto Networks

Whether in healthcare, industrial or any other application the data being used to optimise processes will have zero value unless they are secured. Notably, by the end of this year, almost 90% of all data is expected to require a meaningful level of security, but less than half of it will be secured (per IDC). Each data breach costs $4.4m on average globally, although this figure rises to over $10m in the US, according to IBM. The FBI has said that direct losses from cybercrime totalled $16.6bn in 2024, a 33% year-on-year increase. The EU estimates that worldwide cybercrime costs may exceed €5tr.

As in every other industry, AI is changing the rules of the game. Cyber criminals are already harnessing generative AI to produce deep-fake videos and highly personalised phishing messages to steal data or money. AI-related security incidents had “more than doubled since last year,” according to Palo Alto Networks. More than 50% of Chief Information Security Officers (CISOs) state that generative-AI has increased the frequency of cyber threats against their company, and a similar percentage noted that gen-AI had made these threats more sophisticated based on a recent PWC survey.

From the other side, AI technologies are being used to protect businesses against threats from attackers. Almost 40% of CISOs say that they are using AI in identifying risks, threat intelligence analysis and threat detection (according to Splunk). Over 40% of business and technology leaders admit to lacking an understanding of the cyber risks associated with disruptive technologies such as gen-AI and just 1 in 5 companies believe they are well prepared to defend against high-volume AI-powered bot attacks (figures from PWC and Axios respectively).

What all the above implies is that corporate spend on cybersecurity will need to rise, as will increased training. Morgan Stanley sees the market for cyber spending growing at a 10%+ annual growth rate through to the end of this decade, with Dollars allocated to this segment increasing ~50% faster than overall software spend. Research from ISACA notes that even with the pace of technological evolution, the current global workforce of cybersecurity professionals stands at 5.5m, but the industry currently needs double this number (10.2m). It is also an important reminder to us, as ISACA notes, that 88% of security incidents still stem from human error.

Extra Section: Autonomous Vehicles (and Drones)

• Season Seven Blog posts: #4, #32, #34, #25
• Relevant theme pieces: 04/15, 02/17, 04/21, 04/24, 10/22
• Key statistic: Autonomous vehicles have driven over 33m miles cumulatively without human intervention and have had 78% fewer injury-causing crashes compared with a human driver over the same distance (Waymo – for their own vehicles)

“Autonomous vehicles aren’t going to take over all at once, but instead are going to start augmenting what humans can do over the next decade… you fast forward 15, 20 years, I think that the autonomous driver is going to be a better driver than the human driver”

Dara Khosrowshahi, Chief Executive of Uber Technologies

Which industry could next be turbocharged by data and AI? Potentially the auto sector, in our view. Vehicles already are a form of software on wheels and will only become more so. It was certainly abundantly evident from our 2025 visit to California that autonomous vehicle hype is back. Some of this is justified. We first wrote a decade ago about how the road to autopia (as we termed it) would be long and complex. Autonomous vehicles admittedly only currently work in clearly defined urban boundaries and with many in-built constraints, but to see them in action is to begin to believe.

Listen to Uber’s CEO Dara Khosrowshahi. On a recent call with the investment community, he highlighted the success of Waymo's autonomous vehicles (AVs) on its network, noting that they complete more daily trips than 99% of Uber's human drivers. This achievement marks a significant milestone in Uber's partnership with Waymo, showcasing the potential of self-driving cars to enhance productivity and efficiency in ride-hailing services. High utilisation reinforces economic viability. Once a revenue model is better proven, financing for AVs becomes easier. It is also worth noting that Waymo’s autonomous vehicles have driven now driven more than 33m miles cumulatively without human assistance. During this period, the company reports that there were 78% fewer injury-causing crashes compared with a human driver over the same distance.

Before we get too excited about the potential of AVs, consider that there are probably fewer than 5,000 operational in the US and China combined at present. The viability of autonomous vehicles has yet to be adequately demonstrated in busy and complex areas such as airports or at high speeds on motorways. Older and narrower European streets may prove problematic too. Nonetheless, there could be 35,000 AVs on the road globally by 2030, with the market worth up to $400bn ten years from now (based on estimates from Goldman Sachs and McKinsey respectively).

The vehicle of the future will likely be a hybrid. Autonomous vehicles will not supplant manual ones overnight for a variety of reasons. Expect all cars to contain an increasing number of features that will allow for greater autonomy. Adaptive cruise control and lane assist are current examples. More will follow. Similarly, just as an increasing number of vehicles will embed autonomous features (and hence a growing software component), so a greater percentage of cars will be electric. The world now sells as many EVs in a week as it sold each year a decade ago. This year, EV sales will comprise a 20% share of all global cars sales, but this figure could reach 33% by 2027 and 45% by 2030 (per Bloomberg New Energy). Improving technology means that range anxiety and charging speeds are becoming diminishing concerns.

Project further out and the sight of electric vertical take-off and landing transport solutions (or eVTOLs) in our skies will become normalised. We have been impressed with what we’ve seen so far. Bulls of these eVTOL opportunities such as Morgan Stanley estimate that the market could worth $1tr by 2040.

Honourable mentions

There is, sadly, never enough space in this publication to cover all the topics that deservedly merit attention. We could have written about water and food (both integral to human health) or sustainability (where there is much work still to be done). We have profiled these themes in prior annual publications but thought it more interesting to discuss below subjects with more topical relevance. All three unrelated topics have also been discussed in dedicated Blog pieces over the past twelve months.

• Stablecoins
  The past twelve months has seen major progress in alternative payment mechanisms. Most crucially, the GENIUS Act (short for the Guiding and Establishing National Innovation for US Stablecoins Act) in the US includes the provision for stablecoins to be backed one-for-one with US dollars, or other low-risk assets. Although ~90% of all current stablecoin volume is crypto trading related, consumer and merchant acceptance will be a major theme in 2026. “We’ve [already] started to move beyond the proof of concept stage,” says Michael Miebach, the Chief Executive of Mastercard. Progress, of course, will not be linear. For any currency to become a general-purpose payment tool, it needs to be not only seamless and predictable but also have significant reach, distribution and global merchant acceptance. Add in to this the importance of multi-level security and fraud protection as well as compliance with local laws and regulations across multiple geographies (see Blog post #27 for more). Watch this space. Our first theme piece next year will explore the stablecoin topic in more detail.

• Quantum computing
  2025 is the UN International Year of Quantum Science and Technology. After several false starts, there is growing evidence that quantum solutions are becoming increasingly viable. Recent breakthroughs in the quantum space (some of which we profiled in post #22) have helped to turbo-charge progress. At the same time, a record level of venture capital has gone into quantum within the last year, per Crunchbase. A strong industry consensus is emerging that commercial quantum services will likely be available in around five years’ time (see post #28). By 2040, quantum could deliver $450-850bn of economic value, estimates BCG. Watch for more exciting developments next year.

• Online dating
  Nothing is more fundamental than forging human connections. However, the process has never been easy, particularly when it comes to finding a partner. Dating should, therefore, represent a strong category to which big data analysis and AI tools can be leveraged to improve outcomes. There are 670m single people of dating age in the world, excluding the Chinese market. At the same time, 80% of Gen-Z individuals polled (by Match Group) say that they are “looking for a meaningful connection.” Consider dating apps as an enabler. Platform businesses (in any walk of life – think Uber, Airbnb elsewhere) seek to reduce friction by connecting supply and demand via a trusted intermediary. Add in AI and you have a potentially perfect relationship. Match’s platform generates 5bn new data points daily. Around 500m matches occur each month. More on potential happiness in Posts #2, #24 and #30. 2026 may be a lucky year for some.