Everything that changes before 2036, in ten charts

By 2036, on the charts that follow, people will be a minority on the web and machines will have been reading more of it than we do for several years. Most of us will meet AI in the tools we already use, and most of us will use it deliberately. Well over half of new cars will be electric, and a third will carry hardware built for some form of self-driving. The humanoid robot market will have either delivered ten million units or fewer than one. And the encryption protecting all of it will either have been replaced or will be running out of time to be.

Some of that is measured. Most of it is modelled. The point where one becomes the other is marked on every chart, because the difference between the two is the whole story of this year. The machines are ahead of schedule, and the schedule was wrong in both directions at once. Cloudflare's chief executive predicted bots would pass humans on the web in late 2027; it happened in June 2026. Estimates of Chinese humanoid shipments tripled inside six months. The qubit count needed to break the internet's encryption fell twentyfold on a single paper. Meanwhile the most-shared chart of the year, Linux surging past Windows, turned out to be measuring crawlers.

So these ten charts are drawn to show the shape rather than the number. Most run to 2036; one runs to 2040, because that is where the most ambitious forecast in the piece sits. Where credible sources disagree by a wide margin, we have drawn the band rather than picked a line, and where they are measuring different things we have said so rather than joined them up. Two of the charts will not say what you expect. One of them contains a set of dates no company can move.

1. Humans become a minority

Delegating one task to an agent does two things at once. It removes the pages a person would have viewed, and it adds the pages a machine views instead. Our model assumes roughly seven human page views per self-served task and around a hundred machine fetches per delegated one. That ratio is an assumption, not a measurement, and the chart is sensitive to it. But under any plausible version of it the human share moves far faster than adoption, and human use does not have to fall at all for the human share to collapse.

2. The crossover: machines reading more than people, some time after 2030

Strip out the legacy scrapers and training crawlers and look only at live, person-initiated agent fetches against human page views. Agent traffic is somewhere around 0.4% of web requests today. On our central model it passes human traffic early in the next decade. That is a large claim and it deserves to be stated as one.

Here is what the crossing actually requires. The agent-to-human ratio today is roughly 0.4 to 42.5, or about one to 112. Reaching parity by 2031 means that ratio grows about 112-fold in five years, which is around 157% a year compounded. That is not a timid forecast. It is a strong one, and it rests on assumptions about how many tasks each person delegates, how many fresh fetches each task triggers rather than cached answers or API calls, and how much human browsing each delegation actually displaces. Change any of those and the crossing moves by years. We have kept 2031 as the illustrative case because it follows from the same assumptions used in chart 1, not because it is the most probable single year.

3. The driver: how people are actually meeting AI

The adoption question is usually asked as though AI were a destination people choose to visit. Increasingly it is not. It is embedded in the search box, the email client and the document editor people were already using. Those are different things and they deserve different lines.

The reason to draw three lines rather than one is that they will not move together. The top line is close to saturation already, because it counts anyone who sees a generated answer above their search results whether they wanted one or not. The middle line is the traditional adoption curve. The bottom line is the one that drives every other chart in this article, and it is the one nobody measures well yet. Being bold about the top line costs nothing; being bold about the bottom one is the actual forecast.

4. Which tasks move first

Adoption arrives by task, and within any single population the order is fairly consistent: research first, then creation, then decisions, then transactions. The gap between the first and the last is measurable. Among people who use AI at all, more than three-quarters use it to shop, yet nearly one in three will not let it spend money, and only around 6% of workers say they go to AI first when a task lands on them.

Read each group on its own terms. Among workers who already use AI, the tasks near the top are the ones where a first draft is useful even when imperfect and a person checks the output anyway. Among all adults, the tasks near the bottom involve money, health or a date that cannot be missed, and those are where people keep their hands on the wheel. Microsoft's own Work Trend Index found decision-making accounting for 28% of Copilot activity, so the decision layer is moving faster than most people assume. The transaction layer, where an agent actually pays, is the one still held back by the third of people who will not let it, and that is the layer that changes the economics of the web when it moves.

5. Linux on the one measure that cannot be gamed

Page-view trackers spent 2026 reporting a Linux surge that turned out to be bot traffic reclassified. Measured on Valve's hardware survey, which reads the client rather than a user-agent string and cannot be inflated by crawlers, Linux was 3.90% in August 2026 against Windows at 93.95%.

Linux gained more share in three months of bad measurement than it has in a decade of real adoption. That is the whole lesson of this article in one sentence.

One caveat we hold rather than dismiss. It is entirely possible that Windows faces a sharper fall than either line above: the Windows 10 hardware cut-off has stranded a large installed base, European public procurement is moving with unusual conviction, and the next generation of personal devices may not be PCs at all. If that happens it will show up first on Steam and in first-party government analytics, not on page-view trackers. Nothing in bot-proof data shows it yet, and we would rather publish a chart that is early than one that is wrong.

6. The quantum clock, and why the deadline is not a qubit count

The number everyone wants is the year a quantum computer breaks RSA-2048. Nobody can give it, and the reason is worth understanding, because the chart below is easy to misread.

Two things are true at once. The capability is not close: the largest demonstrated error-corrected count is under a hundred, and it is at a code distance far below what Shor's algorithm needs. And the estimates keep moving in one direction: Google's Craig Gidney cut the physical-qubit requirement roughly twentyfold in a single 2025 paper, trading an eight-hour run for one under a week, and a February 2026 architecture paper proposes breaking RSA-2048 with under 100,000 physical qubits using newer codes. IBM's own roadmap, taken at face value, passes the estimate on the chart between 2031 and 2033. Vendor roadmaps are ambitions, not deliveries. Crossing that line is not the year encryption breaks; it is the year the qubit count stops being the constraint.

The deadline is not scheduled for the day the machine arrives, because encrypted traffic captured today can be stored and decrypted later. The EU's draft NIS2 amendment in early 2026 described harvest-now-decrypt-later as likely occurring already. The NSA's schedule for national security systems has three separate dates: new acquisitions must comply from 1 January 2027, equipment that cannot support the new algorithms must be phased out by 31 December 2030, and the algorithms are mandated for use by 31 December 2031. Those bind national security systems, not every company, but they set the pace that suppliers to those systems will follow, and a June 2026 US executive order extended migration requirements across federal agencies.

7. Cars: electric first, autonomous second

The two transitions are usually discussed together and are running several years apart. Electrification is well past its inflection; autonomy is barely at its own.

8. Air taxis: launch is real, scale is contested

An earlier version of this section used a single narrow forecast and presented it as the answer. That was wrong, and the correction is more interesting than the original claim.

The approvals are genuinely close. Joby's quarterly filing of August 2026 put the fourth of the FAA's five certification stages at roughly three-quarters complete, and the company has been flying production-conforming aircraft since March. Archer says it was first to close the third of four phases. The FAA's eVTOL Integration Pilot Program lets pre-certified aircraft operate across 26 states, and Joby flew the first such point-to-point flights in New York in April 2026. Joby is positioned to carry paying passengers from a Skyports vertiport at Dubai International in 2026 under a six-year exclusivity, has absorbed Blade's Manhattan passenger business and its 90,000 annual riders, and Archer and United have announced a nine-node New York network with Archer also selected for the 2028 Los Angeles Olympics. This is not a technology waiting for permission. It is a technology at the final gate.

The honest statement is not that forecasters disagree by a factor of several hundred. It is that nobody has published comparable forecasts for the same market, and the numbers most often quoted alongside each other were never measuring the same thing. What is settled is the shape of the launch: two to five aircraft per city at around $200 to $300 a ride. At least six manufacturers have ceased operations or entered insolvency since 2023, including Lilium and Volocopter, and the sector has consumed more than $13bn in equity since 2019 against passenger revenue in the United States that remains effectively zero until type certification lands, which analysts now put no earlier than mid-2027. The companies still standing are exactly where they need to be. Whether this becomes a transport mode or a premium service is the open question, and a scope-matched forecast that would answer it does not yet exist.

9. Humanoid robots: the line is live, the volume is not

Tesla's Optimus line at Fremont, converted from Model S and X production, began operating in late August 2026. That is real. What it is producing is low-volume units for internal training and data collection, with commercial sales targeted for 2027. As of mid-2026 Tesla had an estimated 1,000 to 1,200 Optimus units across Fremont and Giga Texas, no external sales, and no published uptime figures; on the January 2026 earnings call the chief executive acknowledged that none were yet doing useful work. Wolfe Research does not expect meaningful external revenue before late 2027, and the AI5 chip the robot is designed around is not due until volume production around mid-2027.

The consumer end is arriving ahead of Tesla. 1X's NEO, backed by OpenAI, is the first home humanoid with transparent pricing and a confirmed delivery timeline: $20,000 outright or $499 a month, with more than 10,000 pre-orders and deliveries through 2026. XPeng closed a $900m round to bring IRON to mass production by the end of the year. Figure is building its third-generation robot at roughly one an hour. Unitree's G1 sells for around $13,500 and its R1 for under $6,000. Chinese manufacturers accounted for roughly 97% of global humanoid shipments in the first half of 2026.

The economics are moving faster than the units. Bank of America puts a China-built 2025 bill of materials near $35,000, falling below $17,000 by 2030, with actuators more than half the build, which is why Tesla designs its own. Tesla targets $20,000 to $30,000 at scale; most analysts expect $100,000 to $150,000 for early units. Goldman Sachs projects a $38bn humanoid market by 2035. The Fremont line is designed for up to a million units a year, and Tesla has declined to give a 2026 target. Mass production is a 2027 story. The line going live in 2026 is the thing that makes 2027 possible.

10. Who builds all this

Stanford's AI Index 2026 says the lead between the best American and Chinese models has changed hands more than once since early 2025. In February 2025 DeepSeek-R1 briefly matched the top US model. By March 2026 the leading US model sat 39 rating points ahead on the Arena leaderboard, 1,503 against 1,464. That is a lead of under 3%, and it is not a lead anyone should assume is permanent.

The composition of the lead is the interesting part, because no country leads everywhere. The United States dominates capital and infrastructure: $285.9bn of private AI investment in 2025 against China's $12.4bn, a factor of 23, with California alone accounting for $218bn, and 5,427 data centres, more than ten times any other country. China leads on output and physical deployment: 69.7% of global AI patent filings, 23.2% of publications, 20.6% of citations against 12.6% for the US, and industrial robot installations at roughly nine times the American rate. South Korea leads the world on patents per head. And a single foundry in Taiwan fabricates almost every leading AI chip.

What actually follows from this

Measure your own split before the defaults change

Find what proportion of your traffic your CDN or edge classifies as automated, and how much of that is AI-related rather than legacy scraping. From 15 September 2026 new Cloudflare domains will have training and agent bots blocked by default on pages carrying advertising, so this is a live setting that changes next week, not a research exercise.

Start the cryptographic inventory this year

The quantum chart above is reassuring about capability and irrelevant to your deadline. NIST moves FIPS 140-2 validations to historical status on 21 September 2026, the EU's national strategy milestone falls on 31 December, and the NSA's acquisition gate for national security systems opens on 1 January 2027, with phase-out by the end of 2030 and mandatory use by the end of 2031. Begin with anything that must stay confidential past 2030, because that material is already exposed to harvesting.

Do not buy a strategy from a chart with one data source

The Linux line is the cautionary tale. An entire news cycle formed around a measurement artefact, and businesses made noise about migrations on the strength of it. Any single-source chart showing a mature market moving fifteen points in a quarter has broken before the market has.