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How Long Does It Take to Hit 50 Million Users?

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How Long Does It Take to Hit 50 Million Users?

How Long Does It Take to Hit 50 Million Users?

The Chart of the Week is a weekly Visual Capitalist feature on Fridays.

Imagine it’s the year 1960, and you’re an entrepreneur that’s about to launch the next big thing.

Let’s assume that your product is actually pretty revolutionary, and that you’re going to receive widespread buzz and word-of-mouth traction. How quickly do you think it could be adopted by millions of users?

Before the internet and consumption of digital goods, the use of a product could only spread as fast as you could manufacture the physical good. You would first need many millions of dollars in capital, a plant, a workforce, and inventory. Then, once the product is ready for distribution, you’d need mass advertising, word-of-mouth, sales channels, and press coverage to stand a chance.

Even then, if the product is really revolutionary, you’re looking at a decade or more for it to get widespread adoption.

Atoms Versus Bytes

Automobiles took 62 years to be adopted by 50 million users. The telephone took three years just to be in the homes of 50,000 people.

But these are both physical goods that need raw materials, skilled workers to produce, and economies of scale. They are made of atoms – and atoms must abide by the laws of physics.

In the modern era, you don’t have to produce a physical good. All you need to do is produce a useful piece of code that be replicated or re-used indefinitely at a marginal cost near zero, and it can spread like a wildfire.

Product / TechnologyTime it Took to Hit 50 Million Users
Airlines64 years
Automobiles62 years
Telephone50 years
Electricity46 years
Credit Cards28 years
Television22 years
ATMs18 years
Computers14 years
Mobile Phones12 years
Internet7 years
Facebook4 years
WeChat1 year
Pokemon Go19 days

As you can see, the transition from physical to digital goods has affected adoption rates, but so has the growing power of network effects.

Metcalfe’s Law

Metcalfe’s Law states the effect of a network is proportional to the square of the number of connected users of the system (n2).

Within the context above, it simply means that each additional user of a good or service adds additional value to others in that network. New goods or services in the digital realm can harness this network effect to gain users at unprecedented rates. It’s why social media, apps, and the internet were able to take off so quick.

It’s also why the augmented reality game Pokémon Go was able to reach a mind-blowing 50 million users in just 19 days.

And now, with unparalleled connectivity and more than four billion internet users globally, the next big thing could hit that milestone even faster than Pok̩mon Go. Instead of almost three weeks, it might do so in a few days Рor even a few hours.

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Charted: The Jobs Most Impacted by AI

We visualized the results of an analysis by the World Economic Forum, which uncovered the jobs most impacted by AI.

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Charted: The Jobs Most Impacted by AI

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Large language models (LLMs) and other generative AI tools haven’t been around for very long, but they’re expected to have far-reaching impacts on the way people do their jobs. With this in mind, researchers have already begun studying the potential impacts of this transformative technology.

In this graphic, we’ve visualized the results of a World Economic Forum report, which estimated how different job departments will be exposed to AI disruption.

Data and Methodology

To identify the job departments most impacted by AI, researchers assessed over 19,000 occupational tasks (e.g. reading documents) to determine if they relied on language. If a task was deemed language-based, it was then determined how much human involvement was needed to complete that task.

With this analysis, researchers were then able to estimate how AI would impact different occupational groups.

DepartmentLarge impact (%)Small impact (%)No impact (%)
IT73261
Finance70219
Customer Sales671617
Operations651817
HR57412
Marketing56413
Legal46504
Supply Chain431839

In our graphic, large impact refers to tasks that will be fully automated or significantly altered by AI technologies. Small impact refers to tasks that have a lesser potential for disruption.

Where AI will make the biggest impact

Jobs in information technology (IT) and finance have the highest share of tasks expected to be largely impacted by AI.

Within IT, tasks that are expected to be automated include software quality assurance and customer support. On the finance side, researchers believe that AI could be significantly useful for bookkeeping, accounting, and auditing.

Still interested in AI? Check out this graphic which ranked the most commonly used AI tools in 2023.

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