• Big Tech calculated to harvest up to $162,492 per person in inflation-linked commercial value from internet users worldwide over a lifetime, according to first-of-its-kind report
• Across the world’s estimated 6,000 million internet users the report’s upper lifetime estimate would amount to approximately $745 trillion in commercial value.
• The study, which assessed 129 major companies, found Amazon, Alphabet, Microsoft, Meta and Anthropic are some of the most significant beneficiaries of data capture.

Web3 Foundation today launched ‘The Hidden Price of Free: What Your Data Is Really Worth’, a groundbreaking report revealing that Big Tech and AI companies earn upto $160,000 in commercial value from each internet user over a digital lifetime.

This equates to a staggering $745 trillion across the combined global population of internet users over a period of 60 years.

The study calculated the companies earn upto $8,500 per year from USA internet users per year, upto $2,206 per user in United Kingdom and Europe and $407 in the rest of the world. Globally this equates to an annual amount of upto $908 per internet user.

Over a lifetime that means the commercial value for a user in the USA is $511,869, UK and Europe $132,387, $24,424 in the rest of the world and overall $54,499 globally – or a huge $1.08m in the USA, $260,542 in UK and Europe, $72,821 elsewhere and $162,492 globally when inflation-linked.

In relative terms, the lifetime figure is equivalent to almost five years of full-time employment in the UK, using the ONS 2025 benchmark of $52,474 per annum.

On an inflation-linked basis, the US lifetime figure of $831,301 is roughly equivalent to two times the Q1 2026 median sales price of a new US house. Amazon, Alphabet (Google), Anthropic, Microsoft and Meta are explicitly listed in the report, each earning up to $1,000 annually on a single internet user.

The report shows that the modern internet is not free but paid for through personal data. Searches, clicks, locations, purchases, prompts, messages, images, preferences and behavioural signals are collected, analysed and monetised by some of the world’s most powerful companies, usually without users having meaningful visibility, bargaining power or participation in the value created.

Unlike previous attempts to estimate the value of personal data, which have focused mainly on advertising revenue per active user, Web3 Foundation’s methodology takes a broader view of how human data is monetised in the modern digital economy.

The study examines advertising, AI subscriptions, enterprise licensing, API access, data brokerage, marketplaces, algorithmic recommendations and AI-driven cost savings.

This allowed the findings to account not only for social media and search platforms, but also for emerging AI firms, hardware-linked digital ecosystems and data brokers whose business models increasingly depend on collecting, analysing and reusing personal data at scale.

The report stresses that the figures are not presented as precise valuations or direct cash entitlements owed to individuals. Instead, they are intended as a benchmark for understanding the scale of commercial value associated with personal data and the extent to which that value is captured by companies rather than users.

Why AI changes the data economy

Web3 Foundation argues that artificial intelligence makes the imbalance more urgent. Personal data is no longer used only to target adverts. It is used to train models, improve recommendations, power enterprise systems, build behavioural profiles, create predictive products and generate new forms of machine intelligence.

Every search query, location signal, online purchase, social interaction, uploaded image or chatbot prompt can become part of a wider data economy. As AI systems become more capable, human-origin data becomes more valuable, while users remain largely excluded from the economic upside.

Web3 as a different model

The report says Web3 offers a fundamentally different vision for the internet. Rather than relying on centralised platforms that collect and monetise user data behind closed doors, Web3 technologies are built on decentralised digital infrastructure that can give individuals greater control over their identity, assets and online activity.

In a Web3-enabled internet, users could decide what data they share, with whom and on what terms. The report argues this could shift power away from dominant technology platforms and towards the individuals who generate the underlying value.

“For too long, the internet has operated on an implicit bargain that users do not fully understand: convenience in exchange for surveillance. This report helps expose the scale of that imbalance. The modern digital economy is powered by human data, yet the people generating that value have little visibility, control or participation in the upside. Web3 technology can offer a path toward a more equitable internet, where individuals have genuine ownership over their digital lives rather than simply being the raw material for someone else’s business model.” – Gavin Wood, founder, Web3 Foundation

“The internet does not have to work this way. For decades, digital platforms have been built around centralised control, where users hand over their data, identity and value in exchange for access to services. Web3 represents a fundamentally different model, one where individuals can own their digital assets, verify their identity without surrendering personal information and participate more fairly in the online economy. As AI accelerates and data becomes even more valuable, building a more transparent, user-led internet is becoming increasingly urgent.” – Bill Laboon, vice president, Technical Operations, Web3 Foundation

The company began the process on Wednesday morning, starting with staff in Asia.

Workers in Singapore received the first emails at around 4 a.m. local time, while employees in the United States and other regions are expected to hear later in the day.

People familiar with the plans said the notifications will roll out in stages across time zones.

Meta has asked many of those affected to work from home while the process continues. The cuts are part of a restructuring as the company moves more resources into artificial intelligence and reduces costs elsewhere in the business.

The reductions are expected to hit engineering and product teams the most. Some staff were told earlier that further changes could follow later in the year, depending on how the restructuring progresses.

At the same time, Meta has moved about 7,000 employees into newly formed teams focused on AI work, including product development and autonomous systems. The company ended March with just under 80,000 employees before these latest changes took effect.

In an internal memo, Meta’s Head of People, Janelle Gale, said the company is moving towards a flatter structure.

“We’re now at the stage where many orgs can operate with a flatter structure with smaller teams of pods/cohorts that can move faster and with more ownership.”

“We believe this will make us more productive and make the work more rewarding,” she said.

Chief Executive Officer Mark Zuckerberg has made artificial intelligence the company’s main priority.

Meta has committed more than $100 billion in capital spending this year on AI infrastructure and related projects, as it tries to keep pace with competitors including Google and OpenAI.

The company has already carried out several rounds of layoffs in recent years as part of an efficiency stimulation. It has also encouraged staff to use AI tools in daily work, including coding and internal systems automation.

Inside the company, the changes have created unease. Some employees have complained about job security and the direction of internal AI projects.

More than 1,000 staff members signed a petition asking the company to avoid extensive data collection from employee devices for AI training, including inputs such as keystrokes, mouse movement and screen activity.

“Automators like Meta risk no longer being an employer of choice as it’s being revealed that they will cut out the human when the opportunity presents itself,” said Jan-Emmanuel De Neve, professor of economics and behavioural science at University of Oxford.

“Doing so might well lead to short-term cost savings but risks longer-term growth potential by undermining employee wellbeing and engagement.”

Investor considerations have also grown around the scale of Meta’s AI spending and whether it will deliver returns.

While the company describes the job cuts as a way to offset the cost of its AI expansion and restructuring, analysts at Evercore estimate the layoffs could generate about $3 billion in savings for Meta.

That figure is small compared with its bigger investment plans, and capital expenditure could reach about $145 billion this year, with expectations of further heavy spending on AI infrastructure over the coming years.

The research firm predicts Meta will generate $243.46 billion in net advertising revenue in 2026. That would put it just ahead of Google, which is projected to bring in $239.54 billion over the same period.

Meta’s ad business is expected to expand by 24.1% this year, up from 22.1% in 2025. Google’s growth, by contrast, is forecast to hold steady at 11.9%.

Focusing on automated advertising tools is enhancing Meta’s Advantage+ suite, which has gained traction among advertisers who want quicker campaign setup and better returns on spending. 

That demand is helping the company pull in more marketing budgets at a time when brands are watching costs closely.

“In ⁠surpassing Google, Meta has essentially had many of its core ⁠strategies validated,” said Max Willens, principal analyst at Emarketer.

Added to this, Meta has also expanded its ad footprint in recent years. It introduced advertising on WhatsApp and Threads, opening new inventory for marketers. At the same time, Instagram Reels is competing in the short-video space, where TikTok and YouTube Shorts are already strong.

Meanwhile, Google still earns from a mix of businesses, including subscriptions such as YouTube Premium. That spread provides stability, but it may also slow how quickly its ad revenue grows compared with Meta’s more focused push.

The market is concentrated. Emarketer expects Google, Meta and Amazon to account for 62.3% of global digital ad spending in 2026.

Smaller platforms are likely to feel more pressure if ad budgets tighten. Analysts say companies such as Snap and Pinterest are more exposed when advertisers shift spending towards larger, established platforms.

Emarketer noted that recent court rulings involving Meta and YouTube were not included in its projections and are not expected to significantly change the outlook.

Details shared with investors, and reported by Axios, outline a strong growth path. The company expects ad revenue to reach $11 billion in 2027, then $25 billion in 2028, and $53 billion in 2029.

These figures depend on one key assumption where OpenAI believes its products could reach 2.75 billion weekly users by the end of the decade.

Early this year, OpenAI began testing ads in ChatGPT for some users in the United States. The test focused on people using the free tier and the lower-priced Go plan.

Within six weeks, the pilot crossed $100 million in annualised revenue. By March, more than 600 advertisers had signed up.

That early traction gives a clearer picture of where the company is heading. Ad is no longer an experiment but an indispensable part of how OpenAI plans to make more revenue, alongside subscriptions and enterprise deals.

The market is large but crowded. Alphabet reported $294.69 billion in advertising revenue in 2025, while Meta posted $196.18 billion.

OpenAI is trying to take a share of that ad market by using a different advantage, ultimately boosting revenue. In chat-based systems, users usually state exactly what they want, which could make adverts more precise.

Still, there are issues. Some analysts have warned that showing ads inside ChatGPT could affect how people trust the service but OpenAI says it has not seen that so far.

The company reports low dismissal rates and no drop in its trust metrics since the pilot began.

Not everyone is taking the same route. Competitor Anthropic has said its Claude chatbot will remain ad-free, drawing a line between the two approaches.

Meanwhile, advertising is expected to carry a large share of OpenAI’s revenue as it tries to keep up with the high cost of building and running its AI systems.

The company is also strengthening itself as a business that can scale in the same way as the largest internet platforms, with ads being a big part of that plan.

The Competition and Markets Authority said on Tuesday it will take a fresh look at Microsoft’s approaches, months after deciding not to act on earlier findings.

This time, the regulator is considering whether to give Microsoft “strategic market status” in business software, and this would allow closer oversight and direct intervention.

At the centre of the case is how Microsoft links its software, including Windows Server and Microsoft 365, to its own cloud platform. Regulators have noted that customers face extra costs when they try to run these tools on rival services.

That, they say, makes it harder for businesses to switch providers or spread workloads across different clouds.

Companies want flexibility and when pricing or licensing regulations get in the way, it limits choice and raises expenses.

The UK cloud market is tough. Amazon and Microsoft each control about 30 to 40% of the sector, covering services such as storage, processing and networking.

Google follows with a much smaller share of around 5 to 10%. Earlier findings from the regulator said this level of concentration was already affecting competition.

The CMA noted that both Microsoft and Amazon have recently taken steps to ease some of the pressure. These include reducing certain fees tied to moving data between platforms and improving how systems work together. Still, the watchdog expects more changes in the coming months.

CMA chief executive Sarah Cardell said the regulator is acting in a “flexible, pragmatic way to deliver real impact, as quickly as possible for UK customers”.

She added: “Cloud remains central to our approach – we’ve seen real progress through our engagement with Microsoft and Amazon to drive meaningful improvements on egress fees and interoperability and we expect more action from them over the coming months.”

Microsoft says the cloud licensing adjustments it has agreed to focus on data transfers, switching between providers and system compatibility.

Its vice chairman and president, Brad Smith, said: “The changes address the CMA’s commitment to ensuring that UK customers can continue to move, deploy, and operate their workloads in the clouds of their choice with confidence, flexibility, and ever-reduced friction.”

Amazon, for its part, said the steps it has taken formalise its support for customer choice, including the ability to run services across multiple cloud platforms.

Beyond the UK, regulators in both the European Union and the United States are examining similar issues in cloud computing. The focus is largely the same, reviewing whether large providers are using their position in software and infrastructure to limit competition.

Within that surge, the drive between Google and Microsoft has become one to pull focus on, not just for technology leadership, but for how artificial intelligence (AI) turns into profitable business, especially with committed spending.

Two Companies, Two Directions

Even before you look deeper, you’d notice both companies are building similar systems, but you’d see the difference in how those systems are used.

Google is pushing its models into products people already use every day, including Search, Android, and YouTube. Its Gemini platform has crossed 750 million monthly users, giving it reach that few competitors can match.

Microsoft is taking a different route which is more structured. Its Copilot tools are built into Word, Excel, Teams and other workplace software. The idea is to make businesses pay for productivity.

That difference is where we place our attention. Google has scale, while Microsoft has pricing.

The Competition is Infrastructure

It is easy to focus on apps and chat interfaces, but that is not where the case is being decided.

It is in infrastructure you’d find the competition; data centres, chips, and computing power.

Alphabet, Google’s parent company, plans to spend $175 billion to $185 billion in 2026 alone, largely on servers, networking and AI capacity.

Microsoft is also increasing spending, with its capital expenditure expected to move towards $100 billion or more, driven by demand for cloud and AI services.

This level of investment changes the nature of the industry. AI is not just software, it is capital-intensive, closer to energy or telecoms than traditional tech.

I would put it this way, whoever controls compute, controls the market.

Products: Gemini vs Copilot

The difference in strategy becomes better to grasp at the product level.

Google’s Gemini is built for wide use, sitting inside search results, mobile devices and developer tools. Updates have been frequent, with new versions released through 2025 and early 2026 to improve reasoning and performance.

Microsoft’s Copilot is more targeted, focusing on workplace tasks, writing documents, analysing spreadsheets, and summarising meetings.

But adoption?

Microsoft has around 15 million paid Copilot users, a small share of its Microsoft 365 base of hundreds of millions.

That gap stresses the fact that interest in AI tools is high. Paying for them is still limited.

Cloud: Where the Money Actually Comes From

The revenue engine is behind the scenes. Google Cloud has been expanding, with revenue growth close to 48% year-on-year, driven largely by demand for AI workloads.

Microsoft Azure is however a larger business, with strong growth tied directly to AI usage and enterprise demand.

This is where the competition becomes tougher because companies are not just using AI tools, they are renting computing power to run them.

Cloud turns AI into something billable.

Spending is Increasing Faster Than Returns

There is, nonetheless, an imbalance.

Microsoft is targeting $25 billion in AI-related revenue by 2026, supported by Copilot and Azure services.

Google is already seeing profits in advertising and cloud from its AI rollout.

But both are spending far ahead of what they are earning.

Even within Microsoft’s ecosystem, only a small percentage of users are paying for AI features, despite heavy investment and promotion.

So when does this start paying off?

It is Important to note that Investors are not ignoring the risk.

Google’s decision to increase spending has already triggered mixed reactions in the market, even as its core business stands strong.

Microsoft is facing a different issue, which is adoption. Copilot is growing, but not at a pace that fully justifies the scale of investment yet.

So the market is in a strange position, believing in the long-term potential, but watching the short-term numbers carefully.

Here the Bigger Question Comes

This has gone beyond a competition between two companies. Will the current level of investment produce the kind of productivity being promised?

The comparison with past technology cycles is unavoidable. Large amounts of capital are being deployed ahead of proven returns. That does not automatically mean a bubble, but it does introduce risk.

Right now, demand for computing power is strong, but what we don’t know is whether that demand will remain strong enough to justify the infrastructure being built.

Who is Ahead?

The answer depends on how you measure it.

Google is ahead when it comes to reach. Its products touch billions of users, and its AI systems are already embedded into everyday digital activity.

Microsoft comes top in structure. It has a clearer path to monetisation through enterprise software and cloud services.

Google and Microsoft are strong when it comes to AI, both are spending heavily, but neither has fully solved the same problem, which is turning scale into sustained profit.

So, let’s not look at who builds the better model between Google and Microsoft or who comes top in AI spending, but who can turn artificial intelligence into a reliable business before the cost of building it becomes harder to justify.

That is where this growth will be decided.

A source familiar with the matter said the job cuts were carried out on Wednesday and affected units including Reality Labs, social media teams and recruiting.

The scale is smaller than earlier plans, but it follows internal discussions about deeper reductions.

Earlier in the month, Reuters reported that Meta had considered larger layoffs that could affect 20% or more of its workforce. Those plans have not been fully carried out, but they are still part of longer-term restructuring discuss.

In a statement, a Meta spokesperson said, “Teams across Meta regularly restructure or implement changes to ensure they’re in the best position to achieve their goals. Where possible, we are finding other opportunities for employees whose positions may be impacted.”

The company employed nearly 79,000 people as of December 31, according to its latest annual filing.

With these changes tied to high costs, Meta is increasing spending on artificial intelligence (AI), with total expenses projected at between $162 billion and $169 billion in 2026.

A large share of that budget will go into data centres, computing infrastructure and hiring specialised talent.

At the same time, the company is cutting back in areas that no longer sit at the centre of its plans. Reality Labs, which focuses on augmented and virtual reality, has recorded heavy losses in recent years.

Reports put those losses at about $16 billion between 2023 and 2025.

Now, attention has shifted, and Chief Executive Mark Zuckerberg has placed artificial intelligence at the core of the business, reducing the weight previously given to AR and VR projects.

The latest layoffs also touch sales, global operations and other support roles, according to earlier reports. Some affected employees, especially outside the United States, have been offered options to move into other roles or locations.

Meta is not alone in this direction. Other large technology companies have made similar decisions, cutting jobs in hardware and cloud units while increasing investment in AI.

The new plan targets senior leaders, including Chief Executive Mark Zuckerberg, as the company expands its drive into artificial intelligence and tries to keep key talent.

Regulatory filings show that several top executives will now be eligible for stock options. They include the finance chief, technology chief, product chief, operating chief, president and legal chief. Most of them will also receive higher restricted stock awards, which vest over time.

The stock options come with conditions, as the lowest tranche only pays out if Meta’s share price reaches $1,116.08. That is about 88% above its latest close of $592.92. The highest tier requires the stock to climb to $3,727.12, more than six times its current level.

If the targets are not met by February 2028, the unvested options will be released gradually until August 2030. They expire in March 2031 if unused.

A company spokesperson said the package is a “big bet” and that it “will not be realised unless Meta achieves massive future success, benefiting all of our shareholders.”

This stresses how intense the competition for AI talent has become. Companies such as OpenAI, Google and Anthropic are offering large pay deals to attract researchers. Meta has also been active, hiring aggressively and acquiring smaller firms to strengthen its AI teams.

In March, the company brought in Dreamer AI, a startup working on advanced AI systems, as part of its expansion into what it calls “superintelligence” research.

Spending has surged alongside hiring, with Meta reporting $72 billion in capital expenditure in 2025 and expects that figure to rise to as much as $135 billion in 2026. Much of that is tied to AI infrastructure, including data centres and computing power.

Analysts expect Meta’s stock to trade between $838 and $935 in 2026, with some forecasts going higher. Even so, the new option targets sit well above those estimates.

Executives only benefit if the company delivers exceptional growth. So, Meta is tying pay to performance, believing AI will drive that outcome.

That is a 36% year‑on‑year increase from 2025, making this one of the fastest capital expenditure (CapEx) booms in modern corporate history. 

So, let’s discuss. Is this exceptional AI CapEx surge cycle driving productivity in the economy, or are we inflating another technological asset bubble?

The AI CapEx Scale: What’s Happening Now

Across the largest tech firms, the hyperscalers and cloud giants, capital spending is now structural. Amazon, Google, Meta and Microsoft are expected to put hundreds of billions into new infrastructure in 2026, much of it dedicated to specialised computing clusters, advanced networking and data centre capacity. 

The focal point of this spending is not mere servers or office upgrades. It’s data centres built specifically for high‑power compute workloads, facilities optimised for parallel processing at scale. 

These require specialised hardware like GPUs and high‑bandwidth memory, and they draw massive amounts of energy. 

One recent example shows just how strategic these moves have become. Nebius Group signed a multi‑year deal with Meta Platforms worth up to $27 billion to supply dedicated AI computing capacity by 2027, a contract driven by extreme demand and limited supply for high‑performance computing systems. 

Productivity: What the Investment Could Bring

No doubt that enhanced computing capacity enables economic value. Faster processing, more reliable inference workloads, and greater cloud availability can drive:

• Higher labour productivity by automating routine tasks.
• Faster research and development cycles in sectors from healthcare to manufacturing.
• Lower costs for compute‑intensive services, once infrastructure matures and utilisation improves.

For context, the semiconductor industry, a cornerstone of this infrastructure build‑out, is forecast to approach nearly $1 trillion in sales in 2026, with AI‑specific chips maintaining strong annual growth. 

From a macro perspective, such CapEx adds directly to aggregate demand and GDP in the short term. Data centre construction, advanced chip manufacturing, and supporting supply chains all contribute to economic activity that wouldn’t exist without this cycle. 

Bubble Territory: Where the Risks Begin

But there are strong arguments that we are edging into asset inflation rather than productive investment.

First, the pace of spending vastly outstrips current revenue realisation in the economy. Many of these specialised facilities operate at negative operating margins early in their life, requiring ongoing funding before they generate sustainable returns.

Second, a lot of the valuations attached to tech infrastructure assets incorporate lofty future earnings expectations. If those earnings don’t materialise, because adoption slows or competition increases, we could face rapid repricing. 

We’ve already seen some tension in the market, with certain historic investment commitments being scaled back. 

Third, hyperscalers are relying more on external financing even as their own cash flows get tighter. That’s a classic hallmark of an investment boom that may not be fully backed by near‑term productive returns. 

Semiconductors and Data Centres: The New “Oil”?

The analogy of compute as “the new oil” captures two truths:

1. Dependency: Modern AI workloads require massive compute capacity, just as 20th‑century industry relied on petroleum.
2. Infrastructure bottlenecks: Scaling compute, even with unlimited capital, is limited by semiconductor supply, power delivery, and cooling technology.

Already, suppliers like TSMC have posted strong revenue outlooks, showing reliance on advanced chips across the industry.

In parallel, smaller specialist data centre operators, such as CoreWeave, have expanded at a rapid clip. CoreWeave now operates dozens of facilities globally and has become a major supplier for bespoke compute capacity. 

But then, this infrastructure is expensive and energy‑intensive. Many facilities find it hard to break even without long‑term contracts or guaranteed utilisation.

Investment Implications: Winners and Fragilities

From an investment standpoint, certain firms appear ready to benefit if demand holds:

• Nvidia is at the centre of the compute supply chain. Its recent San Jose GTC 2026 forecast shows at least $1 trillion in chip revenue by 2027, driven by demand for next‑generation chips at scale. 
• Other chip designers and foundries stand to gain from backlogged orders and long production lead‑times.
• Data centre REITs and infrastructure funds may see longer‑term cash returns as contracts mature.

On the risk side, overcapacity, falling prices for older hardware, and slower adoption outside of hyperscale use cases are still substantive challenges.

So, Growth Engine or Asset Bubble?

Standing here in March 2026, we see both sides.

On the productivity side, this spending wave is building infrastructure that will underpin major advances in how industries operate. It’s tangible investment in capacity, not just speculation in intangible assets.

On the asset inflation side, the pace and scale of spending go beyond today’s revenue reality. Markets have priced future growth aggressively, which increases the risk of repricing if adoption deviates from expectations.

Now, are we financing a foundation for long‑term productivity, or are we inflating the price of future earnings prematurely?

The company says the planned subscriptions will come with extra tools for everyday users, creators and businesses, including new ways to work, create and share content. 

These paid options will sit outside Meta Verified and will be tested in different forms across each app rather than launched as a single package.

From what Meta has outlined, there is no fixed model yet. Instead, the company intends to experiment with different bundles and features, adjusting its approach based on user response. 

The goal is to avoid forcing one paid experience across platforms that serve very different audiences.

An important part of the plan involves Manus, the autonomous agent company Meta acquired in December for a reported $2 billion. Meta plans to weave Manus into its consumer apps while continuing to sell it as a standalone product to businesses. 

The company previously described the technology as a way to deliver tools that can complete complex tasks with minimal input.

“Manus’s exceptional talent will join Meta’s team to deliver general-purpose agents across our consumer and business products, including Meta AI,” the company said at the time of the acquisition.

Signs of early integration are already appearing. Reverse engineer Alessandro Paluzzi, known for spotting features still in development, has shared evidence suggesting Meta is working on a Manus shortcut inside Instagram.

Video creation will also become part of Meta’s subscription tests. The company plans to introduce paid tiers for Vibes, its short-form video creation feature inside the Meta AI app. 

Vibes, launched last year, allows users to generate and remix videos. While it has been free until now, Meta intends to move it to a freemium model, where subscribers can unlock additional video creation limits each month.

Some of the most concrete details so far relate to Instagram. According to Paluzzi, a subscription could allow users to create unlimited audience lists, see which followers do not follow them back, and view Stories anonymously. What paid features might look like on WhatsApp and Facebook has not yet been disclosed.

Meta says the new subscriptions are informed by lessons learned from Meta Verified, its paid verification service introduced in 2023. Meta Verified is largely aimed at creators and businesses, offering a verified badge, direct support, impersonation protection and other tools. The new subscriptions, by contrast, are designed for a wider audience.

Across the social media industry, advertising growth has slowed, competition from platforms like TikTok has increased, and paid features are becoming more common. 

Snap’s Snapchat+ service, priced from $3.99 a month, has passed 16 million subscribers and continues to grow, showing that users will pay if they see value.

But still, looking at the risk of subscription fatigue. With users already paying for streaming, cloud storage and productivity tools, convincing them to add another monthly fee will not be easy. 

Meta says it plans to roll out the tests gradually and gather feedback before deciding how far to push its subscription plans.