India's TikTok ban shows forcing teens off their phones isn't always good

India's TikTok ban shows forcing teens off their phones isn't always good



By Mihir S Sharma

 


Keir Starmer’s British government has been cursed with a long to-do list on which almost every bullet point is deeply unpopular. A ban on social media for teens, on the other hand, is uncomplicatedly supported by the public. The relief was discernible in the prime minister’s voice when he said it would “give children their childhood back.” 


There are plenty of reasons to agree that social media is indeed making children unhappy and unsafe. But bans fueled by moral certainty and high purpose are the easy part. The unpleasant stuff comes later: enforcement, dealing with side-effects, restraining yourself from letting controls multiply across the internet.

 
 


Britain’s ban — which officials promise will go harder and further than in other nations such as Australia — is an iteration of the same knee-jerk paternalism that led the country to introduce a generational ban on cigarettes. There is, however, a global trend here, first visible in India, of treating social media as a danger too important to be left to markets and the unpoliced internet. And the reasons go way beyond the instinct to protect citizens from harm.

 


TikTok, for example, has been banned in India since 2020, and was almost blocked by the US as well. Indian politicians saw prohibition as a way of striking back against China, where the app’s parent company ByteDance is based. American officials worried about Beijing’s data-harvesting and its ability to nudge an entire generation toward disaffection and nihilism.

 


Where things have evolved is that the perceived threat is no longer a specific app from a particular foreign adversary. Many in the West have come to think of big tech companies in general as meddling and irresponsible, and reckon the American giants are just as untrustworthy to chaperone our kids as Beijing.

 


This is a much broader fear, and makes the chances of successful limits far slimmer. You might be able to block a list of Chinese apps, as India has done pretty effectively, yet managing every teenager’s internet access is a Herculean task. India’s TikTok ban did not stop people from gawking at short videos. They kept at it, shifting swiftly and smartly, in the way youngsters do, to other apps. These were mostly American platforms, whose vast resources make them formidable opponents for anyone eager to police them.

 


Britain’s under-16s will surely be just as ingenious as their Indian peers. They may shift away from certain leading apps to others, or to bulletin boards and forums. Many will discover VPNs and location spoofing, or borrow an older sibling’s phone or account. And they will be aided in this quest by online actors — malign or indifferently profit-seeking — who still want to reach them: advertisers, ideologues and predators. Teens’ online world may paradoxically become tougher to oversee and regulate.

 


So what happens next? Those implementing limits in Britain or elsewhere will soon recognise that a light-touch approach to age verification will leave gaps that some kids fall through. When that happens — and the ferocious tabloid media will find enough examples to make it sound like an epidemic — regulators will need to decide on whether to further tighten their grip.

 


The UK could move toward a universal digital identity needed to access the internet, or it might even ban VPNs. Schools, parents or siblings may be held responsible if they openly allow or encourage kids to circumvent the ban.

 


There are real costs, too, that policymakers will not have counted. When India banned TikTok, it changed the creator economy. ByteDance’s algorithm had done a valuable thing by pushing forward the unexpected, the amateur and the disempowered. Random young people from India’s disconnected and forgotten small towns became stars. Once TikTok was banished, YouTube and Instagram replaced all that with the more familiar landscape of manufactured and big-spending influencers. Nobody predicted that.

 


We do not yet know what Britain’s ban, and others like it, will cost a generation in terms of self-expression and community. The same evidence base that demonstrates social media’s capacity for harm also shows that “the buffering effects against [real world] stress that online social support from peers may provide can be especially important for youth who are often marginalised, including racial, ethnic, and sexual and gender minorities.”

 

It is possible that, in the end, this ban will work. Perhaps teenagers will indeed put down their phones and go outside; or at least stop having the most noxious ideologies thrust on them before they are old enough to develop proper British cynicism. But in India, at least, banning TikTok didn’t turn back the clock. It just changed how the internet molded people. 
(Disclaimer: This is a Bloomberg Opinion piece, and these are the personal opinions of the writer. They do not reflect the views of www.business-standard.com or the Business Standard newspaper)



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AI-made ads promise cheaper reach, but can brands avoid slop trap?

AI-made ads promise cheaper reach, but can brands avoid slop trap?



Let’s start with a flashback. Hema, Rekha, Jaya, and Sushma liked Nirma; ‘Jaago re’, urged Tata Tea; Fevikol told the 60-year journey of a sofa; and the erstwhile Hero Honda made us feel it was indeed ‘Desh ki Dhadkan’. All these and many more are shining examples of creative brilliance in advertising. Human intelligence, cultural resonance, and emotional connection made these ads so memorable and evergreen. But something is changing.

 


Disney is preparing to launch a beta version of an artificial intelligence (AI)-generated television ad tool in July 2026. The tool can generate scripts, videos and music through a single workflow and is targeting small and medium-sized advertisers that do not have enough video assets, according to a Business Insider report.

 
 


At the very least, the move indicates a larger shift in advertising. AI is entering high-value video advertising, including connected TV and streaming, where production costs have traditionally kept smaller brands away.

 


For Indian advertisers, the shift could be significant. Small businesses, such as SMEs, that once needed separate budgets for scripting, shoots, editing, voiceovers, music, compliance and platform-specific cuts may now be able to create basic video assets faster and at lower cost. But the same promise also carries a warning: If video ads become cheap, quick and self-serve, Indian consumers may soon see far more ads—not necessarily better ones.


What is driving adoption


Industry executives say the adoption of AI-generated ads is not being driven by cost alone. Aditi Olemann, Vice President, Marketing & Communications at Cashfree Payments, says that novelty, operational efficiency, and speed are driving this adoption.

 


“First is the novelty factor. AI video creation capabilities have advanced dramatically in the last year; hence, these ads stand out as distinct and memorable, capturing audience attention effectively. Second is operational efficiency. By eliminating the need for traditional shoots and logistical complexities, AI allows for seamless iteration and refinement without costly reshoots. Finally, there is the advantage of speed. AI-driven production enables rapid deployment”, Olemann said.

 


Brands are no longer making one campaign for one medium. They need multiple versions across Instagram, YouTube, connected TV, over-the-top platforms, short-video apps, quick-commerce platforms and performance channels. Each format demands a different cut, duration, language, design and call to action. That is where speed becomes the selling point.


A shortcut


Traditional video production is expensive as it involves multiple layers of creative and technical work. For SMEs, the production bill can often exceed the budget available for media distribution. AI tools promise to compress that process by generating scripts, visual drafts, edits, voiceovers, music and localisation options at greater speed.

 


Aditya Jangid, Managing Director, AdCounty Media, said, “Finally, AI is democratising the process of creating creative material for ads. Small businesses lacking access to expensive creative facilities can create professional-level advertisements using AI technologies.”

 


Olemann said AI-generated ads can deliver a high return on investment for SMEs by allowing faster production and freeing up budgets for distribution.

 


“It’s a mix of both. For an SME starting out, AI-generated ads can deliver high RoI by enabling faster production and freeing up budget for distribution. However, scaling is challenging; with rising token costs, producing hundreds of ads quickly leads to diminishing returns where production costs outweigh the benefits. If your primary goal is awareness, it is better to limit AI-generated content and prioritise investment in distribution,” she said.


Why India could adopt faster


India may be one of the natural markets for AI-generated advertising because of the combination of a fast-growing digital ad market, high video consumption, and language diversity.

 


An Indian advertiser may not need one national video. It may need the same offer in Hindi, Tamil, Telugu, Bengali and Marathi, with separate cuts for YouTube, Instagram, connected TV and commerce platforms. For regional brands, local language communication can make the difference between visibility and conversion.

 


“The most important benefit of using AI for video ads in Indian SMEs and regional brands will come from multilingual localisation. Videos can now be localised, dubbed and customised in several languages using less cost and with more efficiency. This is especially true of India, where consumer engagement becomes much better when there is communication in local languages,” Jangid said.

 


Early adopters are likely to come from sectors where digital performance marketing is already common. Jangid said e-commerce, D2C brands, fintech, edtech, travel, food delivery, gaming and real estate would likely be early users as they run high volumes of campaigns and require continuous testing of messages, visuals, and formats.


The slop problem


Where AI still struggles is the part advertising has always depended on: Emotional recall. With AI, cheaper creativity can become cheap-looking creativity very quickly. This is AI slop, where synthetic content is mass-produced mainly for scale, often with limited originality, weak emotional pull, and generic visuals. AI can make more ads, in more languages, for more platforms. What it cannot guarantee is memory.

 


Rahul Kashyap, Executive Director, PRP Group Pvt Ltd said the industry should be careful not to overestimate what AI can replace.

 


“What concerns me is the rush to overestimate what AI can replace. Advertising is a creative pursuit at its heart, and human insight is its core. If we shortchange that in the name of efficiency, we risk producing work that checks boxes and leaves no impression. Brand distinctiveness is not an output of automation. It is built through human choices, accumulated over time, and no algorithm changes that,” he said.

 


Jangid made a similar distinction between performance marketing and long-term brand building.

 


“But brand building needs emotional storytelling, cultural resonance and unique brand elements that build memorable structures in people’s minds. And in these areas, the power of human imagination remains crucial,” he added.

 


Olemann said many brands may use AI-generated ads because they lack the resources for long-term brand building. But she also warned that widespread AI adoption could dilute distinctiveness.

 


“While long-term brand building is ideal, many brands lack the resources to pursue it, making AI-generated ads a practical choice for short-term performance marketing. Currently, widespread AI adoption risks diluting brand distinctiveness, but rapidly evolving capabilities will soon allow for the creation of unique, brand-specific creative,” she said.


Trust, disclosure and brand safety


The concerns around AI-generated ads go beyond quality. They include misleading product claims, fake-looking product demos, synthetic testimonials, voice and likeness misuse, copyright issues around music and visuals, weak brand consistency, lack of disclosure and consumer mistrust.

 


These risks are particularly sensitive in categories such as healthcare, finance, education, luxury and products that rely heavily on credibility or expert claims.

 


Jangid said authenticity, transparency, copyright, disinformation and consumer trust will become more significant as AI-driven advertising becomes more common.

 


“One of the major threats will be the generation of misleading or manipulated content that will be difficult for consumers to identify as fake,” he said.

 


“Another issue will be the intellectual property rights concerns that will arise as AI models learn from copyrighted creative works. Brands will have to make sure that all the assets generated by artificial intelligence adhere to both legal and ethical standards to prevent any potential problems,” he added.

 


Olemann said disclosure should be a basic safeguard. “A critical safeguard is requiring AI platforms to automatically disclose when content is AI-generated. Given the potential for unethical use, such transparency is essential,” she said.

 


Jangid also called transparency crucial. “When it comes to synthetic media, AI-generated spokespersons or digitally manipulated media, consumers must know that they exist. Disclosure rules in the industry will be able to ensure transparency,” he said.

 


He said India will need to consider AI-generated content disclosures, data privacy and security regulations, accountability measures, intellectual property regulations and deceptive advertising restrictions. But he added that regulation should balance innovation and consumer protection.

 


“The goal should not be to limit the technology but to promote responsible AI adoption. In the end, trust will be the most valuable currency in the age of AI-driven advertising,” he said.


Agencies under pressure


It is unlikely that AI will kill legacy advertising agencies that have a solid creative foundation, but it may change where they make money. Lower-end production work such as first drafts, edits, cutdowns, resizing, localisation, dubbing and performance variants may increasingly be automated. That could put pressure on production revenue, especially for agencies that rely on volume-based creative work.

 


But agencies may still matter for strategy, brand voice, approvals, cultural relevance and risk control. As production becomes cheaper, clients may be more willing to pay for sharper thinking, supervision and governance.

 


Kashyap warned that governance will become a larger issue. “The bigger unresolved question is governance. AI currently operates without meaningful regulatory guardrails, and I believe that is going to change sooner than the industry expects. Regulatory bodies are paying close attention, and compliance frameworks are coming. When they arrive, they will define not just what is permissible but how accountability is demonstrated, enforced, and reported across every player in the ecosystem. The organisations that are already thinking about governance seriously, not just chasing capability, will be in a far stronger position when that moment arrives,” he said.


What to watch next


AI-generated ads will grow because the economics are attractive. They promise lower cost, faster turnaround, more personalisation, and measurable outcomes. For Indian SMEs, D2C brands and regional advertisers, they could make video advertising more accessible than before.

 


But the winners may not be the brands that produce the most ads. They may be the ones who use AI to produce relevant ads without sacrificing trust, originality, and distinctiveness.

 


Disney’s tool shows where advertising is headed: Video ads are becoming cheaper, faster and more self-serve. The challenge for brands will be to ensure that efficiency does not become the enemy of memory.



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China tightens indium metal's export scrutiny as AI demand increases

China tightens indium metal's export scrutiny as AI demand increases



China is stepping up scrutiny over exports of indium, leading some buyers to fear the niche metal, sought after for next-generation data centers, may be added to the export control regime that has become one of Beijing’s most potent trade weapons. 


China produces nearly 70% of the world’s indium, a byproduct of zinc refining mostly used in displays and solder but also the raw material for making indium phosphide, used to make high-speed optical chips for AI data centers. 


Beijing put indium phosphide on an export control list in February 2025 and the restrictions have become enough of a hurdle for next-generation data centers that the CEO of Nvidia-backed chipmaker Coherent traveled to Beijing with President Donald Trump in May to raise the issue. 

 


While indium metal is not on the export control list, two buyers told Reuters about growing scrutiny over their purchases from Chinese customs. For the first time this year, a European buyer was asked to disclose information about end users, including where they were based. 


A major buyer in North America said approvals had gone from same day to several days, which they attributed to more scrutiny of paperwork and described as “tense”. This buyer had not been asked for extra information by customs. 


China’s Ministry of Commerce did not immediately respond to a request for comment on a public holiday. 


All the buyers declined to be named owing to the sensitivity of the topic. 


The extra due diligence is not uniform and two other buyers told Reuters they had heard of extra scrutiny but not faced it themselves. So far, Reuters has not identified any shipments that have been blocked. 


Nonetheless there is some concern in the small industry that this is a prelude to tighter controls or the end-user disclosures which China, and other countries with export control regimes, use to chart global supply chains and chokepoints. 


Indium has been identified as a potential vulnerability for the U.S., whose Defense Logistics Agency earlier this year released a request for proposals to stockpile up to 403 tons of the material over three years. 


Another North American buyer said they suspected that the reporting requirements were “a precursor to restrictions or outright bans on exports.”

 



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RIL Chairman Mukesh Ambani pushes young engineers to build AI for India

RIL Chairman Mukesh Ambani pushes young engineers to build AI for India



Reliance Industries’ Chairman Mukesh Ambani on Friday placed the country’s engineering talent at the centre of Jio’s massive artificial intelligence push, calling on them to join forces to “build for India” as the Reliance Intelligence enters the next phase, of execution.


Asserting that India should not remain a mere consumer of AI built elsewhere, Ambani outlined Jio’s next growth chapter that pivots heavily toward artificial intelligence.


“I firmly believe that India should not be a mere consumer of AI created elsewhere. It must become a creator, adopter, and global leader in AI,” Ambani said while speaking at Reliance Industries’ 49th AGM.

 


He noted that Reliance Intelligence announced last year aimed to build a profitable AI infrastructure, platform, and services business serving consumers, enterprises, and governments at scale.


“We set out with a clear vision, identified the focus areas, and began building the right partnerships with Google, Meta, and NVIDIA. Now, we are entering the next phase — Execution,” he said.


Jio delivered on its promise made a decade ago of providing broadband connectivity to everyone, everywhere, and Reliance Intelligence is now promising AI to everyone, everywhere, he said.


“And we shall deliver on this promise too,” he added.


Ambani attributed the success of the Jio revolution to courage, creativity, and commitment of thousands of young Indian engineers who helped Jio in shattering the myth that the country could only import foreign technology.


“Before Jio, many believed that India could only import technology from the world. Our engineers proved otherwise. They built, tested, deployed, and operated technologies at an unprecedented scale,” Ambani said.


Today, Jio is not just integrating technology, it is creating original technology.


Reliance Intelligence offers an even bigger opportunity to young, promising engineers.


“They will get to work on problems of national scale and impact. They will build and deploy technology for 1.5 billion Indians. They will create India-born innovation that the world can adopt,” Ambani said.


Inviting them to “come, build with us, and build for India,” Ambani promised the scale, resources, and freedom to develop powerful, language-fluent, and affordable AI that empowers everyone from farmers to creators while actively driving productivity and job creation.


“…Come, build with us. And build for India. Build AI that serves humanity; AI that is powerful, trusted, yet affordable; AI that is fluent in every Indian language; AI that empowers farmers, students, doctors, shopkeepers, workers, creators, and families… We will give you the scale, the resources, the freedom, and the responsibility to solve some of the most important challenges of our age,” Ambani added.



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AI Assistant Market: The AI you use may depend on your phone, and work, not your preference

AI Assistant Market: The AI you use may depend on your phone, and work, not your preference



For the past few years, the question “which AI are you using” would likely have produced a common answer: ChatGPT, by default, for almost everything. That is no longer quite true. Market intelligence firm Sensor Tower’s State of AI 2026 report shows a market where Google Gemini, Anthropic’s Claude and a handful of others have carved out distinct audiences with distinct habits.

 


ChatGPT is still, by a wide margin, the AI assistant most people in the world use. It commands 1.11 billion monthly users worldwide, more than Google Gemini and Claude combined. However, the report’s data shows its market share has been on the decline, dropping below half for the first time since the generative AI boom began. At the same time, other platforms, including Claude and Google Gemini, have been gaining significant ground.

 
 


While this owes something to improving capabilities among the competition, it also has to do with what device a user is interacting with AI on, and what they are using it for. At least that is what insights from Seema Shah, VP of Insights at Sensor Tower, suggest.


The Android effect is real


Start with the most structural force driving the trend: the operating system itself. Google Gemini’s growth, from 285 million worldwide monthly users in May 2025 to 662 million by May 2026, has coincided with its deepening presence across Search, Gmail, Docs and Android itself.

 

Google, at its 2025 I/O conference, announced several new AI capabilities and deeper integration of Gemini into the Android operating system. These included Gemini Live’s camera and screen-sharing capabilities and deeper integration of Gemini into Google apps for cross-app functionality, among other features that rolled out on Android devices through the rest of the year.

 


“Android integration is clearly an advantage for Google Gemini and has likely contributed meaningfully to its growth,” Shah said. Roughly 81 per cent of Gemini’s users are on Android devices, compared with 70 per cent for ChatGPT, 61 per cent for Claude and 56 per cent for Grok, she noted, a gap that points to Google’s ecosystem and device integrations introducing Gemini to a large audience by default.


But that does not explain the whole story, according to Shah. “Gemini’s growth is not limited to Android,” she said. Looking only at iOS, where Google enjoys none of its Android advantages, Gemini remains one of the leading AI assistants. Between January and May 2026, it ranked second globally by downloads among AI assistant apps on iOS, behind only ChatGPT, and third by average monthly active users, behind ChatGPT and China’s Doubao. Its iOS MAU climbed more than 800 per cent year-on-year over that period.

 


Gemini’s popularity on iOS could be attributed to a number of reasons. For one, Google has been rolling out new Gemini features, such as Gemini Live’s camera and screen-sharing capabilities, to iOS almost as consistently as to Android. For another, Apple’s own portfolio of native AI features has remained limited, with the company only recently introducing its Siri AI assistant for iOS, leaving more room for a third-party assistant like Gemini to fill the gap.


Claude’s audience looks like a different market altogether


If Gemini’s story is about distribution, Claude’s is about who is actually opening the app. Claude’s worldwide monthly users went from 60.2 million in December 2025 to 245 million by May 2026, a roughly fourfold jump in five months that took its global market share from 3 per cent to 10.3 per cent. In India, the climb was just as sharp: 13.3 million users in December to 72.3 million in May, with market share rising from 2.2 per cent to 10 per cent.

 


Shah traced the growth to audience composition more than to any single event. “Claude has benefited from growing demand for AI assistants focused on professional, research, and developer use cases,” she said, adding that Sensor Tower’s traffic and audience data show Claude users have stronger ties to platforms such as GitHub and LinkedIn than users of many competing AI assistants, a pattern that points to particularly strong adoption among technical and professional audiences.

 


The report’s own traffic analysis backs this up, with GitHub and LinkedIn accounting for more than 2 per cent and nearly 2 per cent of Claude’s inbound traffic respectively, a meaningfully higher share than what feeds rival assistants.

 


However, Claude’s significant growth in recent months cannot be attributed entirely to user personas and specific use cases. As per the report, OpenAI’s agreement to work with the US Department of War triggered a wave of ChatGPT uninstalls in the United States, peaking at roughly 200 per cent above the app’s average in the week of March 9 to 15.

 


Shah pointed to this directly as a factor in Claude’s gains. “Claude gained traction in the US following backlash to OpenAI’s partnership with the Pentagon in late February,” she said. “Uninstalls for ChatGPT spiked in the following days and Claude recorded more US downloads than ChatGPT each day from March 1 to 5.” 


ChatGPT has led on daily downloads every day since, but the gap has stayed considerably narrower than it was before March, she added. By May 2026, Claude’s US market share had climbed to nearly 14 per cent, up from 5 per cent in December.

 


Anthropic’s own spending has played a part too, Shah said. “Anthropic has significantly increased its marketing investment. The company ramped digital advertising in late 2025 and into 2026 and was among the AI brands advertising during the Super Bowl, helping raise awareness among mainstream audiences.” That matters because it complicates a tidy narrative where Claude’s growth is purely organic, driven by word of mouth among engineers. Some of it was bought, the same way ChatGPT and Gemini buy attention.


Popular AI’s based on personas


The Sensor Tower report also showed that user profiles vary significantly across leading AI assistants. As per data on Android mobile app users in the US in Q1 CY2026, Grok users were more than four times as likely to be crypto traders, while Claude users were approximately three times more likely to use the AI for crypto trading. By contrast, ChatGPT and Google Gemini attracted a broader mix of users, suggesting a more mainstream audience base.

 


A few key findings from the report stand out:


  • Grok users are 4.33x more likely to fall into the Crypto Traders persona than the general population, while Claude users are 3.06x more likely to fall into the same category

  • Grok users are 2.42x more likely to use the AI for fitness-related suggestions than the general population

  • Grok users are also 2.42x more likely to use the chatbot for gig-related work

  • Copilot users are 3.44x more likely to fall into the Peer to Peer payers persona than the general population

  • Gemini users are 1.73x more likely to use the chatbot for shopping for sneakers than the general population

  • ChatGPT users are 1.35x more likely to be students than the general population


Generative AI platforms are taking this into account


Analysis of the top 50 ad creatives in the US this year, included in the report, suggests that companies are well aware their platforms are being used for specific use cases, and are tailoring marketing accordingly.

 


As per the report, ChatGPT expanded beyond education, with everyday-use creatives rising from 8 per cent in H1 CY2025 to 28 per cent in YTD (year-to-date) 2026. Meanwhile, student and learning creatives, which accounted for 54 per cent of top ads in H1 CY2025, no longer appeared among its leading campaigns.

 


Google Gemini and Microsoft Copilot, meanwhile, are focusing on distinct user needs, as per the report. Gemini doubled down on image generation and education, with the two categories accounting for 76 per cent of its top creatives in YTD 2026. Copilot, in contrast, emphasised practical utility, with everyday-use creatives increasing from 30 per cent in H1 2025 to 48 per cent in YTD 2026, and productivity-focused ads rising from 10 per cent to 24 per cent over the same period.


What you ask an AI may also depend on what device you use


Sensor Tower’s report is built on app and web traffic, not on what is actually said inside conversations. Microsoft’s analysis of 37.5 million Copilot conversations between January and September 2025, the largest study of its kind at the time, fills in some of that gap, and found that what people ask an AI for depends heavily on the device they are using. Health and fitness questions skewed toward mobile. Productivity and career conversations skewed toward desktop during the workday. Philosophical questions became more common late at night, and entertainment chatter dropped off sharply during work hours.

 


That distinction, between a desktop tool reached for during work and a mobile companion reached for everywhere else, maps reasonably well onto what Sensor Tower is seeing across assistants. Claude’s heavier tilt toward GitHub and LinkedIn traffic looks like a desktop, work-context pattern. Gemini’s dominance on Android, where it rides along on a phone someone is using for everything from maps to messaging, looks like the mobile, ambient-use pattern.

 


Neither study proves the other’s findings, but together they sketch a market where the assistant a person ends up using is shaped as much by when and where they are reaching for it as by which model they think is “best.”


Maturing market and revenue


AI has evolved well beyond an experimental tool for consumers. As per the Sensor Tower report, with business and professional use cases expanding, users are increasingly willing to pay for premium features and subscriptions.

 


Claude, with its focus on research and professional workflows, has seen average monthly revenue per user (ARPU) in the US rise from less than $0.50 in September 2025 to $2.76 in May 2026.

 


This is also evident in Claude’s user distribution. As of May 2026, 13.3 per cent of Claude’s iOS users in the US were subscribers, the highest share among AI platforms. By comparison, 8 per cent of ChatGPT users and 9.7 per cent of Perplexity users in the same demographic were subscribers.

 


Overall, global in-app purchase revenue from AI apps is projected to surpass $4.25 billion in the first half of CY2026, up 36 per cent half-over-half.

 


Against that backdrop, India’s revenue position is an uncomfortable data point in the report. The country is projected to log 5.82 billion hours of generative AI app usage in H1 CY2026, more than three times the 1.66 billion hours logged a year earlier. Yet India’s projected in-app purchase revenue from AI apps for the same half-year is just $38 million, against the worldwide total of $4.25 billion, under 1 per cent of global AI app revenue from one of the world’s largest and most engaged user bases.

 


Shah’s explanation is structural rather than AI-specific. “The gap largely reflects broader mobile market dynamics rather than anything unique to AI apps,” she said. “India is one of the world’s largest mobile markets by users, but it remains relatively under-monetised compared with markets such as the US, Japan, South Korea, and Western Europe. In 2025, India accounted for roughly 0.6 per cent of global mobile IAP revenue across iOS and Google Play, despite representing a much larger share of users.”

 


That said, the trend line is improving. Shah said that India’s mobile IAP revenue grew 130 per cent between 2020 and 2025, compared with 58 per cent globally, and the country climbed to 21st globally by IAP revenue in 2025, up from 26th in 2020.

 


AI apps specifically are doing better than the broader market might suggest. In May 2026, ChatGPT ranked third, Claude seventh, and Grok 25th among all of India’s top apps by IAP revenue, regardless of category, which Shah read as evidence that “while revenue per user remains lower than in more mature subscription markets, there is meaningful willingness to pay for premium AI services.”

 


Closing the rest of the gap, in her view, will depend on continued growth in digital payments, subscription adoption and higher-value use cases, with AI providers likely to lean on premium features, more capable models and localised offerings to convert more of their enormous user bases into paying subscribers.



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Your smart TV, camera, fridge, and vacuum are online. Who else is watching?

Your smart TV, camera, fridge, and vacuum are online. Who else is watching?


Walk through a modern household and count how many devices are connected to the internet. The smart TV in the living room remembers what you watched last night. The robot vacuum is creating a map of your home. The security camera above the front door streams footage to your phone. The smartwatch is charging beside the bed.

 


Each of these is an Internet of Things (IoT) device — an everyday object equipped with sensors, software and a persistent internet connection that allows it to send and receive data. At its core, the smart-home proposition is convenience. Devices automate repetitive tasks, respond to remote commands and reduce friction in everyday life.

 
 


Yet behind that convenience lies a question many consumers rarely consider: where does all that data go?

 


Every smart camera recording a doorway, every robot vacuum mapping a room and every voice assistant responding to a command is continuously exchanging information with servers located far beyond the home.

 


Most of the time, this flow of data goes unnoticed. But when security controls fail, the same systems designed to make life easier can become gateways to privacy breaches, surveillance and cyberattacks.

 


Concerns about connected devices are growing. A Wall Street Journal report highlighted how millions of internet-connected devices are being exploited to support cybercriminal operations. Separately, researchers examining AI-powered toys have raised concerns about data exposure within homes.

 


The common thread is simple: behind the convenience of smart devices lies a growing risk of hidden vulnerabilities that can expose homes, personal data and even entire networks.


Your home is now a network


The smart home is no longer a futuristic concept reserved for technology enthusiasts. It has quietly become part of everyday life.

 


Over the past decade, internet-connected devices have evolved from niche gadgets into mainstream household products. Wi-Fi routers, smart TVs, connected speakers, security cameras, baby monitors, smart doorbells, streaming devices and robot vacuums now occupy spaces once filled by traditional appliances.

 


For many consumers, connectivity is no longer a premium feature. It is an expectation.

 


Falling data costs, improved internet connectivity and affordable hardware have accelerated adoption across urban households. Smart TVs are commonplace, app-connected security cameras are increasingly used in homes and small businesses, and voice assistants have become fixtures in living rooms and kitchens. Robot vacuums are also gaining popularity among upper-middle-class households.

 


The appeal is straightforward: convenience, automation and remote access.

 


What often goes unnoticed is that every smart device is effectively a small computer connected to the internet. Much of the data these devices collect is transmitted to cloud servers operated by manufacturers.

 


While consumers focus on the device sitting in their homes, cybersecurity experts argue that the greater risk often lies in the cloud infrastructure powering it.

 


The invisible language of smart devices


To understand how smart devices can be compromised, it helps to understand how they communicate.

 


Many IoT devices, including robot vacuums, smart cameras, thermostats and baby monitors, rely on a communication standard known as MQTT, short for Message Queuing Telemetry Transport.


Originally developed for industrial environments such as oil pipelines and satellite systems, MQTT has become widely used in consumer devices because it is lightweight, efficient and easy to implement.

 


Think of MQTT as a postal service for machines.

 


Devices do not communicate directly with one another. Instead, they send messages to a central server known as a broker. The broker organises these messages into labelled channels called topics.


A robot vacuum may publish information about its battery level, cleaning status and camera feed to a specific topic. A smartphone application subscribed to that topic then receives the data.

 


The system works efficiently, but it relies on one critical assumption: that the broker only allows authorised devices and users to access relevant information.

 


This is enforced through access-control rules that determine who can read or write data to specific topics. When those rules are configured correctly, the system functions as intended. When they are not, sensitive information can become exposed.


What exactly is a backdoor?


The term “backdoor” often evokes images of secret access mechanisms hidden inside devices. In reality, it refers to a broader range of security weaknesses.

 


One form is accidental. These vulnerabilities emerge through poor engineering rather than malicious intent. This is what happened in the case of DJI’s Romo robot vacuum.

 


A software engineer discovered he could access thousands of devices because access controls had not been configured correctly. Using a legitimate login token, he connected to DJI’s servers expecting to see only his own device. Instead, he was presented with data linked to thousands of others.

 


No sophisticated hacking was required. The system simply failed to verify whether he was authorised to access the information.

 


The second type of backdoor is more concerning: software intentionally embedded into devices.


Security researchers have documented cases involving inexpensive smart TVs, digital picture frames and streaming devices that contained software enabling third parties to use a homeowner’s internet connection without their knowledge.

 


Once connected to a home network, such software can establish links to external servers and quietly route internet traffic through the household connection.

 


The device continues performing its advertised function, but it may also be supporting activities the owner never authorised.


The DJI Romo robot vacuum case


The risks associated with connected devices became particularly visible earlier this year through an incident involving DJI’s Romo robot vacuum.

 


Software engineer Sammy Azdoufal was attempting to control his vacuum using a PlayStation 5 controller. To achieve this, he examined how the device communicated with DJI’s cloud infrastructure through MQTT.

 


Instead of accessing only his own device, he discovered that DJI’s servers were exposing information linked to thousands of other vacuums worldwide. The issue was not caused by sophisticated hacking. Azdoufal was using a valid authentication token associated with his account. However, the company’s MQTT broker lacked adequate access controls.

 


Reports suggested that information from approximately 7,000 devices across more than 20 countries was potentially exposed. The data reportedly included floor maps, camera feeds, audio streams and other device information. Importantly, the vulnerability was not caused by a weakness in MQTT itself or by encryption failures. The problem lay in server-side authorisation.

 


Encryption protects data while it is being transmitted. Authorisation determines who is permitted to access that data. In this case, the authorisation controls failed.

 


DJI later acknowledged the issue and implemented server-side fixes. Because the flaw existed within the company’s cloud infrastructure rather than the devices themselves, users did not need to install software updates.

 


The incident highlighted an important reality: in connected homes, the greatest security risks may reside not within the device itself, but within the cloud systems managing it.


The device you bought may be working for someone else


To understand how hidden software can operate inside connected devices, Wall Street Journal reporter Jack Gillum conducted a simple experiment. He purchased five inexpensive internet-connected devices, including digital picture frames and streaming boxes, from major retailers. Soon after connecting them to a test network, unusual internet traffic began flowing through the connection.

 


Activity linked to gambling websites, cryptocurrency services and attempts to access online accounts appeared to be routed through the network, despite no one in the household initiating it.


Researchers later found that the devices contained residential proxy software. This software effectively turns a consumer’s internet connection into part of a commercial proxy network, allowing paying customers to route their traffic through genuine residential IP addresses.

 


In practice, the homeowner unknowingly becomes an intermediary for someone else’s online activity.

 


Experts cited in the report suggested that some manufacturers may be paid to include such software before devices are sold, while other infections spread through malicious applications. Either way, the outcome is the same: a device purchased for convenience becomes part of a hidden digital infrastructure.

 


Researchers found evidence that some devices were being used in distributed denial-of-service (DDoS) attacks, while others were receiving repeated login attempts from external actors. Law-enforcement officials cited in the report linked residential proxy networks to activities including fraud, ticket scalping and cyberattacks.


When the toy is listening


The issue becomes even more concerning when the device belongs to a child. AI-powered toys and interactive companions capable of holding conversations with children are becoming increasingly popular.

 


In June 2026, Cybernews researchers analysed Android applications associated with popular AI toys, including Miko, Loona, Dash & Dot and Sphero. Their findings raised several concerns. Nearly half of all permissions requested by the applications were classified as “dangerous” under Android’s security framework. All 10 applications requested precise location access. Six requested microphone access and five requested camera access.

 


One application, Loona, also requested background-location access, allowing it to track a user’s location even when the application was not actively being used. Researchers also identified tracking software embedded within many of the applications.

 


Trackers were found in seven of the 10 apps examined. While some were used for analytics and crash reporting, others were designed for advertising and profiling.

 


The Miko application stood out, requesting nine dangerous permissions and containing eight embedded trackers.

 


Researchers noted that data minimisation is particularly important for children’s applications because young users are less likely to understand what information is being collected and how it may be used.


Convenience comes with a cost


The common thread running through these incidents is not necessarily a flaw in a single product. Rather, they reflect a broader issue within the connected-device ecosystem. As manufacturers race to add features and connectivity, security has often lagged behind.

 


Consumers tend to focus on the physical device sitting in their homes, but much of the activity takes place in cloud systems that store data, process commands and enable remote access. When those systems are not secured properly, vulnerabilities can emerge at scale. 


Encryption remains important, but it is only one layer of protection. Equally important are the controls that determine who can view, modify or interact with data once it reaches the cloud. Modern smart devices increasingly contain cameras, microphones, location services and mapping technologies capable of collecting highly sensitive information.

 


Security researchers have repeatedly demonstrated how weak authentication systems, misconfigured servers and excessive permissions can expose that information to unauthorised parties. The reality of connected living is that the greatest risk may not be the gadget sitting on a shelf but the invisible network of servers supporting it.

 


Every smart device requires consumers to place trust in manufacturers — trust that their infrastructure is secure, access is restricted appropriately and personal information is protected. The convenience offered by connected devices is undeniable. But recent incidents serve as a reminder that convenience often comes with an unseen trade-off.

 


As smart homes become more common, the challenge for both consumers and manufacturers will be ensuring that connectivity does not come at the expense of privacy and security.



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