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Baidu Bets Big on AI Comeback as Advertising Slump Deepens and Ernie Falls Behind Rivals

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Baidu is entering a critical phase of its artificial intelligence transition, with CEO Robin Li promising to restore the company’s Ernie model to the frontier of AI even as the deterioration of its traditional advertising business weighs heavily on revenue and profit.

The Chinese search and technology giant reported second-quarter revenue of 31.33 billion yuan ($4.7 billion), down 4% from a year earlier and below the 31.96 billion yuan expected by analysts, according to LSEG data. Its U.S.-listed shares fell sharply after the results.

The numbers expose the central tension in Baidu’s strategy: the company’s AI businesses are growing rapidly, but not yet fast enough to compensate for the decline of the advertising franchise that built its business.

Online marketing revenue fell 19% to 13.1 billion yuan in the quarter as weak consumer spending and the prolonged property downturn encouraged companies to reduce marketing budgets. The weakness shows how exposed Baidu remains to China’s broader economic slowdown, particularly because advertising demand tends to weaken when businesses become more cautious about spending.

At the same time, Baidu’s AI-powered businesses are becoming an increasingly important part of the company. Revenue from Baidu Core AI-powered Business reached 12.5 billion yuan, up 25% from a year earlier and equivalent to roughly half of Baidu General Business revenue. AI Cloud Infrastructure revenue rose 50% to 7.3 billion yuan, while GPU Cloud revenue surged 283%, accelerating from 184% growth in the first quarter.

That GPU growth is notable because it indicates that Baidu is benefiting from the broader AI infrastructure spending cycle even while its consumer-facing businesses struggle. Companies are now purchasing computing capacity for model training and inference, creating a potentially significant new revenue stream for Baidu’s cloud operations.

The shift also changes the nature of Baidu’s AI opportunity. The company does not necessarily have to win the chatbot market outright for its AI strategy to succeed. It can monetize AI through cloud computing, model services, enterprise applications, advertising products and other infrastructure.

But Ernie remains strategically important because the strength of Baidu’s foundation models can determine how much of that ecosystem the company controls.

That is where the company faces a growing problem.

Ernie has gone months without a major upgrade, while competitors such as Alibaba and Moonshot AI have continued to introduce newer models. China’s AI market has moved rapidly toward open-weight models, capable reasoning systems and AI agents, raising the standard that Baidu must meet to remain a leading model provider.

Li’s response was unusually direct. He told analysts that Baidu intends to bring Ernie back to the AI frontier and continue investing in leading talent and technology.

“In a market like this, we believe long-term competitiveness ultimately comes down to sustained technology investment, application-driven approach, and patience,” Li said.

That statement points to a potentially expensive second phase of Baidu’s AI strategy.

The company has already been investing heavily in computing infrastructure and personnel. Its capital expenditure increased sharply in the quarter, with spending on AI chips and data centers adding to the financial burden of the transition.

But it comes at a difficult time. Baidu is being asked to spend more on AI precisely when its legacy business is producing less cash and its profitability is deteriorating. Net income fell to about 2.3 billion yuan from 7.3 billion yuan a year earlier. The decline illustrates the cost of maintaining an expensive AI infrastructure push while the advertising engine contracts.

Still, Baidu has financial resources to sustain the investment. The company reported 283.1 billion yuan in cash and investments at the end of June and generated 3.4 billion yuan in operating cash flow during the quarter.

The more important question is therefore not whether Baidu can afford to invest in AI. It is whether those investments can generate returns quickly enough to offset the structural deterioration of its older businesses.

This matters because China’s AI competition is becoming less forgiving.

Alibaba has been expanding its Qwen model family and pushing open-weight AI, while DeepSeek, Moonshot AI and other Chinese developers have been releasing models that compete aggressively on cost, coding, reasoning and agentic capabilities. The competitive landscape means Baidu cannot rely on its early position in China’s generative AI market.

Its challenge is also broader than simply improving benchmark scores.

Baidu needs Ernie to become commercially useful across an ecosystem that includes cloud computing, search, enterprise software and AI applications. A stronger model could improve the company’s ability to monetize search queries, attract developers, increase cloud demand and create new enterprise products.

That makes the model upgrade promised by Li strategically important well beyond the chatbot itself.

There is also a potentially important change occurring inside Baidu’s revenue mix. The company’s AI-powered business has grown from an emerging segment into roughly half of its general business revenue. Yet AI applications revenue was only about 2.5 billion yuan in the second quarter, broadly flat from a year earlier, while AI Cloud Infrastructure provided much of the growth.

That suggests Baidu’s AI monetization is currently being driven more by infrastructure demand than by rapidly expanding consumer AI applications.

The distinction carries implications for the company’s future margins. Cloud infrastructure can produce substantial revenue, but it requires expensive computing hardware and data-center capacity. A successful foundation model, by contrast, could potentially generate higher-margin revenue through software, subscriptions, advertising and enterprise applications once the underlying technology has been developed.

Baidu therefore needs to move from selling the infrastructure required for the AI boom to capturing more of the value created by the applications built on top of it.

Its advertising business adds urgency to that transition.

Baidu’s traditional search model is vulnerable to changes in how consumers obtain information. If users increasingly turn to AI assistants for answers rather than conventional search results, generative AI could disrupt both the technology and economics of the company’s historic core. That creates a paradox for Baidu. AI is simultaneously the technology threatening to reshape its search business, and the technology it hopes will create its next major growth engine.

The company is consequently attempting to replace one business model while defending another, all during an unusually intense period of competition.

The second-quarter figures show that the transition is already underway. AI-related revenue is growing at double-digit rates, GPU Cloud demand is accelerating, and AI now accounts for a substantial portion of Baidu’s core business. Yet total revenue continues to fall because the legacy advertising business is contracting faster than the new businesses can expand.

That makes the next phase of Baidu’s AI strategy a test of execution rather than ambition.

Li has made clear that Baidu intends to spend the money and accept the patience required to regain technological ground. The investment could eventually strengthen the company’s position across cloud, search and enterprise AI.

But the company must demonstrate that Ernie can once again compete with China’s fastest-moving models and that Baidu can turn that technological capability into profitable products.

Bitcoin Reclaims $65,000 as Markets Rebound

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Bitcoin climbed back above the $65,000 level, marking its first return to that threshold since early this month.

The move came during a broader rebound in risk assets and followed several days of tight trading between roughly $62,000 and $65,000.

Bitcoin has spent months stuck in a prolonged slump that pushed many retail traders out of the market, drained billions from crypto investment funds, and even turned some of its largest traditional buyers into net sellers.

Amid this weakness, a familiar group of deep-pocketed participants has begun to reappear as buyers; Bitcoin whales. Recent price action showed Bitcoin building on recent gains after Wall Street opened. Data indicated the cryptocurrency briefly pushed to or through $65,000 before consolidating near the high end of its recent range.

This occurred against a backdrop of reduced expectations for an aggressive Federal Reserve rate hike and a weaker dollar, both of which typically support risk assets including crypto.

The advance also coincided with statements confirming the Strait of Hormuz remained open and operating, helping ease some geopolitical pressure that had weighed on markets earlier. U.S. equities, including the S&P 500, showed signs of recovery from recent lows at the same time, providing additional tailwinds for Bitcoin.

Despite the short-term strength, Bitcoin remains well below its late-2025 peaks near $125,000. The market has spent much of recent months consolidating in a lower range after a significant pullback.

Traders and analysts have pointed to the $63,000–$65,000 zone as a key decision area. Holding above $63,000 has been viewed as constructive for further upside, while a clean break and sustained move beyond $65,000–$65,700 could open the path toward higher targets in the mid-to-high $60,000s.

Demand dynamics remain mixed. Spot Bitcoin ETF flows have shown periods of outflows in recent weeks, raising questions about the strength of institutional buying near current levels.

At the same time, reduced selling pressure on exchanges and cooler leverage metrics have helped support the rebound. Lower exchange inflows and a pause in aggressive short positioning contributed to the ability of price to push higher without immediate heavy resistance.

Technical structure has improved modestly. Bitcoin broke a multi-week downtrend line and reclaimed important moving averages near $64,000.

Momentum indicators shifted into more constructive territory, though the market remains range-bound overall. Key support continues to sit in the low $63,000s and around $61,000, while resistance clusters near recent highs and the $65,500–$67,000 area.

The $65,000 level carries both psychological and technical weight. Repeated tests of this zone in recent weeks have made it a focal point for traders.

A sustained hold above it would strengthen the case for a more durable recovery, while failure to maintain the level could return price to the lower end of the recent consolidation range.

The broader backdrop remains challenging. Bitcoin is still trading well below its 2025 highs and sits more than 40% lower on a year-over-year basis. Retail participation has thinned, and several crypto funds have seen significant outflows.

Yet the return of whale buying is being watched closely by those looking for early signs that a longer-term bottom may be forming. Large holders accumulating during periods of low retail interest and weak sentiment has historically reduced the liquid supply available on the market and sometimes preceded stronger price recoveries.

On-chain metrics reinforce the picture of restrained selling pressure. Total balances held by the largest cohorts have climbed from earlier lows, even if they remain below previous cycle peaks. Long-term holders continue to show little appetite to sell, with a growing share of Bitcoin remaining dormant for extended periods.

While whale accumulation alone does not guarantee an immediate rally, it removes a meaningful amount of Bitcoin from active circulation.

As of the latest trading, Bitcoin continues to hover near the upper end of its short-term band. Market participants are watching whether the current rebound can attract fresh demand or whether the $65,000 area once again acts as a ceiling.

The combination of improving macro signals, easing geopolitical concerns, and technical progress has given bulls a window of opportunity, but confirmation will depend on follow-through in the sessions ahead.

Pony.Ai Builds 4,000-Vehicle Overseas Robotaxi Pipeline As China’s Autonomous Driving Firms Go Global

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Chinese autonomous driving company Pony.ai is building an overseas robotaxi pipeline of more than 4,000 vehicles as it accelerates international expansion, seeking to turn advances in China’s highly competitive autonomous driving market into a global commercial opportunity.

The company said on Tuesday that the vehicles have already been contracted, although deployment schedules will depend on regulatory approvals, operating permits and other local requirements. Pony.ai did not disclose how many of the vehicles are already operating outside China or provide a timeline for completing the deployments.

The expansion comes as Chinese robotaxi companies look abroad for growth. Competition in their home market is intensifying, while regulatory and technological progress is opening opportunities in the Middle East, Europe and other Asian markets.

Pony.ai is targeting a global robotaxi fleet of 3,500 vehicles by the end of the year.

Europe Emerges As A Major Battleground

Pony.ai last week announced plans to deploy more than 2,000 robotaxis across Europe through an expanded partnership with Uber, marking one of its most significant overseas expansion initiatives.

The broader pipeline of more than 4,000 vehicles indicates that the Uber deployment is only part of the company’s international strategy.

Chief Executive James Peng said during an earnings call that all of the vehicles in the overseas pipeline had already been contracted, but their rollout would depend on securing the necessary permits and meeting operational requirements in individual markets.

The approach highlights one of the biggest constraints facing autonomous driving companies: having the technology is only one part of commercialisation. Companies must also navigate different rules governing autonomous vehicles, passenger safety, insurance, mapping, data and liability across jurisdictions.

Pony.ai’s international ambitions are being supported by rapid growth in its robotaxi business. The company reported second-quarter revenue of $36.2 million, an increase of 68.8% from a year earlier. Its net loss narrowed 14.9% to $45.4 million.

The strongest growth came from robotaxis. Robotaxi revenue surged 691.2% year-on-year and accounted for about one-third of total company revenue for the first time.

Pony.ai said it remains on track to generate more than 3.5 times its 2025 robotaxi revenue this year.

“We will continue to advance our full-year plans and are confident in our ability to exceed our full-year robotaxi services revenue target,” Peng said.

The numbers point to an important shift for the company. Robotaxis are moving from a technology demonstration and pilot project toward a meaningful commercial business, although Pony.ai remains loss-making as it spends heavily on autonomous-driving technology and fleet deployment.

Pony.ai is not alone in pursuing overseas markets.

Rival WeRide is also examining expansion opportunities in Australia, South Korea, Japan and Southeast Asia. The international push reflects a broader strategy among Chinese autonomous-driving companies to diversify their revenue sources as competition at home intensifies.

China has become one of the world’s most active markets for autonomous driving, giving local companies access to large passenger and vehicle datasets, dense urban environments and an increasingly mature electric-vehicle ecosystem.

That domestic scale can help companies improve their technology and lower operating costs. But it also means several companies are competing for partnerships, passengers and regulatory approvals in the same market.

International expansion offers a way to increase the addressable market and establish commercial relationships before competitors secure key territories.

Robotrucks Provide Another Growth Avenue

Pony.ai is also expanding beyond passenger transportation. Revenue from its robotruck business increased 40% year-on-year in the second quarter, as the company develops autonomous heavy-duty and light-duty vehicles for commercial applications.

The company aims to deploy between 500 and 1,000 autonomous heavy-duty trucks in China within two to three years. It also plans to scale its driverless light-duty truck fleet to 100,000 vehicles by 2030, according to its robotruck chief, He Xing.

The robotruck market could ultimately provide a different commercial model from robotaxis. Freight operators can potentially benefit from autonomous vehicles through higher utilization, lower labour costs and more predictable logistics operations, making the economics potentially attractive even before fully autonomous passenger transport becomes widespread.

Pony.ai’s 4,000-vehicle pipeline should therefore be viewed as a measure of contracted demand and expansion potential rather than an indication that thousands of robotaxis will immediately begin carrying passengers.

But each deployment must clear local regulatory and operational hurdles, and autonomous driving rules differ significantly between countries.

For Pony.ai and its rivals, the next phase of competition will consequently involve more than developing capable autonomous systems. Securing government approvals, local partners, fleet infrastructure and commercial contracts will be equally important.

If Pony.ai can convert a substantial portion of its overseas pipeline into operating fleets, the company would gain an important foothold in markets outside China while accelerating the transition of robotaxis from experimental services into a global transportation business.

Perplexity’s Airtel Giveaway Shows India Can Drive AI Growth, but Monetization Remains the Test

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Perplexity’s year-long giveaway of its premium AI service to millions of Airtel customers is emerging as an important early test of whether AI companies can turn free access into durable usage and, eventually, paying customers in India.

The experiment generated a huge increase in Perplexity’s reach, according to TechCrunch. But as the first free subscriptions expire, the data presents a more complicated picture: downloads have collapsed, while user activity and revenue remain well above pre-promotion levels.

That distinction could be important for an AI industry increasingly using free trials, discounted plans and telecom partnerships to accelerate adoption in price-sensitive markets.

Perplexity began the experiment in July 2025 through a partnership with Airtel, India’s second-largest telecom operator. Airtel’s roughly 360 million customers were offered a 12-month subscription to Perplexity Pro, which normally costs about $200 a year.

New redemptions ended on January 16, but customers retained access for a year from the date they activated the offer. The earliest participants therefore began reaching the end of their free subscriptions in July and faced renewal charges unless they canceled.

The promotion immediately transformed Perplexity’s position in India.

According to Sensor Tower data shared with TechCrunch, the company’s app recorded 5.9 million downloads in India in July 2025, a 625% increase from June. The figure was also greater than the 5.4 million downloads Perplexity had accumulated during the entire first half of 2025.

The growth continued well beyond the initial launch.

Perplexity recorded an estimated 56 million downloads in India during the seven months in which new customers could claim the Airtel offer, more than nine times the number recorded during the preceding seven-month period.

Monthly active users more than doubled to 8.9 million in July and eventually reached about 22 million in October.

The Free Users Did Not Simply Disappear

The more revealing part of the experiment began after the promotional window closed. Perplexity’s Indian downloads fell sharply once new customers could no longer claim the free subscription. Sensor Tower estimates that the company recorded 3.3 million downloads between February and July, a decline of more than 90% from the previous six months.

Yet usage remained considerably higher than before the Airtel partnership.

Monthly active users stood at nearly 14 million in July, down 37% from the October peak but still more than five times the roughly 2.6 million monthly users Perplexity averaged during the first half of 2025.

“While the time-sensitive nature of this promotion would naturally lead to a decline in adoption after the offer period, ongoing usage has remained resilient,” said Abe Yousef, senior insights analyst at Sensor Tower.

Perplexity, he said, now has “significantly more users” in India than it did before the promotion.

That suggests the giveaway may have done something more valuable than simply generate a temporary download spike. It appears to have introduced millions of Indian consumers to Perplexity and created a larger installed user base that persisted after the promotion ended.

The bigger question is whether that user base can be monetized.

Revenue Is Rising As Downloads Fall

Early revenue data offers an encouraging signal for Perplexity. Sensor Tower estimates that the company’s Indian in-app purchase and subscription revenue between February and mid-August increased about 60% compared with the period when new users were still able to claim the Airtel offer.

The increase has continued as the first free subscriptions have begun expiring.

Between July 18 and August 12, Perplexity’s average daily in-app purchase revenue in India was 9% higher than during the preceding 30 days and 27% above the average recorded during the first half of 2026. That creates an important divergence: Perplexity is acquiring far fewer new users, but the users already on the platform appear to be generating more revenue.

However, the figures do not establish that former Airtel users are converting to paid Perplexity Pro subscribers. The free subscriptions were configured to renew automatically, meaning users who did not want to continue had to cancel before their renewal dates. Some of the increase in revenue could therefore come from customers who simply failed to cancel.

Sensor Tower cannot distinguish between those users and customers who deliberately decided to pay after their free year ended. It also cannot isolate former Airtel subscribers from Perplexity’s other paying customers in India.

That makes the coming months more important than the initial revenue increase.

Data from another app intelligence company, Appfigures, suggests the Airtel partnership produced growth that was specific to Perplexity rather than simply reflecting a broader surge in demand for AI applications.

“I compared Perplexity’s downloads to ChatGPT and Claude to ensure it wasn’t more appetite for AI, and it wasn’t,” said Ariel Michaeli, co-founder and CEO of Appfigures.

Before the promotion, Perplexity averaged about 11,200 daily downloads in India during the week before its launch. That increased roughly twentyfold to nearly 223,000 downloads per day during the first week of the promotion.

The pace continued increasing, reaching approximately 305,000 daily downloads between mid-September and mid-October.

Downloads of OpenAI’s ChatGPT and Anthropic’s Claude remained broadly stable over the same period, according to Appfigures.

Appfigures also estimates that Perplexity’s monthly net mobile revenue in India increased from approximately $34,000 in January 2025 to $70,000 in December and $156,000 in July 2026.

The company generated an estimated $878,000 in India during the first seven months of 2026, 16% more than it generated during the whole of 2025.

Michaeli cautioned, however, that the increase cannot automatically be attributed to Airtel users converting into paying customers. The enormous visibility created by the promotion could also have attracted paying customers who never participated in the giveaway.

India Has Become The AI Industry’s Growth Laboratory

The significance of Perplexity’s experiment extends beyond one company. India has become the world’s largest market for generative AI app downloads, helped by its huge population, more than a billion internet users, relatively inexpensive mobile data, and a smartphone market of more than 700 million users.

But converting that enormous audience into revenue is considerably harder. Consumers in India are generally more price-sensitive than users in wealthier markets, making the country attractive for companies willing to subsidize access in exchange for scale and long-term user acquisition.

Perplexity’s Airtel experiment has since been followed by even greater promotional efforts.

OpenAI made its lower-priced ChatGPT Go plan available free for a year in India in August 2025. Google subsequently partnered with Reliance Jio to provide eligible customers with free access to its AI Pro subscription for 18 months.

The emerging model is therefore becoming increasingly clear: telecom operators provide distribution at enormous scale, while AI companies absorb much of the initial cost of acquiring users.

The bet is that once consumers incorporate an AI assistant into their daily routines, some will eventually become willing to pay for continued access.

That is a very different proposition from simply maximizing downloads.

The Real Test Starts Now

Perplexity’s Airtel deal appears to have succeeded at the first stage of the experiment. It dramatically increased awareness, downloads, and active users and appears to have left the company with a substantially larger Indian user base than before.

The second stage is considerably harder.

The company must determine how many of those users are willing to pay when they lose access to the free premium service. That conversion rate will determine whether the billions of dollars potentially spent by AI companies subsidizing users in India represent customer acquisition investments or simply expensive giveaways.

There is also a retention question. Users who became accustomed to Perplexity Pro for a year may continue using the service, but they have alternatives. ChatGPT, Claude, Gemini, and other AI services are competing aggressively for the same users, often with their own free tiers and promotional offers.

That makes habit formation crucial. If consumers use Perplexity because it has become part of their regular search and information workflow, a meaningful share may be prepared to pay. If they primarily used it because Airtel made the premium product free, conversion could be much weaker.

The Airtel cohort will provide one of the clearest early indicators of whether AI companies can successfully move from subsidized distribution to sustainable consumer revenue.

For Perplexity, the most encouraging signal so far is not the 56 million downloads generated during the promotion. It is that nearly 14 million people were still actively using the service in July, even after downloads had collapsed.

But the decisive metric will be the number of those users who continue paying after their free year ends.

The experiment has therefore moved from an acquisition story to a monetization test. Over the coming months, as successive groups of Airtel customers reach their renewal dates, the industry will get a much clearer picture of whether India’s enormous appetite for AI can finally translate into the recurring revenue that AI companies need.

OpenAI Launches ChatGPT for Teens With New Safety and Anti-Cheating Measures

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OpenAI is launching a dedicated ChatGPT experience for teenagers with additional safety protections and education-focused tools, as the company faces growing scrutiny over the risks of AI chatbots for young users and the use of generative AI in schools.

The new ChatGPT for Teens experience, announced Monday, will introduce age-appropriate safeguards designed to limit teenagers’ exposure to harmful or developmentally inappropriate content. It will also incorporate tools intended to make ChatGPT function more as a learning assistant than a shortcut for completing schoolwork.

The launch comes after a series of lawsuits and public concerns alleging that AI chatbots can contribute to serious mental-health problems among young people, including cases involving teen suicides. Those legal and societal pressures have increased scrutiny of how AI companies protect minors as chatbot adoption has expanded.

OpenAI says the new protections will be enabled by default for teen users. The company said they are based on its Under-18 Principles in its Model Spec, which it says draw on developmental science and guidance from experts.

The move also addresses a separate problem that has emerged in schools: students using ChatGPT to complete assignments without actually learning the underlying material.

A central feature of the teen experience will be Study Mode, which is designed to guide students through problems rather than simply provide answers. Instead of immediately producing a solution, ChatGPT can use guiding questions and step-by-step assistance to encourage students to work through the material themselves. The system will also support quizzes and learning visualizations.

OpenAI is additionally introducing homework reminders that can appear when the system detects that a teenager may be attempting to use ChatGPT to obtain an answer rather than understand the material. In those situations, the chatbot will encourage the student to switch to Study Mode.

Parents and guardians will have additional controls, including the ability to determine when Study Mode should be enabled by default. Existing family tools will allow parents to manage settings, receive safety notifications, and establish Quiet Hours.

The effectiveness of those safeguards, however, will depend heavily on how reliably OpenAI can identify a user’s age and how difficult it is for teenagers to circumvent restrictions.

Teenagers are often capable of finding ways around parental controls and other digital restrictions, making enforcement a significant challenge for any platform. OpenAI’s system will therefore face a practical test between the protections it has designed and the ways young users actually interact with the technology.

The company has not yet demonstrated publicly how resistant the new system will be to attempts to circumvent its safeguards. That raises a broader question about the timing of the initiative.

ChatGPT was launched in late 2022 and has since grown into one of the world’s most widely used AI services. Meaningful protections specifically designed around teenage users are arriving only after the chatbot has already reached enormous scale.

AI companies have faced enormous challenges in developing general-purpose systems that can serve adults, students, and younger users while maintaining different standards of safety and access.

The risks are significant for teenagers because AI systems can produce convincing but incorrect information, reinforce problematic interactions or respond inappropriately to sensitive subjects. A system designed primarily for adults cannot necessarily be assumed to be suitable for younger users simply because the underlying technology is the same.

OpenAI is therefore attempting to move toward a more age-specific model in which the chatbot’s behavior and available controls vary according to the user’s age. The company is also expanding efforts to improve AI literacy among young people.

The ChatGPT maker announced a partnership with CodeAI to help teenagers understand how AI systems work, how to direct and question them, and how to use the technology more effectively.

The educational strategy extends beyond individual users. OpenAI already offers ChatGPT for Teachers, providing schools with institution-managed access to AI and tools intended to help educators incorporate the technology into classrooms.

The combination of Study Mode, parental controls, and AI education suggests OpenAI is trying to shift the debate from whether teenagers should use AI to how they should use it. That is becoming increasingly important as schools struggle to establish rules around AI-assisted assignments. Banning chatbots outright has proved difficult to enforce, while unrestricted access can make it easier for students to outsource homework and other academic work.

OpenAI’s approach instead seeks to make the chatbot an intermediary in the learning process. The company wants students to use AI to understand concepts, test their knowledge, and work through problems rather than simply receive finished answers.

However, a student determined to avoid learning can still seek direct answers, use another AI system, or potentially find ways around restrictions. Likewise, identifying when a user is genuinely struggling with homework versus deliberately attempting to cheat is not always straightforward.