Tesla will tentatively begin offering public rides in driverless robotaxis in Austin, Texas on 22 June, according to Elon Musk, marking the long-delayed debut of a service he first promised back in 2019.

A Delayed Vision Finally Approaches Reality

Tesla (and SpaceX) boss Elon Musk has been claiming for years that fully autonomous Teslas were just around the corner. For example, in 2019, he said Tesla would have a million driverless cars on the road by 2020. Instead, the company spent years refining its Full Self-Driving (FSD) software and shifting its hardware strategy, meaning that the commercial robotaxi launch never materialised, until now.

Rollout in Austin, Texas

Musk now says that Tesla’s planned launch in Austin will involve a small fleet of around 10 to 20 Model Y SUVs operating within a geofenced zone of the city. These vehicles will use what Musk has called “FSD Unsupervised”, meaning they are intended to operate without a human driver behind the wheel. Musk stated in a post on X: “Tentatively, June 22. We are being super paranoid about safety, so the date could shift.”

Spotted

The announcement came just days after testing vehicles were spotted in southeast Austin with the word “Robotaxi” printed on them. In a separate post, Musk also claimed that from 28 June, “the first Tesla that drives itself from factory end of line all the way to a customer house” will take place, something he has described as a major milestone in autonomous production.

What Exactly Is a Robotaxi?

A robotaxi is a fully autonomous vehicle that provides taxi services without a human driver. The idea is that a customer can summon a vehicle via an app, ride to their destination, and exit, all without interacting with a human operator. Tesla’s version of the service will begin in a limited area, with remote monitoring for safety.

Following Waymo and Cruise

It should be noted that Tesla is not the first company to the market with a robotaxi service. For example, Tesla’s approach resembles that of competitors like Waymo and Cruise, who also began robotaxi rollouts in restricted zones under strict conditions. Waymo, for example, already operates commercially in Phoenix and parts of San Francisco and Los Angeles. Cruise, backed by General Motors, had a promising start but suspended operations in late 2023 following a pedestrian injury incident that drew regulatory scrutiny.

Why It Took So Long

The idea of self-driving cars has been around for over a decade, but mass-market deployment has proven far more difficult than early estimates suggested. In Tesla’s case, the core challenge has been both technical and regulatory.

For example, Tesla’s FSD system has been under investigation by the US National Highway Traffic Safety Administration (NHTSA) following multiple incidents involving crashes, some reportedly due to the software’s failures in low-visibility conditions. In one case, a pedestrian was killed.

While Tesla has previously claimed that all its cars since 2016 had the necessary hardware for autonomy, Musk admitted earlier this year that many vehicles will require upgrades to run the current FSD software. The company has now moved to a vision-only system, removing radar and LiDAR, a decision that has been widely criticised by autonomous vehicle experts.

Data Troubles Too

There is also the matter of data. Unlike Waymo, which maps its operating areas in detail using high-definition 3D maps, Tesla has tried to rely on neural networks trained on massive volumes of driving footage. This has made scaling difficult and introduced variability that regulators have found hard to approve.

Musk’s Image and Its Impact on Tesla

Elon Musk’s personal brand has become increasingly polarising in recent years. His public alignment with cryptocurrency memes, his vocal support for Dogecoin, and a turbulent relationship with Donald Trump have drawn both criticism and ridicule. While once celebrated for visionary innovation, Musk has also faced backlash over controversial posts, involvement with DOGE, erratic business decisions, and mass layoffs at several of his companies.

More recently, Musk’s role in advising Trump (followed by a very public fallout) has alienated large segments of Tesla’s consumer base, particularly in Europe. Tesla’s EV sales have shown signs of slowing, with increased competition from Chinese automakers and established rivals in Europe and the US. This has placed added pressure on the robotaxi rollout to deliver fresh growth.

Why Austin?

It seems that Austin is a strategic choice for a rollout for several key reasons. Texas has relatively permissive regulations around autonomous vehicle testing and deployment, especially compared to states like California. Also, Tesla already has a significant presence in Austin through its Gigafactory, and the area offers a variety of suburban and semi-urban driving conditions ideal for early robotaxi trials.

Start in the “Safest” Areas

The service will begin only in the “safest” areas of Austin, Musk has said. Vehicles have been repeatedly seen mapping and testing routes in the same neighbourhoods in southeast Austin. This narrow initial footprint allows Tesla to mitigate risk while gathering user data and refining its service.

What’s at Stake for Tesla and the Industry

At this point for Tesla and Musk, the financial stakes are high. Tesla has pivoted sharply away from its earlier strategy of producing affordable EVs for the mass market. Instead, it now appears to see autonomy, and robotaxis specifically, as its key to future growth. If successful, the robotaxi service could create a powerful new revenue stream with high margins and recurring user engagement.

For Tesla, therefore, this launch is not just a new product but is a test of its ability to deliver on technological promises that have been years in the making. It is also a reputational gamble. Any high-profile failure could undermine consumer confidence and invite further regulatory scrutiny, and further criticism or damage to the Musk brand.

For the wider industry, Tesla’s move is likely to intensify competition. Waymo, Zoox (Amazon-owned), and Apple’s long-rumoured autonomous vehicle programme will all be watching closely. A working Tesla robotaxi in a live environment could reignite investor interest in autonomy after a period of cooling.

Urban Mobility

If Tesla can prove its model works safely and reliably, the implications for urban mobility may be significant. Businesses could use robotaxis for employee transport, client travel, or local delivery in a cost-effective, on-demand way. Fleet management costs could drop, while ride availability and convenience could increase.

For example, local firms in Austin that rely on staff movement between offices or sites may benefit from more predictable, automated transport. It could also open new possibilities for tourism, hospitality, and customer service sectors where flexible, affordable point-to-point mobility can add real value.

However, some business leaders remain cautious. Liability in the event of an accident, limited coverage areas, and regulatory grey zones still pose challenges. Insurance, data privacy, and workplace policy updates would also need to evolve to support robotaxi use at scale.

Early Enthusiasm Meets Persistent Criticism

Despite the enthusiasm, experts remain wary. Tesla’s refusal to use LiDAR, i.e. a tool nearly all other AV companies rely on for precise spatial mapping, has been called “reckless” by some in the field. Public demonstrations have also drawn criticism. For example, in 2024, a group of safety advocates staged a protest using child-sized mannequins in San Francisco to show that Tesla’s FSD software failed to stop in simulated pedestrian scenarios.

Also, regulators are bound to be watching closely. The NHTSA’s ongoing investigations may yet influence the pace and scope of Tesla’s rollout, and cities with stricter AV policies may not welcome Tesla’s robotaxis without additional testing and third-party validation.

How Others Have Fared in This Space

As noted earlier, Tesla is not the first company to offer driverless ride services. Waymo has been operating in Phoenix since 2020 and has expanded gradually to parts of San Francisco and Los Angeles. Its vehicles use LiDAR, detailed mapping, and a cautious rollout process that has largely avoided major safety incidents.

Cruise, another major player, ran services in multiple US cities but paused all operations after an accident in late 2023 triggered widespread scrutiny and a loss of confidence in its safety protocols. Zoox, owned by Amazon, has been slower to launch but continues to test its purpose-built autonomous shuttles in California and Nevada.

Tesla’s approach is arguably more ambitious, but also riskier. Its reliance on general-purpose AI rather than detailed pre-mapping sets it apart, for better or worse. Whether that gamble pays off now rests, in large part, on the roads of Austin.

China’s Robotaxis Are Already Operating at Scale

While the US and Musk have drawn much of the global attention around autonomous vehicles, it’s worth noting here that China has quietly moved ahead with large-scale robotaxi deployments in several major cities. Companies like Baidu, Pony.ai and AutoX have all launched commercial driverless ride services in selected urban areas, in some cases without any human safety drivers onboard.

For example, Baidu’s Apollo Go service currently operates in cities including Beijing, Wuhan, Chongqing and Shenzhen. In certain districts of these cities, passengers can hail a fully driverless robotaxi using a mobile app, with the vehicle arriving and completing the journey without any human intervention. Baidu has already reported over 3 million autonomous rides completed and says that, in Wuhan, it now runs more than 100 driverless cars each day.

Pony.ai, backed by Toyota, is also operating robotaxi trials in Beijing and Guangzhou and has obtained permits for driverless testing in key urban zones. Meanwhile, AutoX, which is backed by Alibaba, claims to be the first company in China to run a completely driverless fleet in Shenzhen. Its vehicles operate on open roads with no onboard safety driver and no remote monitoring, under the approval of local authorities.

Why Is It Working In China?

China’s progress has been driven in part by a supportive regulatory environment. For example, several cities have introduced staged permission systems for autonomous vehicles, often designating specific districts for testing and public use. These areas are typically well-mapped, controlled and connected, which helps reduce the complexity and risk of operating without a driver.

Unlike Tesla’s reliance on vision-based AI alone, Chinese robotaxi providers typically use a combination of LiDAR, radar, high-definition mapping and vehicle-to-infrastructure data. This hybrid approach has allowed them to demonstrate higher consistency and, so far, avoid high-profile safety failures.

The result is that robotaxis in China are no longer just test cases but have become part of everyday urban mobility for some residents. While the scale remains relatively localised, the maturity of these deployments provides a valuable benchmark for global players, including Tesla.

What Does This Mean For Your Business?

Whether Tesla’s robotaxi launch becomes a turning point for the company or another overhyped milestone will depend heavily on how it performs in the real world. Unlike earlier promises tied to theoretical capabilities, this rollout involves real passengers, real roads, and real expectations. A smooth and safe service could help re-establish confidence in Tesla’s long-term vision and give the company fresh momentum at a time when its EV market share is under pressure and its public image is increasingly tied to the unpredictability of Musk himself.

For regulators, competitors, and the wider public, this trial will serve as a test case for what a driverless future might actually look like. If Tesla’s system operates reliably within its geofenced limits, it could pressure US cities and lawmakers to accelerate AV frameworks and could encourage other providers to speed up their deployments. However, any serious incidents could lead to renewed regulatory clampdowns or stall the broader industry’s progress.

UK businesses, while not directly impacted by the Austin launch, should be watching carefully. If Tesla proves its robotaxi model can be safe, efficient, and scalable, pressure may build for the UK to define clearer policies on AV services. Sectors like logistics, corporate travel, hospitality, and facilities management could all benefit from more flexible, low-emission transport solutions, especially in urban areas facing congestion and net zero targets. It may also prompt innovation across Europe’s mobility sector, where trust, data security, and transparency will be essential.

For now, Tesla’s plan to move from test footage to public fares is quite a bold move. The company has much to prove, both in terms of technology and trust. Whether the robotaxi rollout marks the beginning of a new chapter or another delay in an already chequered timeline remains to be seen.

Meta’s new AI app is under fire after users unknowingly shared private chats, including legal queries, personal data and audio clips, on the public web.

The issue lies with a “share” button that appears after each chatbot response. Users can post content without realising it’s publicly visible, especially if logged in via a public Instagram account. Security expert Rachel Tobac called it a “privacy nightmare” after spotting names, addresses and court-related questions shared online.

Some posts appear jokey or attention-seeking, but many involve sensitive or reputationally risky content. One user asked about a rash, another discussed tax evasion, and several uploaded CVs and legal references, seemingly unaware they were going public.

Launched on 29 April, the app has already hit 6.5 million downloads. However, experts say Meta should have anticipated the risks of blending private AI queries with social sharing.

Businesses should avoid using AI tools through personal logins and steer clear of sharing anything sensitive unless privacy settings are crystal clear.

Electric roads that wirelessly charge vehicles as they drive are now moving beyond demonstration and into real-world use, offering a glimpse of a transport future with fewer cables, faster charging, and lighter electric vehicles.

Global Trials Are Shaping the Next Phase of EV Infrastructure

Mainly based in the US at present, from city buses in California to delivery vans in Detroit and with motorway freight trials in Europe, it looks as though the rollout of wireless charging roads is picking up pace. This means that the technology is no longer confined to lab tests or closed tracks but is now actually being trialled on public roads, backed by major vehicle manufacturers and public infrastructure funds. For UK businesses and councils planning for large-scale EV adoption, the rapid global progress could offer valuable lessons, and a possible roadmap for future deployment.

Momentum

Electreon, the Israeli firm behind many of these pilots, says the momentum is beginning to shift. “We’re excited to demonstrate how Electreon’s technology can optimise electric fleet usage,” said Stefan Tongur, Vice President of Business Development. “This is about minimising downtime and enabling charging across time and location.”

How Do Wireless Electric Roads Work?

Wireless electric roads use inductive charging which is the same basic technology behind cordless phone chargers. Coils are embedded just below the road surface and connected to the electricity grid. When an electric vehicle with the right equipment passes over them, energy is transferred via a magnetic field to the vehicle’s battery.

The road segments activate only when authorised vehicles are detected, making the system both energy-efficient and safe. For this system to work, vehicles need a receiver mounted underneath to benefit from the charging. Power is managed in real time via a cloud-based platform that adjusts energy flow, tracks vehicle usage and allows for remote diagnostics.

Why This Could Help the Shift to EVs

For many drivers, range anxiety and charging delays are still barriers to switching to electric vehicles. The big plus point about wireless charging roads is that they offer a way to charge en route, thereby potentially removing the need for large battery packs and long charging stops.

For example, a delivery van or taxi could gain a top-up charge while waiting at traffic lights, at taxi ranks, or while driving between stops. This not only cuts downtime but could allow vehicle manufacturers to reduce battery size, lowering both emissions and cost.

Also, by flattening peak demand on the electricity grid and spreading charging throughout the day, the system could also support wider grid resilience. For countries like the UK, where both EV uptake and grid demand are rising sharply, this aspect has particular relevance.

Projects Taking Shape Around the World

Several real-world projects are already showing how the technology works.

In Detroit, Michigan, a quarter-mile stretch of 14th Street became the first public wireless charging road in the US. It’s now being expanded with support from the Michigan Department of Transportation and industry partners including Ford and UPS. The site also supports wireless overnight charging at a UPS depot, demonstrating how dynamic and static charging can work together.

In California, UCLA is deploying the same technology to electrify its BruinBus fleet ahead of the 2028 Olympics. Wireless charging coils are being embedded along a key campus route and at a new transit hub shared with other operators.

In Europe, Sweden, France and Germany are leading efforts. A 2 km test route on France’s A10 motorway is due to support up to 200 kW of charging for trucks. Sweden’s longer-term national ambitions have been scaled back due to cost, but smaller pilots continue, such as a 1.65 km stretch on Gotland. Germany is evaluating inductive charging alongside overhead cable systems on its Autobahn network.

Could This Work in the UK?

While the UK is not currently hosting any wireless electric road pilots, the concept has started to gain attention among infrastructure planners and local authorities. As the government aims to end the sale of new petrol and diesel vehicles by 2035, new approaches to charging infrastructure are being explored.

Back in 2015, the UK Department for Transport signalled early interest in the concept. “The potential to recharge low emission vehicles on the move offers exciting possibilities,” said then-Transport Minister Andrew Jones. “The government is already committing £500 million over the next five years to keep Britain at the forefront of this technology.”

Wireless roads could actually prove particularly relevant for UK cities with high taxi, bus and delivery van traffic. For example, wireless coils at taxi ranks outside Heathrow or in central London could support low-emissions targets while reducing visual clutter from charge points.

There may also be opportunities to integrate the technology into depot environments or council-run fleet hubs, such as bin lorry depots or local bus garages, where predictable daily routes and return-to-base schedules make charging efficiency critical.

For rural businesses operating in harder-to-reach locations, dynamic charging roads along key A-roads could one day reduce reliance on sparse rapid chargers. Although costs remain a barrier, strategic deployment in the UK’s most used corridors could be a viable starting point.

Who’s Leading the Charge?

The leading technology developer in this space is Electreon, an Israeli firm with active trials in the US, Germany, France, Italy, Norway and Israel. The company has built partnerships with major automakers including Toyota, Ford, BMW and Stellantis, and is now working on both aftermarket retrofit kits and built-in vehicle charging systems.

Electreon also provides what it calls Charging-as-a-Service, allowing fleet operators to pay a subscription rather than build and own the infrastructure. This could become an attractive model for UK bus companies or logistics firms looking to upgrade to electric without massive capital expenditure.

According to Electreon, the system is designed to integrate smoothly into daily fleet operations. “Our wireless charging solution enables vehicles to charge throughout the operational day, minimising downtime and reducing the need for large battery packs,” said Stefan Tongur, the company’s Vice President of Business Development.

Other players include Hevo Power and Witricity, both of which are working on wireless charging hardware and standards. SAE’s J2954 standard (and the upcoming J2954/2 for trucks) is helping to create consistency across vehicle manufacturers and infrastructure developers.

Benefits for Fleets, Cities and the Environment

Wireless charging is best suited to vehicles with regular, predictable routes e.g., city buses, last-mile delivery vans, taxis, or refuse trucks. These are also the vehicle types that make up a large portion of urban emissions.

For example, by enabling smaller batteries and constant top-up charging, electric bin lorries in London or Manchester could stay on the road longer without needing depot downtime. This helps both emissions goals and operational efficiency.

In logistics, charging vehicles while they load or unload could reduce idle time. In public transport, bus services could stay electric and reliable even in areas without large depot charging capacity.

On a broader scale, widespread wireless infrastructure could enable manufacturers to offer lighter, more efficient EVs at lower cost, thereby removing another barrier to adoption.

What’s Holding the Technology Back?

Despite the enthusiasm, wireless roads are expensive to build. In Detroit, for example, costs have been reported at nearly $2 million per mile. Indiana’s high-power truck corridor is costing around $11 million per quarter-mile.

Installation can also raise maintenance challenges. In-road coils may affect road resurfacing schedules, and some test sites have seen overheating or pavement cracking under certain traffic loads.

Vehicle compatibility is another hurdle. For example, most EVs on the road today do not support wireless charging, and while retrofitting is possible, it adds complexity and cost. Until OEMs begin including wireless receivers as standard, usage will remain limited.

There are also practical constraints on where the technology should be deployed. For example, experts agree that not every road needs to be electrified and targeted placement along high-use routes or fleet corridors currently is seen as the most efficient approach.

Still Niche, But Moving Fast

Wireless electric roads are not about replacing every plug-in charger. Instead, they represent a smart, strategic solution for the vehicles and locations that need it most. With UK councils under pressure to cut fleet emissions, and operators seeking more efficient ways to electrify, this evolving technology could soon be part of the answer.

What Does This Mean For Your Organisation?

At the moment, it looks as though wireless charging roads are unlikely to become the default for every vehicle or every mile of tarmac, but the idea offers an opportunity to improve the way key vehicles are powered and operated. For example, for commercial fleets, delivery vans, buses and urban taxis, the ability to charge without stopping could drive real gains in efficiency, availability and emissions reduction. These are use cases where the business model already makes sense and the benefits are most immediate.

For UK businesses, particularly those with depot-based or high-frequency urban fleets, this could offer a way to cut costs without investing in large-scale grid upgrades or building out conventional charging infrastructure. The reduced need for larger batteries may also help ease supply chain pressures and allow for lighter, cheaper vehicles that are better suited to city environments. In areas where charging infrastructure is hard to install or already oversubscribed, such as busy city centres or constrained industrial estates, wireless charging could prove especially useful.

The same applies to public sector stakeholders. Local authorities managing refuse trucks, park maintenance fleets or public transport services could use this technology to meet emissions targets more easily while streamlining day-to-day operations. Where councils are upgrading road surfaces or building new transit infrastructure, wireless charging could be built in from the start.

For now, however, the barriers are still significant. Cost, standardisation and vehicle compatibility continue to limit broader rollout. That said, progress is clearly accelerating. As vehicle manufacturers begin to integrate wireless receivers as standard, and more cities commit to zero-emissions transport goals, the conditions for uptake will become increasingly favourable. While not a silver bullet, wireless charging roads are emerging as a credible and focused part of the wider shift towards sustainable transport.

ChatGPT’s ‘Projects’ make life a lot more organised, when it comes using their platform. Doubtless with this in mind, OpenAI have added four powerful new features which we explore in this episode.

[Note – To Watch This Video without glitches/interruptions, It may be best to download it first]

Need to send a sensitive email that shouldn’t stick around or be shared? Gmail’s Confidential Mode lets your message self-destruct after a set time, blocks forwarding, copying, downloading and printing, and adds optional passcode protection.

How to:

– In Gmail, click Compose.
– Tap the lock with a clock icon at the bottom of the compose window.
– Choose an expiry date (from 1 day up to 5 years).
– Select SMS passcode if you want to add verification.
– Click Save, then write and send your email.

What it’s for:

Use this when emailing things like passwords, financial details, legal documents or quotes — anything that shouldn’t be saved or shared. The expiry ensures your message won’t linger indefinitely, and the recipient can’t easily forward or download it.

Pro-Tip: Add an expiry reminder in the subject line (e.g. “Expires in 7 days”) — and remember recipients can still screenshot the content, so it’s best for lower-sensitivity communications.

ChatGPT now includes meeting recording, cloud integration and deep research tools, marking its biggest push yet into everyday business workflows.

Featured For Everyday Business Use

With over 3 million enterprise-focused customers now using ChatGPT (up from 2 million earlier this year), OpenAI appears intent on securing its place in the core workflow of modern businesses. With this in mind, OpenAI has released some new business-focused features for ChatGPT which are designed to embed ChatGPT more deeply into the kinds of platforms, files, and meetings professionals already depend on.

Update

The latest ChatGPT feature update, designed specifically for paid users across business and education plans, introduces three key capabilities that shift ChatGPT from a smart chatbot to a practical everyday work assistant. These are:

1. Cloud connectors, which let users query documents in platforms like Google Drive or SharePoint.

2. Meeting recording and transcription, available directly inside the ChatGPT (macOS) app.

3. Deep research tools that aggregate and cite information from a variety of business apps and data sources.

It seems that each one has been designed with a view to reducing friction, eliminating app-switching, and (hopefully) helping users access, understand and act upon information more efficiently.

Search Across Your Own Files With Cloud Connectors

One of the most immediately useful additions, ‘Cloud connectors’, means users can connect ChatGPT to leading cloud services. Supported platforms include Google Drive, Microsoft OneDrive, Microsoft SharePoint, Dropbox, and Box.

Once connected, for example, ChatGPT can access stored files like PDFs, Word documents, presentations and spreadsheets, and use that content to respond to user queries. The functionality supports both simple search (“Find last week’s planning document”) and more complex analysis (“Summarise our Q2 sales figures from uploaded reports”).

The connectors operate with full respect for organisational access permissions, i.e. only content which the user is allowed to access is returned, and all files are previewed directly inside the chat for faster referencing.

Who Can Use it?

Cloud connectors are available to Team, Enterprise, and Edu users globally. Pro and Plus users can access them too, except in the UK, Switzerland and the European Economic Area, where availability is restricted for now due to data privacy regulations.

Meeting Recording Giving Structured Notes from Live Conversations

ChatGPT now also includes ‘Record Mode’, the ability to record and transcribe meetings or voice notes, a feature available through its macOS desktop app for Team users. The tool turns spoken content into structured, searchable summaries, all complete with key points, time-stamped citations, and suggested action items.

How?

After a recording is made, the output is saved as a canvas document, which can then be edited, expanded, or turned into emails, project plans or even code. It also becomes part of the user’s searchable knowledge base within ChatGPT.

For example, a team lead could ask: “What did we agree during Monday’s planning meeting?”

ChatGPT would respond with a time-stamped summary pulled from the transcript, thereby saving the need to rewatch the recording or chase colleagues for notes.

Limitations and Availability

Record Mode is only available to users on Team plans using the macOS desktop app. OpenAI says recording sessions can be up to two hours long, and transcripts follow the workspace’s retention policies. Rollout to Enterprise and Edu users is planned, but there’s currently no browser-based option, and speaker diarisation (i.e. who said what) is not yet supported.

Deep Research Connectors For Insights Across Apps

The new ‘Deep Research’ mode allows ChatGPT to produce detailed, cited outputs by pulling together information from internal tools, cloud documents and the web. For example, rather than simply responding to queries in chat, this mode builds more structured research reports that are tailored to a given task.

Supported connectors include:

– GitHub and Linear (engineering and development).

– HubSpot (CRM and marketing).

– Google Drive, Gmail and Calendar.

– Microsoft Outlook, SharePoint, Teams and OneDrive.

Typical use cases could include reviewing recent project work, summarising customer conversations, or combining internal product documents with external market insights.

Users can even export the result as a professionally formatted PDF, with tables, links and citations included.

Who Gets Access?

Deep Research is available to Pro, Plus, Team, Enterprise and Edu users, excluding the UK, EEA and Switzerland. There’s no Free tier access, and setup varies by platform, but some connectors may require authentication, while others are pre-approved by admins.

Model Context Protocol (MCP)

For businesses with custom internal systems or industry-specific data, OpenAI now supports the Model Context Protocol (MCP). This allows technical teams to build their own connectors that link ChatGPT to virtually any structured data source.

For example, these custom connectors can retrieve internal information, such as customer records, billing data or support tickets, and allow ChatGPT to query it as part of a deep research task. The results are combined with public data and other connected apps to create cohesive reports.

Access and Setup

It should be noted that MCP is only available for Pro, Team, Enterprise and Edu customers. Admins are responsible for deploying MCP connectors via a remote server. Once approved, they become available across the entire workspace.

This feature may be particularly useful for large organisations looking to integrate ChatGPT into existing business intelligence systems or build AI-powered internal knowledge tools.

Practical Use Examples

Some examples of how these features could be used to support everyday business tasks include:

– A sales manager using HubSpot data to analyse deal close rates across regions.

– A product owner recording a team call and using ChatGPT to generate a roadmap summary.

– An analyst asking ChatGPT to pull data from Dropbox and Google Drive to create a performance report.

– A developer linking GitHub to summarise pull requests or past sprint changes.

In each case, using these new features, ChatGPT can act as a kind of AI research assistant that’s able to pull from multiple sources, remember context, and suggest outputs tailored to the task.

What About Security, Privacy and Control?

With these new features, it seems that OpenAI has taken some steps to address enterprise concerns around data usage and privacy. For example, OpenAI is keen to point out that:

– Data from connectors and Record Mode is not used to train models for Team, Enterprise and Edu users.

– Audio recordings are deleted immediately after transcription.

– All connector access is opt-in and user-authenticated, and connectors only search files that users have permission to view.

– Admins can restrict or disable access to specific tools through workspace settings.

However, for users on the Free, Plus or Pro plans, OpenAI may use data from connectors to train its models if the “Improve the model for everyone” setting is enabled. Businesses on these plans may need to check this setting to ensure it aligns with their data policies.

A Step Ahead of the Competition?

This move from OpenAI looks like positioning ChatGPT as a serious contender in the growing race for AI-powered productivity. While Microsoft’s Copilot and Google’s Gemini already integrate tightly with their own ecosystems, ChatGPT offers something different: broad compatibility with multiple tools, deep natural language understanding, and cross-platform flexibility.

Smaller players like Notion, ClickUp and Zoom have also added AI-powered summaries or transcription features in recent months but it seems that OpenAI’s latest update offers a more expansive set of capabilities in one interface, provided companies are willing to integrate their workflows.

There are also signs that OpenAI may expand these features further. For example, the company’s documentation notes that more connectors are in development, and that browser support for Record Mode and broader language transcription are both on the roadmap.

What Does This Mean For Your Business?

It looks as though businesses currently using ChatGPT on a Team or Enterprise plan could stand to gain some immediate, practical benefits from this update. For example, being able to search internal documents, capture meetings with actionable summaries, and generate reports from connected tools could help teams cut down on duplication, reduce time spent switching between apps, and improve the speed and quality of decisions. For knowledge-heavy sectors such as finance, legal services, software development or consultancy, these tools offer a way to bring routine research and documentation tasks under one roof.

However, the regional limitations are hard to ignore. For example, it seems that businesses in the UK, the EEA and Switzerland on Pro and Plus plans are currently excluded from using many of the new connectors and deep research features. While this is due to data privacy rules, it still creates inconsistency for organisations with teams in multiple countries, and may affect uptake in regulated industries unless a clearer roadmap for availability is published.

For others in the AI productivity space, the implications are also significant. For example, OpenAI’s approach of building connections into widely used tools like Google Drive, Outlook and HubSpot allows ChatGPT to operate more flexibly across mixed tech environments than many rivals. Microsoft and Google still have the advantage of full-stack integration, but this update increases the pressure on them to improve openness and compatibility. Smaller platforms like Notion, Zoom and ClickUp, which have been quick to adopt AI features, may struggle to match the breadth of this offering unless they build similar connector frameworks.

It seems, therefore, that what happens next may come down to usability and trust. If OpenAI can make these features accessible without excessive setup, and if organisations are confident in the way their data is handled, ChatGPT could become far more than a clever chatbot. It could start to take on the role of an always-available assistant and, crucially, one that understands the context, connects the dots, and can work quietly behind the scenes to keep teams informed, aligned and productive.

Microsoft is warning users that saved passwords will soon be deleted from its Authenticator app, as it phases out the feature in favour of Edge and passkeys.

Major Changes Coming to Microsoft Authenticator

Millions of Microsoft users are being urged to take action ahead of a planned overhaul to the Microsoft Authenticator app. Microsoft says that from August 2025, the app will no longer store or provide access to saved passwords. The change is apparently part of Microsoft’s wider push towards a passwordless future and will directly impact individuals and businesses who rely on Authenticator to manage credentials.

The phased retirement of password and autofill functionality in the app begins this month (June 2025) and ends with permanent deletion in August.

Improved Security and Streamlining

Microsoft says the move is intended to improve account security and streamline its identity tools, but critics have raised concerns about user disruption and the company’s growing dependence on its Edge browser.

What Exactly Is Happening And When?

According to Microsoft’s official support documentation, the changes will roll out in three key stages:

– From June 2025, users will no longer be able to add or import new passwords into the Authenticator app. The app will still autofill existing saved passwords for a short time.

– During July 2025, the autofill feature will be fully disabled, and any stored payment information will be deleted from user devices.

– From August 2025, all previously saved passwords will be permanently inaccessible in the Authenticator app. Any passwords generated through the app but not saved will also be lost.

Microsoft is, therefore, urging users to export their passwords before the August deadline or risk losing them permanently.

Microsoft’s Password Problem

At the heart of the decision is the fundamental issue that passwords are no longer seen as being secure. For example, Microsoft’s internal data suggests the scale of the threat has worsened. In a blog post published last December, the company said it was blocking an average of 7,000 password attacks per second, nearly double the rate from the previous year. Phishing campaigns, brute-force attacks, and credential stuffing continue to rise.

As the blog noted, “Bad actors know [passwords are dying], which is why they’re desperately accelerating password-related attacks while they still can.”

It should be noted here that Microsoft is not alone in this assessment. For example, data from the FIDO Alliance shows that over 35 per cent of people have had at least one online account compromised due to password vulnerabilities. Meanwhile, 54 per cent of those familiar with passkeys say they’re more convenient than passwords, and 53 per cent say they’re more secure.

It seems that Microsoft sees this moment as an opportunity to transition users to more modern authentication methods, particularly passkeys, i.e. credentials tied to biometric data like fingerprints or facial recognition, which are less vulnerable to traditional forms of hacking.

A Nudge Towards Microsoft Edge

In practical terms, Microsoft is also consolidating its password management services under its Edge browser. Users who still want Microsoft to handle their credentials are being directed to switch to Edge, where passwords, addresses, and other autofill data can be securely stored in their Microsoft account.

A new splash screen in the Authenticator app now encourages users to “Turn on Edge” for this purpose. Microsoft notes that passwords are synced with the user’s Microsoft account and can be accessed by signing into Edge, where they are stored under Settings > Passwords.

This change isn’t just about security. It’s clear that this move is also designed to help strengthen Microsoft’s long-standing campaign to increase adoption of its browser. As part of this push, password autofill services are no longer available through Authenticator in Chrome, Safari, or other third-party browsers. Users who don’t want to use Edge are advised to export their passwords and switch to an alternative password manager such as Google Password Manager or iCloud Keychain.

What About Passkeys and 2FA?

Although password storage is being removed, the Microsoft Authenticator app itself isn’t going anywhere. It will continue to support two-factor authentication (2FA), including time-based one-time passwords (TOTP) and biometric logins.

More importantly, Authenticator will remain central to Microsoft’s passkey system. If users have already enabled passkeys for their Microsoft account, they must keep Authenticator enabled as their designated passkey provider. Disabling the app may break access to those accounts.

Passkeys “Superior”

Microsoft says passkeys offer a “superior user experience” by enabling faster logins that are resistant to phishing and replay attacks. But the technology is still in early stages, and many websites and systems, especially in the enterprise world, have yet to adopt it widely.

What Users Need To Do

For individual users, the priority is clear, i.e. export any saved passwords from Authenticator before 1 August 2025. Microsoft warns that any unsaved credentials will be lost, and payment details stored in the app will be deleted by July.

To keep using Microsoft’s ecosystem, users can set Microsoft Edge as their autofill provider on iOS or Android. Those wanting to move to a different platform must export their credentials, then import them into the new tool.

More Complex For Business Users

However, as may be expected, it seems that business users, especially those in IT administration roles, face more complexity. This is because many organisations use Authenticator not only for employee 2FA, but also as a password vault for accessing internal systems and client accounts. The removal of this functionality could lead to operational disruption if not properly managed.

Enterprises will, therefore, need to review whether Edge is suitable across their environments, or whether to transition to third-party tools like Keeper, 1Password, LastPass, or Bitwarden, and others, many of which offer team vaults and admin controls.

Microsoft has published step-by-step guides for exporting credentials from the app and importing them into Edge. However, the company also warns that when exporting passwords, they are no longer encrypted in transit. Users must delete the exported file immediately after import to avoid exposing sensitive information.

Criticism and Concerns

Despite the security rationale given by Microsoft, the move hasn’t gone without criticism. For example, some users see it as an aggressive tactic to push people towards Microsoft Edge. Others are concerned about losing the flexibility that came with Authenticator’s cross-browser compatibility.

The change also comes at a time when Microsoft has faced growing scrutiny over its handling of security. Recent phishing campaigns targeting Microsoft accounts have used Google Apps Script to host realistic-looking fake login pages, tricking users into entering credentials. By removing password storage and advocating for passkeys, Microsoft is positioning itself as proactive, but some argue the change is reactive to recent threats.

Also, many IT professionals, including managed service providers (MSPs), have expressed reservations about using browsers to store sensitive information such as passwords. While Microsoft maintains that Edge is a secure, enterprise-grade browser with built-in defences like Defender SmartScreen and Password Monitor, it remains the case that most security-conscious businesses recommend dedicated password managers instead.

Some MSPs, for example, point users towards platforms like Keeper, which offer stronger access control, audit trails, and encryption options tailored for business environments. Even mainstream alternatives like LastPass (once widely used) have lost trust following a high-profile security breach in 2022, which saw attackers steal encrypted vault data. This has left many in the industry sceptical of relying solely on browser-integrated tools for credential storage.

As a result, it seems that IT teams now face a more difficult decision. Microsoft’s advice to migrate to Edge may be convenient, but it is unlikely to satisfy organisations with strict compliance policies, high-value systems, or users working across multiple platforms. For many, this change serves as a prompt to reassess their overall password and identity management strategy—and not simply swap one tool for another.

Also, it should be noted that, quite simply, not all users or organisations are ready for a passwordless future. Adoption of passkeys remains patchy, and migrating authentication systems requires time, budget, and user training. For small businesses or non-technical users, these changes may be frustratingly complex.

Microsoft appears to be aware of these challenges but remains committed to the transition. As the company put it, “The password era is ending”—and with password-based attacks continuing to rise, the shift may be less about convenience and more about survival.

What Does This Mean For Your Business?

The next few months may be critical for users and organisations who rely on Microsoft Authenticator for password storage. While the company has made its intentions clear and set out a defined timeline, the practical implications are not quite so straightforward. Users will need to act quickly to export their credentials, and those choosing to remain within Microsoft’s ecosystem will need to familiarise themselves with Edge’s autofill features. For many, this will simply be a matter of adjustment. However, for others, particularly in business environments where systems, devices and browsers vary, the change raises more complex operational and security considerations.

For businesses, the impact could be significant. Many will now be forced to re-evaluate how they manage shared logins, administrative access and compliance-sensitive credentials. Microsoft’s preference for its own browser may not align with existing IT policies, particularly in organisations where Chrome or Safari is the standard. Also, while Microsoft promotes Edge as a secure alternative, longstanding guidance from many managed service providers in the UK still discourages storing passwords in any browser. Instead, tools like Keeper (there are other tools), favoured by many MSPs for their advanced controls and business-grade encryption, are often recommended as more robust alternatives.

At the same time, Microsoft’s strategy seems to reflect a wider shift that is now shaping the security landscape. Passwords have long been a weak point, and with attack volumes rising year on year, the company’s decision to pivot towards passkeys is consistent with broader industry trends. However, the reality is that many businesses, especially smaller ones, are not yet equipped to make this leap. Compatibility gaps, legacy systems, and limited resources all present barriers to adoption. Without careful planning and communication, the risk is that essential authentication processes could be disrupted or improperly migrated.

What’s clear in all this is that Microsoft is pushing ahead regardless. By retiring password storage from Authenticator and tying remaining functionality to Edge and passkeys, the company is accelerating a shift that many see as inevitable. Whether this benefits users in the short term may depend less on Microsoft’s vision and more on how quickly organisations can respond, adapt and put the right alternatives in place. For now, IT teams will need to weigh the convenience of Microsoft’s path against the operational demands and risks that come with changing how people log in.

Two European startups have developed groundbreaking tools, including real-time autofocus glasses that adjust to where you look and a bioprinted wound patch for pets that could lead to printable human organs.

Smart Glasses That Adapt As You Look

Finland-based IXI has developed what it claims are the world’s first real-time autofocus prescription glasses. Rather than adding smart features like cameras or displays, the company focuses on correcting vision more naturally.

Founded in 2021 by imaging and optics specialists Niko Eiden and Ville Miettinen, IXI recently raised \$36.5 million in Series A funding. Backers include Amazon’s Alexa Fund and several major European venture firms. The money will support the final development of the company’s first commercial product, IXI Adaptive Eyewear.

How It Works

The system uses a low-power eye-tracking sensor and liquid crystal lenses. When the user shifts focus, the glasses detect eye movement and adjust the lens shape in real-time, typically within 0.2 seconds. The liquid crystals change how they bend light, automatically matching the user’s focal distance.

All the electronics fit within a standard frame, and battery life is expected to last two days, with the lenses reverting to a fixed prescription mode if the power runs out.

Aimed at Replacing Progressive Lenses

IXI has targeted the new glasses at those with presbyopia, which affects the eye’s ability to focus on nearby objects and typically appears from age 40. Whereas traditional progressive lenses have narrow reading zones and peripheral distortion, IXI says its dynamic lens offers full-field clarity without these trade-offs.

The Next Phase In Eyewear Development?

A key part of IXI’s pitch appears to be that dynamic lenses represent the next logical phase in eyewear development, not just an upgrade to existing products. “Whether it’s us or another company, somebody will crack it,” said CEO Niko Eiden. “The step from static to dynamic lenses is a natural evolution.”

Market and Availability

The global eyewear market is currently worth more than $200 billion and growing at 8–9 per cent a year. IXI, therefore, hopes to launch a consumer-level product targeting older professionals and others frustrated with current lens limitations. No pricing or release date has yet been confirmed, though live demonstrations are expected later in 2025.

What Needs to Improve

Despite the obvious advantages of the new lenses, key technical challenges remain. For example, IXI must deliver all-day comfort, eliminate lens haziness, and meet medical-grade optical clarity standards. Transparent electronics, battery miniaturisation and long-term durability are also all active areas of R&D.

There’s also the threat of competitors emerging. For example, French startup Laclarée and Japan’s Elcyo are also working on autofocus eyewear, though neither has launched a product. Tech giants like Meta and Apple are investing in glasses too, yet their focus remains on augmented reality rather than vision correction. IXI is aiming to fill the gap in between.

Bioprinted Patches for Pets Could Lead to Human Organs

Meanwhile, Lithuanian startup Vital3D is tackling tissue regeneration. Its first commercial product, VitalHeal, is a laser-printed wound patch designed for dogs. The patch embeds growth factors and features microscopic pores that allow air circulation while blocking bacteria.

Vital3D says the technology could eventually be used to bioprint transplantable human organs, but that this goal is likely still 10 to 15 years away. The company has deliberately started with simpler applications in veterinary care as a stepping stone towards more complex human use.

Faster Healing, Lower Risk

The patch is designed to seal wounds, maintain pressure, and accelerate healing. Vital3D claims it can reduce recovery time from 10–12 weeks to just 4–6 weeks. Infection rates could fall from 30 per cent to below 10 per cent, and the number of vet visits required may drop significantly.

The retail price is €300 per patch (€150 wholesale). While more expensive than standard dressings, it could cut overall treatment costs by reducing surgery time and complications.

A Technology Platform, Not Just a Patch

Vital3D uses Two-Photon Polymerisation, a high-resolution laser-based printing technique. Its patented FemtoBrush system allows the laser beam to dynamically change shape during printing, enabling both fine detail and larger structural areas in the same build. The system can print features as small as one micron, within a build volume of 50 x 50 x 100 mm.

The company’s long-term goal is to print implantable human kidneys. For now, the priority is building the core platform by addressing major challenges such as creating vascular networks and supporting cell differentiation. Dog trials are scheduled to begin this year in Lithuania and the UK.

Competing Efforts and Future Outlook

Vital3D is one of several companies working on bioprinted tissue, though it is taking a notably commercial route into the market.

Other startups in this space include US-based Trestle Biotherapeutics, which is developing kidney tissue for research and transplantation, and Sweden’s CELLINK, which builds bio-inks and printing systems for soft tissue reconstruction.

It’s worth noting, however, that Vital3D stands out for its commercial-first strategy, using veterinary applications to test and refine the technology before moving to human use. The company is targeting a €76.5 million addressable market for its pet wound patch across the EU and US, with plans to sell 100,000 units by 2028.

What Does This Mean For Your Business?

For UK opticians and eyewear providers, IXI’s autofocus glasses may introduce a new product category with implications for prescriptions, training and aftercare. As consumer expectations shift towards seamless, tech-enabled vision correction, businesses will, therefore, need to adapt quickly.

In healthcare, Vital3D’s approach may offer a model for phased innovation. For example, by starting with pets and progressing gradually towards human treatment, the company reduces clinical risk while building regulatory and commercial experience. This could be especially relevant for UK medtech startups navigating approval pathways for advanced therapeutic devices.

Both companies face significant hurdles around manufacturing, regulation and market adoption. However, their step-by-step focus on solving practical problems, rather than pushing hype, suggests a more sustainable route to impact. Whether in optometry or regenerative medicine, UK stakeholders may find that these technologies offer useful templates for how to bring complex ideas to market with real-world application in mind.

oogle has (albeit quietly) released a new app that allows users to run powerful AI tools directly on their phones without needing a Wi-Fi or data connection.

Edge Gallery

The new app, called Google AI Edge Gallery, lets users download and run generative AI models locally on Android devices. These models can perform a wide range of tasks, e.g. from answering questions and summarising text to generating images or writing code, all without sending any data to the cloud (no connection needed).

Models Sourced From Hugging Face

The models are sourced from Hugging Face, a leading open AI model platform, and are processed entirely on the user’s device using Google’s LiteRT runtime and on-device ML tools. Users can switch between models, view real-time performance metrics, and even test their own models if they meet the compatibility requirements.

The app’s key functions include:

– AI Chat for multi-turn conversations.

– Prompt Lab for rewriting, summarising, or generating code.

– Ask Image for asking questions about photos.

– A model selection interface with performance benchmarks.

Why?

The move aligns with Google’s growing focus on edge computing, where tasks are carried out on local devices rather than in the cloud. This approach offers key benefits around speed, accessibility, and data privacy.

For example, by letting models run locally, users don’t have to rely on internet connections or send sensitive data to external servers. Google says the app is designed to support developers, tech-savvy users, and organisations that want reliable AI tools even in low-connectivity environments.

The release follows Google’s AI-heavy announcements at Google I/O 2025, where it unveiled new AI features across Android, Gemini, and its Pixel devices.

What Are the Benefits?

Running AI locally offers several practical and privacy-related advantages, such as:

– Offline functionality. Users can run models anywhere, without Wi-Fi or mobile data.

– Faster response times. On-device processing reduces delays caused by network latency.

– Improved privacy. Data stays on the device, which may reassure users handling sensitive information.

– Developer control. Developers can experiment with different models, observe performance, and build edge-native apps.

For example, a field engineer working in a remote area could use the app to summarise technical notes without needing a signal, while a journalist might analyse an image on their phone without uploading sensitive material to the cloud.

Who Can Use It, When, and How?

The AI Edge Gallery app is currently available to download on Android devices via GitHub. It is labelled as an experimental Alpha release, with an iOS version confirmed to be in development, although Google has not yet announced when or where it will be released.

It should be noted that the app is not available on the Play Store. Instead, users must download the app manually from GitHub. Installation requires sideloading the APK file, and Google has published a setup guide on the app’s Project Wiki.

The app is free to use under an Apache 2.0 open-source licence, which allows personal, educational, and commercial use without restriction.

However, it’s worth noting that performance could vary depending on the device’s hardware, and Google advises that newer phones with more RAM and faster processors are likely to be able to run larger models more effectively.

Showcasing Google’s Own Models

This release appears to signal a subtle but strategic shift in Google’s AI rollout strategy. For example, while the company has traditionally focused on cloud-based AI, this app shows it is now investing in local, device-first AI infrastructure.

It may also help Google showcase the performance of its own models, e.g. Gemma 3n, a lightweight model optimised for mobile, and reinforce its presence in the developer community by integrating tightly with Hugging Face and offering flexibility in model choice.

If successful, Google’s AI Edge Gallery could form the basis for deeper AI integration into Android itself, particularly as competitors also move towards local AI capabilities.

What’s In It for Business Users?

For UK business users, the app could prove useful in several scenarios. For example:

– On-site professionals, such as surveyors, logistics workers, or service engineers, could use it in low-connectivity areas to analyse documents, photos, or text.

– Small teams could use offline AI for copywriting, coding, or productivity tasks without incurring cloud service fees or risking data exposure.

– Privacy-conscious sectors such as legal, healthcare, and defence may appreciate the enhanced data control that on-device processing allows.

Although the current app is more developer-focused than enterprise-ready, it gives a strong preview of what local AI could bring to business tools in the near future.

How Does It Compare with Competitors?

The launch is likely to put a bit of pressure on rivals such as Apple, Meta, and OpenAI, all of which are working on or teasing local AI models.

Apple is expected to unveil its own on-device AI model support at WWDC 2025, while Meta recently previewed mobile-ready versions of its LLaMA models. However, most models from OpenAI (including GPT-4) still rely on cloud access, making Google’s offering stand out for now.

Hugging Face has also been expanding its mobile AI support and is likely to benefit from this integration, particularly among Android developers. By giving developers a user-friendly testing ground for their models, Google is most likely hoping to strengthen its own ecosystem while supporting the wider open AI community.

Limitations

Always with tech, despite its promise, the app has its limitations. For example, performance is highly device-dependent, and some models may run slowly (or fail entirely) on older hardware. For instance, image captioning models may take several seconds to process a request unless used on a high-end device.

Also, the user interface is functional but not consumer-ready, and installation via GitHub may deter less technical users. This is, therefore, clearly a tool for early adopters and developers rather than general smartphone users (at least for now).

There are also concerns around misuse. While offline AI increases privacy, it also makes it harder to monitor how models are being used. Without cloud oversight, some experts warn it could be harder to enforce content safety or ethical guidelines.

As one developer on GitHub noted: “It’s amazing tech—but what happens when powerful tools are completely disconnected from accountability mechanisms?” That question may become more pressing as local AI becomes more powerful and widely available.

Regulatory Implications Still Unclear

Because the models run locally, data protection laws such as the UK’s GDPR may not apply in the same way as with cloud-based AI. However, this could raise new questions around model bias, hallucination, and responsibility for outcomes when the tools are used offline.

No formal regulatory guidance has yet been issued in the UK or EU for edge AI use cases of this kind, though industry observers expect the issue to grow in importance as adoption increases.

What Does This Mean For Your Business?

If AI Edge Gallery gains traction beyond the developer community, it could mark the start of a broader move toward decentralised AI usage, giving users more autonomy over their data, tools and workflows. For UK businesses, the ability to run models offline opens up new possibilities for mobile productivity, secure client interactions, and operational resilience in connectivity-limited environments. From a practical standpoint, sectors such as construction, logistics, healthcare, and professional services could all find value in locally executed AI that reduces both costs and compliance risk.

For Google, the app serves multiple strategic purposes. For example, it allows the company to showcase its own AI models in real-world use, gather feedback from early adopters, and strengthen ties with the open-source community through its Hugging Face integration and permissive licensing. At the same time, it positions Google to lead in a space where rivals are only just beginning to move, thereby putting pressure on Apple, Meta and others to accelerate their local AI offerings.

However, running AI models offline complicates questions of oversight, safety and accountability. Without cloud-based controls, there is little to stop misuse, and no guarantee that outputs will meet any quality or ethical standard. For regulators and policymakers, this raises difficult issues around liability and governance that have yet to be addressed in formal legislation.

The wider AI market may also need to reckon with the fragmentation introduced by local deployment. Device specs, model compatibility, and uneven performance could all impact usability, potentially reinforcing digital divides. And while the app is free, it still assumes a baseline of technical knowledge that may put it out of reach for less experienced users.

AI Edge Gallery, therefore, essentially reflects a shift towards placing AI tools directly into the hands of users, no longer tethered to distant servers or platform-controlled APIs. For those in business, development, or digital infrastructure, that shift could prove both empowering and disruptive, depending on how the ecosystem evolves.

Meta and Russian search firm Yandex used hidden background scripts to monitor Android users’ web activity without consent, bypassing incognito mode and browser protections, researchers say.

Hidden Tracking System Uncovered

A new joint investigation has revealed that Meta and Yandex have been covertly collecting the private web browsing data of Android users by exploiting local communication loopholes between mobile apps and browsers. The technique reportedly allowed both companies to bypass standard privacy protections, without the knowledge or consent of users.

The findings were published by an international research team led by Radboud University in the Netherlands and IMDEA Networks Institute in Spain. The group included privacy experts Gunes Acar, Narseo Vallina-Rodriguez, Tim Vlummens (KU Leuven), and others. Their research revealed that Android apps owned by Meta (including Facebook and Instagram) and Yandex (including Yandex Maps, Browser, Navi, and Search) were silently listening on fixed local ports to receive web tracking data via local network connections, thereby effectively joining app-based user identities with users’ browsing habits.

According to the researchers, this practice undermines the technical safeguards built into both Android and modern web browsers, including incognito browsing, cookie restrictions, and third-party tracking protections.

How the Tracking Worked in Practice

Under Android’s permission model, any app granted the “INTERNET” permission (which includes nearly all social media and mapping apps) can start a local server inside the app. Meta and Yandex are reported to have used this ability to set up background listeners on local ports (e.g. via TCP sockets or WebRTC channels).

When users visited websites embedded with Meta Pixel or Yandex Metrica tracking scripts, those scripts could secretly send data to these background ports on the same device. This meant the apps could intercept identifiers and browsing metadata from the websites, despite no direct interaction from the user, and tie them to a logged-in app profile. The researchers say this technique effectively broke down the wall between mobile app usage and private web browsing, two areas users generally expect to remain separate.

Evasion Tactics From Yandex?

While Meta’s version used WebRTC signalling to send identifiers to their native apps, it seems that Yandex implemented a more dynamic system. For example, their apps reportedly downloaded remote configurations and delayed activation for several days after installation, which is behaviour likened by the researchers to malware-like evasion tactics.

Widespread Reach and Long-Term Use

The researchers have reported that the tracking appears to have been extensive. Meta Pixel is currently embedded on approximately 5.8 million websites, while Yandex Metrica is used on more than 3 million. Although the practice was only observed on Android devices, the scale of exposure is, therefore, significant. The researchers report that Yandex has been doing this since at least 2017, while Meta began similar behaviour in late 2024.

Apparent Lack of Disclosure

What makes the findings more concerning is the apparent lack of disclosure to app users, website operators, or browser vendors. For example, developer forums have shown widespread confusion among website owners who were unaware their use of tracking pixels enabled data extraction via app-localhost bridges. Some people reported unexplained localhost calls from Meta’s scripts, with little guidance on what the data was or how it was being used.

Google and Browser Makers Respond

Google, which maintains the Android operating system, has confirmed the tracking method was being used in “unintended ways that blatantly violate our security and privacy principles.” Chrome developers, along with DuckDuckGo and other browser vendors, have now issued patches to block some forms of localhost communication initiated by websites.

Also, Narseo Vallina-Rodríguez, associate professor at IMDEA, noted: “Until our disclosure, Android users were entirely defeated against this tracking method. Most platform operators likely didn’t even consider this in their threat models.”

Countermeasures Rolled Out

As a result of the academic team’s findings, several browser-based countermeasures, such as port-blocking and new sandboxing approaches, are now being rolled out, and Chrome’s patch is reportedly going live imminently.

Meta and Yandex Defend Their Position

In response to the findings, Meta has said it paused the feature and was working with Google to clarify the “application of their policies.”

Yandex, meanwhile, has reportedly denied that any sensitive data was collected, saying that “The feature in question does not collect any sensitive information and is solely intended to improve personalisation within our apps.” However, the researchers argue that the data gathered, including persistent identifiers, browsing activity, and time-stamped behaviour, carries substantial profiling risk.

Privacy Experts Raise the Alarm

Not surprisingly, the episode has drawn some strong criticism from privacy advocates, who argue the tactics used represent a significant overreach and a breach of user trust. For example, the European Digital Rights (EDRi) group issued a statement calling it a “blatant abuse of technical permissions,” while Mozilla Fellow Alice Munyua said the practice “shows exactly why we need more transparency, not less, in how apps interact with user data.”

IMDEA’s Aniketh Girish, one of the study’s co-authors, said the real issue lies in how easily these companies linked users’ web identities to their mobile profiles without any consent or notification.

Implications

For businesses relying on Meta and Yandex advertising tools, the revelations raise fresh questions about the ethical and legal responsibilities of digital marketing. Many companies use Meta Pixel or Yandex Metrica to improve targeting and ad performance, but may now find themselves indirectly involved in opaque data practices.

Businesses Using These Tools Could Be Held Responsible

It seems that businesses using third-party tools like Meta Pixel or Yandex Metrica (e.g. operators and advertisers) aren’t absolved of responsibility if those tools are later found to breach privacy rules. This is because legal and regulatory frameworks such as the UK GDPR place obligations on data controllers to understand and account for how user data is collected and processed, even when using external vendors.

Also, business users and app developers who trust major platforms for analytics and performance tracking may now need to be more cautious.

What Does This Mean For Your Business?

The apparent scale and persistence of this tracking activity reveals more than just a privacy lapse. It shows how trusted platforms may have quietly prioritised data collection over user transparency, thereby exploiting overlooked technical loopholes. The fact that browser-level defences are only now being introduced suggests the issue went unnoticed even by major platform operators.

For UK businesses, the implications are serious. For example, many rely on tools like Meta Pixel or Yandex Metrica for advertising and analytics, but under GDPR, they remain responsible for understanding how data is collected, regardless of who built the tools. This means that if personal data was captured without consent via websites or apps operated in the UK, businesses could be held accountable.

The lack of disclosure to developers and site owners also raises questions about consent and control. If tracking was occurring via localhost connections without their knowledge, they had no way to inform users or adjust settings accordingly. As regulators increase their focus on accountability, ignorance of how embedded tools function is unlikely to offer much protection.

More broadly, this case highlights the need for reform across both mobile platforms and browsers. Researchers say that Android’s local port access requires stronger safeguards, and permission models need updating to prevent similar abuse. Whether that happens will depend on pressure from developers, watchdogs, and public institutions.

At its core, the episode shows how fragile digital trust can be when data is moved behind the scenes without consent. For users and UK businesses alike, the expectation now is not just performance, but clear accountability for how every click and interaction is tracked, stored, and shared.