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.