Your next car might do more than remember your seat position or follow a command: it could use context to anticipate what help you need. That is the vision Demetris Skourides, Cyprus’s Chief Scientist for Research, Innovation and Technology, describes in a Hindustan Times interview—not a claim that today’s cars already offer all of these capabilities. The idea raises a practical question alongside the promise: what may a car infer or do, and what must remain under the driver’s control?
From remembering settings to understanding intent
Most vehicle interfaces are command-driven: a person selects a destination, adjusts a setting or asks for a specific function. Skourides describes a possible shift toward vehicles that interpret a person’s situation and offer relevant assistance. The progression is from configuration memory—retaining preferences—to contextual personalization, in which the vehicle uses circumstances to decide what might be useful.
| Interaction | What the car does | What remains uncertain |
|---|---|---|
| Command-based control | Responds to an explicit instruction, such as entering a destination. | The driver still identifies the task and initiates it. |
| Configuration memory | Recalls settings or preferences. | Remembering a preference does not establish permission to act in other contexts. |
| Intent-oriented assistance | Uses context to suggest or prepare a potentially useful action. | The article presents this as an emerging direction, not a feature available in every vehicle. |
| Authorized action | Could carry out a task within boundaries the owner or driver has approved. | Permissions, review, reversibility and accountability must be made clear. |
Skourides calls the broader change “The automobile is becoming an AI-defined machine.” His point is not simply that more software will appear in cars, but that vehicles may become more capable of interpreting context and coordinating tasks.
What a context-aware car might do
The interview uses examples such as coordinating navigation, charging and notifications to illustrate the vision. A vehicle might, for instance, connect a route with a charging need or manage when information is surfaced to the driver. These examples describe possible assistance, not universal or confirmed production features.
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There is an important distinction between a recommendation and an action. A car can suggest a charging stop without booking or paying for it; it can propose a notification setting without changing it. Any step beyond advice depends on what the driver has explicitly authorized and whether the system explains what it is doing.
More agency should not mean less human authority
Skourides puts the boundary plainly: “An intelligent vehicle must understand not only what it can do, but what it is authorized to do.” He argues that automation should expand what people can accomplish, while leaving them in charge of purpose, permissions and consequential decisions: “Greater machine agency should not mean less human authority. It should mean greater human capability.”
That principle makes the design questions concrete. Before a vehicle can act on someone’s behalf, drivers need to know what information it uses, what it may remember or share, whether it can spend money, and how to inspect or reverse a decision. Skourides also says that sophisticated technology should return attention rather than demand more of it: “The most sophisticated technology should not demand more of our attention. It should give us our time and attention back.”
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Why trust, security and accountability matter
A vehicle that connects with charging services or other mobility providers would operate beyond its own dashboard. That creates challenges around identity, cybersecurity, interoperability, liability, consumer protection and payments. For example, a driver needs confidence that a service request is tied to the right person and vehicle, that sensitive data is protected, and that a disputed transaction can be traced to a responsible party.
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- Privacy and transparency: Drivers need understandable information about what data is used, retained or shared.
- Permissions and oversight: The scope of permitted actions should be explicit, with human approval for consequential choices.
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- Interoperability and consumer protection: Different vehicle and mobility services must work together without obscuring terms, costs or recourse.
These are not secondary details to solve after adding an AI assistant. They determine whether a vehicle’s greater capability is useful and trustworthy in everyday use.
What current industry figures do—and do not—show
PwC’s 2026 Global Automotive Outlook offers evidence that automotive companies expect broader use of advanced technologies, but it does not measure how many cars already have context-aware AI agents.
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| PwC survey finding | What it means |
|---|---|
| 47% current median share | Among surveyed automotive respondents, the median share using advanced technologies to a large or very large extent across value-chain activities, as reported in PwC’s 2026 outlook. |
| 72% expected median share by 2030 | Respondents’ expectation for the same measure by 2030; it is a survey expectation, not a measured future result. |
| Nearly two-thirds pursuing ecosystem participation | PwC reports that nearly two-thirds of surveyed automotive companies are pursuing participation in ecosystems. |
PwC based the outlook on 720 automotive executives at original equipment manufacturers and Tier 1 suppliers across 33 countries, surveyed in March and April 2026. The figures concern company-reported technology use and plans across automotive value-chain activities, not the prevalence of agentic features in consumer vehicles.
The Hindustan Times article also cites examples of companies pursuing different combinations of vehicle computing, AI, software architecture, driver assistance and manufacturing intelligence, including NVIDIA, Google, Mercedes-Benz, BYD and Tesla. Those examples are not a like-for-like comparison of their products or proof that any one company has delivered the full context-aware assistant described here. The article’s further AI-investment and vehicle-shipment figures are not independently established by the sources available for this account, so they are not used as verified industry statistics.
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What to look for as the idea develops
For drivers evaluating future vehicle features, the meaningful test is not whether a car is marketed as intelligent, but whether its boundaries are legible and manageable. Useful questions include:
- Can the vehicle explain why it is making a suggestion or taking an action?
- Can the driver separately control what the car remembers, shares and is allowed to do?
- Does an action involving money, a booking or a consequential decision require confirmation?
- Can the driver review, cancel or reverse an action, and find out who is responsible if it goes wrong?
Those checks distinguish helpful automation from a system that quietly takes authority away from the person using it.
Quick Recap
Sources
- Hindustan Times / HT Tech, “Your next car could know what you want before you tell it: Cyprus Chief Scientist,” updated October 5, 2026.
- PwC, “AI adoption across automotive value chain to surge as sector grapples with rising competition: PwC,” September 24, 2026.
- KPMG, “KPMG Global Tech Report 2026: Automotive.”
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