At the GM Forward event in New York, Chair and CEO Mary Barra unveiled the company’s latest suite of AI-driven mobility initiatives, outlining a roadmap that connects autonomy, conversational intelligence, robotics, and energy innovation into one cohesive vision for the future of driving. She highlighted how GM’s manufacturing scale, software expertise, and AI capabilities are converging to transform vehicles from simple transportation tools into intelligent companions on the road.

One of the most groundbreaking revelations from the event centers on a milestone many thought was still years away: true eyes-off driving for consumers.

GM announced plans to bring eyes-off driving to market in 2028, debuting on the all-electric Cadillac ESCALADE IQ.

With more than 600,000 miles of mapped hands-free roads in North America and 700 million miles driven using Super Cruise without a reported crash, GM is now leveraging insights from Super Cruise—its autonomous division—adding over five million fully driverless miles of validation data.

That foundation of safety systems, technology, scale, and a decade of on-road experience positions GM to lead the next phase of personal autonomy.

Beginning next year, GM vehicles will integrate conversational AI through Google Gemini, allowing drivers to speak to their cars naturally—requesting assistance, directions, or explanations as if speaking with a passenger.

Future versions will introduce GM’s own vehicle-specific AI, fine-tuned with user preferences and the car’s unique intelligence, all connected through OnStar.

The goal: a personal driving companion capable of explaining new features, predicting maintenance needs, and even suggesting dinner spots en route.

In 2028, GM will debut a centralized computing architecture, beginning with the Cadillac ESCALADE IQ. This overhaul represents a full reimagining of how vehicles are designed, updated, and improved throughout their lifetime. Built to power both electric and gas vehicles, the platform unites every major system — from propulsion and steering to infotainment and safety — on a single, high-speed computing core.

The impact is significant. By consolidating once-separate systems into one unified brain, GM vehicles can process vastly more data in real time, respond faster to driving conditions, and seamlessly integrate new capabilities through software updates.

The result:

• 10× greater over-the-air software update capacity
• 1,000× more bandwidth
• 35× increase in AI performance for autonomy and advanced features

This foundation is designed for continuous learning and improvement, allowing vehicles to evolve long after they leave the showroom. It’s not just a performance upgrade — it’s the infrastructure for an era where cars improve with age, powered by intelligent software that keeps learning every mile.

At the Autonomous Robotics Center (ARC) in Warren, Michigan, and its sister lab in Mountain View, California, more than 100 roboticists and AI engineers are training collaborative robots—cobots—on decades of GM production data.

Using telemetry, quality metrics, and sensor feeds, these systems learn from every manufacturing cycle to improve safety, precision, and efficiency.

GM plans to deploy cobots across its U.S. assembly plants, creating adaptive environments where intelligent machines work seamlessly alongside people, improving workplace safety and enhancing the quality of work environments.

GM’s vision for intelligent mobility extends beyond the road and into the home. Many new GM electric vehicles (EVs) are already capable of providing backup power, transforming parked cars into mobile energy assets. In the near future, GM plans to expand this capability from powering homes during outages to supporting the broader electrical grid through vehicle-to-grid (V2G) programs.

Beginning in 2026, GM will offer its GM Energy Home System, combining bi-directional EV charging, a stationary home battery, and optional solar integration. The system will first roll out to GM EV owners through a leasing model, with broader availability to follow.

This unified approach positions the vehicle as part of a connected household energy ecosystem. Homeowners will be able to use their vehicle to keep lights on during emergencies, shift power use during peak hours, or participate in grid-support programs that could eventually help lower energy costs.

A dedicated smartphone app acts as the control hub, offering energy management tools, usage insights, and future capabilities like automated enrollment in vehicle-to-grid programs. The system is designed to evolve over time, allowing customers to unlock new energy features through software updates as infrastructure and policy advance.

Q1: What does “eyes-off driving” mean in GM’s roadmap?
A: Starting in 2028 with the Cadillac ESCALADE IQ, drivers will be able to take their eyes off the road under approved conditions, enabled by data from Super Cruise and Cruise autonomous systems.

Q2: How will conversational AI work in GM vehicles?
A: Beginning in 2026, cars will include Google Gemini-powered voice interaction, followed by a GM-custom AI that learns driver preferences and supports tasks via OnStar.

Q3: What’s the significance of GM’s unified computing platform?
A: The new architecture boosts software-update capacity 10×, bandwidth 1,000×, and AI performance 35× across all vehicle systems.

Q4: How is GM using robotics in manufacturing?
A: GM trains cobots at its ARC and Mountain View facilities to improve safety and efficiency.

Q5: What role do GM’s electric vehicles play in home energy systems?
A: New GM EVs support bi-directional charging and future vehicle-to-grid services, powered by the GM Energy Home System.

GM’s latest announcements signal a shift in how automotive autonomy may evolve: not through rapid consumer release cycles, but through long-horizon engineering, structured validation, and hybrid human-AI systems designed to scale responsibly.

Eyes-off driving represents one of the most ambitious milestones in the industry. Rather than pursuing a vision-only approach, GM is leaning on redundancy, mapped-road validation, and years of safety data, reflecting a view that autonomy must earn trust gradually and transparently.

GM and Tesla are pursuing autonomy with two fundamentally different philosophies:

• GM uses mapped highways, multi-sensor redundancy, and driver-monitoring to expand certified “eyes-off” zones step-by-step.

• Tesla trains primarily through real-world vision-based learning, with systems like Autopilot and Full Self-Driving (FSD) that still require active supervision today.

GM reports 600,000 miles of mapped hands-free roads, 700 million miles driven with Super Cruise, and 5 million fully driverless miles via Cruise, providing a tightly validated foundation for scaling autonomous features.

Tesla, meanwhile, reports over one billion real-world miles using Autopilot and FSD systems combined, though it does not publish mileage attributed to mapped-road validation or certify eyes-off conditions in production environments.

This distinction does not suggest superiority; rather, it highlights two different safety and deployment strategies emerging within consumer autonomy.

Real autonomy is not only a technical milestone, but a trust milestone. The next frontier is proving to drivers that intelligent systems can be relied on, understood, and monitored safely.

For most drivers, safety confidence matters more than software releases. GM’s long-term validation strategy reflects a growing industry trend: pairing AI performance with multi-layer safeguards, emphasizing predictable expansion, traceable validation, and transparent safety checks. This approach reflects a larger shift in mobility toward systems that blend automation with human oversight, rather than fully removing the driver from the loop on day one.

At the same time, its conversational AI, unified vehicle computing platform, and bi-directional energy systems point toward a future where vehicles:

• learn and adapt over time
• support grid-aware home energy use
• anticipate driver needs and context
• improve continuously through software

The result is a vehicle that is not only autonomous — but attentive.

By merging AI, robotics, and energy innovation, GM is signaling an era where cars evolve with their owners. The next decade won’t simply redefine driving; it will redefine trust between humans and intelligent systems, introducing mobility experiences where intelligence enhances control rather than replacing it.

In a mobility landscape where progress will be judged by safety, transparency, and user confidence, GM’s approach reflects a future built not just on autonomy, but on responsible autonomy — vehicles that understand context, manage energy responsibly, and earn trust over time.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant used for research and drafting. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.