General Motors Co. has once again stirred the automotive industry with ambitious promises of advanced technology, but for many observers, the announcements evoke a strong sense of familiarity. At a recent event in New York, GM outlined plans to integrate artificial intelligence and autonomous driving features into its vehicles, aiming to transform cars into intelligent companions. Central to this vision is the rollout of “eyes-off, hands-off” driving technology by 2028, allowing drivers to disengage completely from the wheel under certain conditions.

This push comes amid a broader strategy to leverage software and AI to differentiate GM’s lineup. Starting in 2026, vehicles will incorporate Google’s Gemini AI for conversational interactions, enabling features like natural language queries for navigation or vehicle diagnostics. Yet, as detailed in a recent analysis by Digital Trends, these declarations are giving industry veterans deja vu, reminiscent of earlier unfulfilled pledges in self-driving tech from companies like GM’s own Cruise division.

Echoes of Past Promises

The deja vu stems from GM’s history with autonomous vehicles. Back in 2017, the company touted Super Cruise as a breakthrough in hands-free driving, but scaling it to full autonomy has faced regulatory hurdles, technical glitches, and safety concerns. Now, with the 2028 target, GM is betting on advancements in lidar, radar, and machine learning to enable eyes-off capabilities on highways and select urban areas.

Industry insiders note that competitors like Tesla Inc. and Waymo have set high bars, yet GM’s timeline aligns with a wave of similar announcements. According to reporting from CNBC, GM’s “GM Forward” event also highlighted a single software platform to unify its electric and internal-combustion vehicles, potentially streamlining updates and monetizing subscriptions.

AI Integration and User Experience

Delving deeper, GM’s partnership with Google for Gemini AI promises to make interactions more intuitive. Imagine asking your car to adjust climate controls based on weather forecasts or suggest routes avoiding traffic—all powered by cloud-connected AI. This builds on GM’s OnStar system but aims for a more seamless, voice-driven experience.

However, skepticism abounds. Digital Trends points out that while the tech sounds revolutionary, execution challenges like data privacy and integration with existing hardware could delay rollout. Moreover, GM’s decision to phase out Apple CarPlay and Android Auto in favor of its proprietary infotainment has sparked backlash, as noted in coverage by Carscoops, where CEO Mary Barra defended the move as essential for a cohesive user interface.

Regulatory and Safety Hurdles

For eyes-off driving to become reality, GM must navigate a thicket of regulations. The National Highway Traffic Safety Administration has tightened scrutiny following incidents with autonomous systems, demanding rigorous testing. GM plans to deploy this tech initially in premium models like the Cadillac Escalade, expanding based on real-world data.

Insiders worry about overpromising, echoing the 2010s when GM acquired Cruise for $1 billion, only to see it mired in accidents and lawsuits. A piece in Daily Mail Online highlights consumer fury over ditching popular features, suggesting GM’s tech pivot could alienate buyers if not handled carefully.

Broader Industry Implications

Beyond autonomy, GM is investing in robotics for manufacturing, including “cobots” to assist human workers, as reported by Electric Cars Report. This could lower costs and boost efficiency, positioning GM against rivals like Ford Motor Co., which is doubling down on CarPlay integration.

Ultimately, while GM’s announcements signal a bold future, the deja vu underscores a familiar pattern: groundbreaking tech often meets real-world friction. Success will hinge on overcoming technical barriers and regaining consumer trust, potentially reshaping how we interact with vehicles in the coming decade. As the industry watches, GM’s ability to deliver on these promises by 2028 will be a litmus test for the viability of AI-driven mobility.