For John Kaychi, Senior Group Product Manager for Automated Driving at GM, the future of driving will be defined not only by technical progress, but by whether customers are ready to trust it.
At GM, he leads the product team working on eyes-off driving and how customers experience it. GM’s next major step in automated driving is planned to launch in 2028 beginning with the Cadillac ESCALADE IQ.
“You can have the best technology in the world,” Kaychi said. “But if customers don’t trust it, it won’t stick.”
Kaychi sees the AV industry evolving in three waves: Ridesharing changed behaviors. Robotaxis paved the way for autonomy. Retail, he believes, is where the industry will be tested at scale and has the ability to deliver the biggest customer benefit.
“That’s the edge we’re standing at today,” he said. “The technology is better understood. Hardware is approaching commoditization. The retail market is ready. True autonomy isn’t here yet, but GM is uniquely positioned to lead this next chapter, bringing automated driving to customers at scale.”
Transitioning from driverless demos to a mass-production retail product raises the bar: A controlled demonstration can show technical capability, while a customer product is designed to build confidence through consistent, validated performance over time.
To prepare for real-world driving across the unforgiving "long tail"—inclement weather shifts, sudden road changes and complex human traffic behavior—GM’s product and engineering teams validate against three rich data streams:
- Production retail vehicles sold today, which can provide massive real-world fleet telemetry.
- Next-generation development fleet data engineered for high-precision sensor capture.
- High-fidelity synthetic environments designed specifically to fill the gap on rare edge cases.
Together, these inputs feed a continuous validation loop that refines how the system performs while elevating how the experience feels to the customer. Retail vehicle data is collected with safeguards designed to protect customer privacy. Across each source, data is collected in a disciplined, prioritized manner—focusing systematically on the operational domains that aim to deliver the highest customer value at every step of deployment.
“It’s not just about how the system drives,” Kaychi said. “It’s about how it makes the driver feel. And we’re building for both.”
During Kaychi's tenure at Zoox, he helped launch the company's first employee ridesharing service, deploying autonomous vehicles onto San Francisco's most demanding terrains—steep city hills, blind crests and dense urban corridors around Coit Tower and Lombard Street.
“Getting to see the technology through the eyes of so many people who hadn’t experienced it before reminded me how groundbreaking this technology is and how close we were to making it a reality, especially when operating in a real-world setting with real-world complexity,” Kaychi said. “That moment showed me what was possible, and it continues to shape how I approach scaling autonomy at GM.”
Before eyes-off driving reaches retail customers, GM is combining the production scale of Super Cruise and the autonomous expertise of Cruise. Super Cruise demonstrates GM’s experience scaling complex driver-assistance technology across millions of customer miles. GM is now combining that real-world experience with Cruise’s expertise in AI development and complex testing.
That is why GM’s strategy relies on a deliberate, domain-by-domain rollout, validating each capability against real-world conditions before expanding into the next.
“Eyes-off driving fundamentally changes what routine travel feels like,” Kaychi said. “It transforms time spent behind the wheel into personal bandwidth, giving people space to work, think or simply relax. Automated driving has the power to reclaim that time, and that’s what makes this work so deeply motivating.”
