AI-Powered Annotation: Automotive World Interviews Kognic on Long-Haul Trucking

Daniel Langkilde, Kognic's CEO & Co-founder, was featured as the leading industry expert in a new article published by Automotive World. Automotive World is the leading trade journal for industry executives across global OEM, Supply Chain and Technology partners.

In this interview, Daniel discusses how human feedback and AI work together to accelerate autonomous trucking development. Here's an excerpt from journalist Will Girling's interview with Daniel:

• Human feedback is critical to unlocking efficiency in autonomous trucking. In the article, Langkilde's insights reveal a collaborative effort with Kodiak Robotics, an autonomous truck (AT) developer for the long-haul sector. The partnership demonstrates how integrating scalable human feedback into data pipelines helps teams train autonomous systems faster and more cost-efficiently.
• Langkilde addresses a common misconception about commercial trucking autonomy. "Many thought it would be easier to build autonomous solutions for commercial trucking versus personal driving in urban areas. Turns out, it's not," Langkilde explains to Automotive World. The challenge is that a 'big rig' needs a sensing range greater than or equal to its stopping distance, but LiDAR sensors with 200-250m ranges don't suffice at high speeds carrying heavy loads. The solution requires human expertise: "By creating smarter and faster extrapolations of sensor fusion to fill the sensor range gap, AI can both feed and be fed the solution here," Daniel explains.
• Autonomous trucks (ATs) represent a major leap forward in transportation safety and efficiency, but they require the right data foundation. Jeff Farrah, CEO of the Autonomous Vehicle Industry Association, echoes Langkilde's perspective, highlighting how ATs can address driver shortages and enhance road safety. With human-validated training data guiding AI models, the industry can build autonomous systems that are not only technically capable but also aligned with human expectations for safety and behavior.
• As the industry scales AI integration, the importance of the broader ecosystem becomes clear. Langkilde emphasizes the need for collaboration between technology providers, customers, and regulatory bodies to ensure innovation moves forward responsibly. By demonstrating how human feedback solves real-world transport challenges—making models more reliable, safer, and faster to deploy—the industry can build stakeholder trust and continue scaling successfully.

For the full article, you can access it here (subscription may apply).