Humanoid Robots: The Next Big Challenge Revealed

At a recent World Economic Forum panel in Davos, three leading robotics experts moved beyond the hype to address the fundamental challenges facing the humanoid robot industry. While demonstrations of robots performing parkour and kung-fu capture headlines, the panel focused on the difficult path toward real-world utility and large-scale deployment.

The discussion, moderated by Jamie Heller, highlighted a critical gap between laboratory capabilities and practical applications. Experts from Gecko Robotics, Mech-Mind, and MIT outlined the technological and logistical hurdles that must be cleared before humanoid robots can become a common presence in workplaces and homes.

The central issue facing the industry is not creating a robot that can walk, but one that can work reliably in unpredictable environments. Jake Loosararian, CEO of infrastructure startup Gecko Robotics, identified deployment as the most significant hurdle.

"Deployment is the big problem right now for robotics, in terms of the ability for it to begin to make really large impacts, and for there to be a clear road map," said Loosararian.

Loosararian emphasized that building reliable datasets about real-world environments is critical. Unlike the controlled settings of a laboratory or the curated data available online, robots need firsthand experience with the complexities of physical spaces.

• Forward deployment near actual work sites
• Building robots in environments they will operate in
• Creating unique datasets unavailable on the internet

This approach, he argued, provides the essential information needed for robots to function effectively outside of staged demonstrations.

Even when a robot can perform a task, the cost remains prohibitively high for most applications. Daniela Rus, director of MIT's Computer Science and Artificial Intelligence Laboratory, illustrated this gap with a stark example.

"I can give you a robot that will fold your laundry and load your dishwasher, but it might cost you half a billion dollars," she said.

Bridging the divide between laboratory prototypes and affordable consumer products requires significant advancements in two key areas. First, robots need improved sensors to better perceive and manipulate the world around them. Second, they require new AI models capable of handling unexpected situations and adapting to environments they have not encountered before.

These technological leaps are essential for transforming expensive, single-task machines into versatile, cost-effective assistants capable of taking on jobs traditionally performed by humans.

A major revelation from the panel was the industry's reliance on human operators to control robots remotely. Loosararian referred to this practice as the "dirty little secret" of robotics, noting that many impressive public demonstrations are not fully autonomous.

Teleoperation, where a human pilot controls a robot from a distance, is currently a common method for teaching robots new tasks and navigating complex environments. While effective for learning, it highlights the current limitations of autonomous artificial intelligence.

"There's a lot of autonomy for certain tasks, but for the majority of the cases, for humanoids, it's learning in the environment, and it has to do that with teleoperation," Loosararian explained.

He stressed that robotics companies have an ethical responsibility to be transparent with customers about whether their robots are operating autonomously or with human assistance.

Despite the challenges, there is a clear vision for how humanoid robots can begin delivering value in the near term. Shao Tianlan, CEO of Chinese AI and robotics firm Mech-Mind, outlined a practical approach for factory environments.

Tianlan believes that demonstration is the most intuitive way to teach robots, mirroring how humans learn from one another. He also noted that humanoid robots do not need "Einstein-level" intelligence to perform useful tasks effectively.

"If we want to deploy a robot, I would say demonstration is the most intuitive way to tell robots what to do. That's exactly how we humans teach others," he said.

With Mech-Mind having delivered over 10,000 "intelligent robots" in the last year, Tianlan predicted that humanoid robots will soon take on specific roles in controlled settings.

• Logistics and warehouse operations
• Service industries in structured environments
• Manufacturing assembly lines

He projected that these deployments will occur within the next "few hundred days," signaling a shift from experimental technology to practical tool.

The path forward for humanoid robots is less about flashy parkour and more about solving fundamental engineering and economic challenges. The consensus among experts is that the industry must focus on deployment, cost reduction, and transparency to move beyond the current hype cycle.

While companies like Tesla and Figure prepare for large-scale manufacturing, the real work lies in creating reliable, affordable systems that can operate autonomously in the real world. The next few years will be critical in determining whether humanoid robots can transition from impressive prototypes to indispensable tools in workplaces and homes.