In the high-stakes world of industrial innovation, where aging infrastructure meets cutting-edge technology, Gecko Robotics is emerging as a pivotal player. Founded by Jake Loosararian, the Pittsburgh-based company deploys AI-powered robots to inspect and maintain critical assets in sectors like energy, manufacturing, defense, and public infrastructure. These robots—capable of climbing walls, flying as drones, or swimming through pipes—collect vast amounts of real-world data that traditional methods overlook, turning physical structures into digital intelligence. As Loosararian emphasized in a recent CNBC Closing Bell Overtime interview, without robust data sets, even the most advanced AI algorithms are reduced to mere “math tricks,” unable to drive meaningful efficiencies.

This data deficit is AI’s “dirty secret,” as Loosararian put it, particularly in industries where digital transformation has lagged. Energy companies, for instance, grapple with outdated power plants prone to forced outages and explosions, while manufacturing giants face siloed information that hampers predictive maintenance. Gecko’s approach addresses this by fusing robotics with AI to decode the “world of atoms” into usable bits, enabling clients to optimize operations and reduce risks.

The Data Race: Fueling AI’s Industrial Engine

Loosararian’s insights align with broader industry trends, where the absence of high-quality, real-time data stifles AI’s potential. In his Fortune article titled “AI’s Dirty Secret: Without Data, It’s Just Math Tricks,” he argues that sectors like defense and energy have been “forgotten” by Silicon Valley’s digital focus. Gecko’s robots bridge this gap by gathering data on metal integrity, vibration, temperature, and more, offering a 10x return on existing data investments. This is crucial as global infrastructure ages—36% of U.S. bridges need major repairs, according to posts on X highlighting robots fixing America’s failing systems.

Recent funding rounds underscore investor confidence in this model. Gecko achieved unicorn status with a $1.25 billion valuation after raising $125 million, as reported by The Robot Report. This capital is accelerating expansion into defense and energy, where governments are awakening to asset vulnerabilities. CNBC recognized Gecko as No. 30 on its 2025 Disruptor 50 list, praising its fleet of AI-assisted robots for analyzing asset health.

From Inspection to Predictive Power: Real-World Applications

CEOs in metal manufacturing, mining, and energy are voicing frustration over hyped AI solutions that fail to deliver ROI, Loosararian noted in the CNBC discussion. Gecko differentiates by providing actionable insights, such as improving heat rates in power plants to cut BTUs and boost kilowatts, or slashing shutdown days to prevent costly outages. Case studies from clients demonstrate this: one energy firm used Gecko’s wall-climbing robots to identify corrosion early, averting a potential explosion and saving millions in downtime.

This predictive maintenance capability is transforming operations. As detailed in a World Economic Forum podcast, bridging AI’s data gaps can save lives, reduce emissions, and enhance factory safety. Gecko’s integration of AI with robotics allows for continuous monitoring, turning raw data into efficiency gains. In manufacturing, where factories generate 12TB of data daily but 77% goes unused, per X posts on data alchemy, Gecko’s tech enables predictive quality analysis, much like Siemens’ AI models for welding seams.

Government and Societal Imperatives: Investing in the Future

Not all sectors have the capital for such innovations, raising questions about broader societal investment. Loosararian, speaking at the “Winning the AI Race” event in Washington, D.C., stressed that nations mastering data collection will dominate the AI era. Governments must prioritize this, he argued, as physical infrastructure—like bridges and refineries—lacks the digital fuel for AI algorithms. Without it, economies risk falling behind, especially as China ramps up real-world data gathering, according to a Reuters Connect report.

This urgency is echoed in market projections. The service robotics sector, including players like Gecko, is forecasted to grow significantly by 2035, with AI-driven robots in manufacturing and logistics reaching a $258 billion market, as per WebProNews. Yet challenges remain: ethical concerns, regulatory hurdles, and the need for skilled workers to interpret this data deluge.

Unicorn Status and Beyond: Gecko’s Growth Trajectory

Gecko’s rise to unicorn status, co-founded by Armenian-American entrepreneur Loosararian, reflects surging demand for its build and modernization capabilities. As Yahoo Finance notes, over 70% of Q1 2025 robotics funding targeted task-centric tech like Gecko’s, focusing on “boring” but essential infrastructure tasks. The company’s ranking improved from 42nd to 30th on CNBC’s Disruptor 50, signaling its momentum.

Looking ahead, Gecko is poised to influence global standards. By addressing the data wall—where real-world information is scarce—it’s enabling AI to tackle climate change and improve productivity. In defense, robots inspect military systems, enhancing national security. X posts celebrate this as robots repairing U.S. infrastructure, from oil refineries to bridges, potentially creating safer, high-paying jobs amid workforce shifts.

Challenges and Opportunities: Navigating the AI Data Frontier

Despite successes, adoption barriers persist. Industrial sectors often see a 4:1 ratio of workers leaving versus entering, per Loosararian, exacerbating skills gaps. Gecko aims to accelerate entry by making jobs safer and more efficient through robotics. However, scaling requires collaboration: companies must integrate Gecko’s data with existing systems, while governments invest in infrastructure digitization.

Emerging Tech Brew highlighted how Gecko pivoted to AI after a data dive revealed its necessity for infrastructure-inspecting robots. This “no-brainer” addition has supercharged their offerings, allowing for human-robot collaboration in predictive tasks. As AI evolves, Gecko’s model—collecting and analyzing physical data—could redefine efficiency, reducing costs by up to 20% in manufacturing, according to X discussions on predictive maintenance.

The Path Forward: Winning the AI Race Through Data

Ultimately, Loosararian’s message is clear: data is the fuel for AI’s Ferrari-like algorithms. Nations and companies that invest in decoding the physical world will lead. Gecko’s innovations, from climbing robots to fixed sensors, are already proving this in energy and defense, where efficiencies translate to billions in savings. As StartupHub.ai describes, data is AI’s unsung