--- title: "The Next Robotics Race Isn’t About More Robots" id: "10627" type: "post" slug: "the-next-robotics-race-isnt-about-more-robots" published_at: "2026-08-10T12:48:56+00:00" modified_at: "2026-08-10T12:48:56+00:00" url: "https://capow.energy/blog/articles/the-next-robotics-race-isnt-about-more-robots/" markdown_url: "https://capow.energy/blog/articles/the-next-robotics-race-isnt-about-more-robots.md" excerpt: "For years, the question was how much of the warehouse could be automated. Today, as fleets scale from dozens to hundreds, thousands and beyond, a different question deserves attention." taxonomy_category: - "Articles" taxonomy_author: - "Rebecca" --- ![Image](https://capow.energy/wp-content/uploads/2026/08/ChatGPT-Image-Aug-10-2026-03_39_26-PM.png) - [Articles](https://capow.energy/blog/articles/) # The Next Robotics Race Isn’t About More Robots - [Rebecca](https://capow.energy/author/rebecca-barelcapow-tech-com/) - August 10, 2026 Warehouse robotics has entered a new phase. For years, the question was how much of the warehouse could be automated. Today, as fleets scale from dozens to hundreds, thousands and beyond, a different question deserves attention: **How much productive work are we actually getting from the robots already deployed?** [Book a Meeting](#hubspot-form) Amazon provides a useful illustration of why this question matters. In June 2025, Amazon announced the deployment of its **one millionth robot**, with its robotics network spanning more than **300 facilities worldwide**. At the same time, the company introduced DeepFleet, an AI foundation model designed to coordinate robot movement. Amazon says DeepFleet can improve robot fleet travel time by **10%**. [Amazon’s announcement on its one millionth robot and DeepFleet](https://www.aboutamazon.com/news/operations/amazon-million-robots-ai-foundation-model?utm_source=chatgpt.com) The important signal isn’t simply the size of the fleet. **It’s what becomes important once robotics reaches that scale.** ## **From More Robots to Fewer Constraints** The Supply Chainer recently explored this shift in its coverage of Amazon’s continued investment in warehouse robotics. The article looks beyond the robots themselves to the operational constraints that can limit automated systems, including charging, congestion and upstream processes. As CaPow CEO and Co-Founder Prof. Mor Peretz told The Supply Chainer: **“The objective isn’t to automate a task. It’s to remove the constraint that limits throughput.”** [The Supply Chainer on Amazon’s robotics expansion](https://www.thesupplychainer.com/post/amazon-doubles-down-on-warehouse-robotics-with-new-georgetown-sortation-centre?utm_source=chatgpt.com) That distinction matters. A robot can be highly capable and still operate inside a system that prevents it from being continuously productive. It can wait. It can encounter congestion. Upstream processes can interrupt its flow. And depending on the fleet architecture, it may need to leave productive operation to recharge. At small scale, those interruptions may appear manageable. **At large scale, percentages become capacity.** ## **When 12.5% Becomes 125,000 Robots** Independent researcher Parth Mahajan recently used a thought experiment to illustrate exactly that. [CaPow’s Hyundai Glovis](https://capow.energy/blog/news/capow-helps-achieve-100-uptime-for-hyundai-glovis/) proof of concept measured an approximately **6.75:1 work-to-charge ratio** for the conventionally charged comparison fleet. Mahajan then used Amazon’s publicly reported fleet size as a deliberately hypothetical illustration. Rounded to a **7:1 work-to-charge ratio**, charging represents approximately **12.5% of the operating cycle**. Apply that percentage to a theoretical fleet of one million robots: ### **1,000,000 × 12.5% = 125,000** In Mahajan’s illustrative model, that translates to the equivalent of roughly **125,000 robots charging at a given time**. This requires an important qualification. **It is not a claim, estimate or measurement of Amazon’s actual operations.** Amazon’s actual charging architecture, utilization, scheduling and fleet operating patterns are not established by this calculation. Mahajan explicitly presents it as a counterfactual illustration. Read Parth Mahajan’s analysis And that is exactly why the exercise is interesting. **The important number isn’t 125,000. It’s 12.5%.** At 10 robots, a percentage can look insignificant. At 100, it becomes noticeable. At 10,000, it becomes capacity. At one million, it becomes a strategic question. **Scale doesn’t just multiply robots. It multiplies every constraint around them.** ## **Before Adding Capacity, Measure What Is Consuming It** When an automated operation needs more throughput, adding robots may be one answer. But there is another question worth asking first: **What is preventing the capacity already on the floor from being fully productive?** How much time is spent waiting? Where does congestion occur? Which upstream processes interrupt flow? How much productive availability is lost to charging? And what happens to each of those numbers when the fleet doubles? Charging is not the only constraint, nor is it necessarily the largest constraint in every operation. But the principle is broader: **Before adding capacity, measure what is consuming it.** ## **The Robot Is Only One Part of the System** The industry has spent years making robots better. Navigation is improving. Perception is improving. Fleet management is becoming more sophisticated. AI is improving coordination. Amazon’s DeepFleet is one example of the growing focus on [optimizing the operation](https://capow.energy/blog/articles/amr-charging-and-agv-charging-how-oems-can-optimize-operations-with-in-motion-power-delivery/) of the **fleet**, rather than simply improving an individual robot. Energy deserves to be considered through the same operational lens. For mobile robots, energy is connected to movement, routes, scheduling and availability. If obtaining energy requires a robot to interrupt productive operation, charging is no longer simply a battery specification. **It becomes an operational variable.** The same thinking applies to congestion, waiting, workflow and every other constraint that prevents a robot from doing productive work. ## **The Question Is Changing** The first chapter of warehouse robotics asked: **Can a robot do the job?** The next asked: **Can we deploy robots reliably at scale?** Now another question is emerging: **How do we get more productive capacity from the fleets already deployed?** Because as fleets become larger, even relatively small improvements in availability, movement efficiency or waiting time can represent meaningful operational capacity. The next robotics race may not be defined only by who deploys the most robots. **It may be defined by who becomes best at removing the constraints that stop them.** ### **Sources** [Amazon – One million robots and DeepFleet](https://www.aboutamazon.com/news/operations/amazon-million-robots-ai-foundation-model?utm_source=chatgpt.com) [The Supply Chainer – Amazon Doubles Down on Warehouse Robotics With New Georgetown Sortation Centre](https://www.thesupplychainer.com/post/amazon-doubles-down-on-warehouse-robotics-with-new-georgetown-sortation-centre?utm_source=chatgpt.com) Parth Mahajan – CaPow: Can the Warehouse Floor Become the Charger? https://parthresearch.substack.com/p/capow-can-the-warehouse-floor-become?r=u7kur&utm_medium=ios&utm_source=notes-share-action ## Author - [Rebecca](https://capow.energy/author/rebecca-barelcapow-tech-com/) Rebecca Barel - Head of Marketing | CaPow [View all posts](https://capow.energy/author/rebecca-barelcapow-tech-com/) [mailto:Rebecca.barel@capow-tech.com](mailto:Rebecca.barel@capow-tech.com) [https://capow.energy/about/](https://capow.energy/about/) [Book a Meeting](#hubspot-form) ## Categories ## Similar [https://capow.energy/blog/articles/unlocking-cost-savings/](https://capow.energy/blog/articles/unlocking-cost-savings/) - [Articles](https://capow.energy/blog/articles/) ### [Unlocking Cost Savings: Getting More From the Mobile Robots Already on Your Manufacturing Floor](https://capow.energy/blog/articles/unlocking-cost-savings/) [Read More](https://capow.energy/blog/articles/unlocking-cost-savings/) [https://capow.energy/blog/articles/the-productivity-ceiling-no-one-planned-for/](https://capow.energy/blog/articles/the-productivity-ceiling-no-one-planned-for/) - [Articles](https://capow.energy/blog/articles/) ### [The Productivity Ceiling No One Planned For](https://capow.energy/blog/articles/the-productivity-ceiling-no-one-planned-for/) [Read More](https://capow.energy/blog/articles/the-productivity-ceiling-no-one-planned-for/) [https://capow.energy/blog/articles/why-energy-architecture-is-becoming-a-strategic-discipline/](https://capow.energy/blog/articles/why-energy-architecture-is-becoming-a-strategic-discipline/) - [Articles](https://capow.energy/blog/articles/) ### [The Missing Layer in Warehouse Automation: Why Energy Architecture Is Becoming a Strategic Discipline](https://capow.energy/blog/articles/why-energy-architecture-is-becoming-a-strategic-discipline/) [Read More](https://capow.energy/blog/articles/why-energy-architecture-is-becoming-a-strategic-discipline/)