- Robotics at the tipping point — once science fiction, robots are now scaling across industries, powered by cheaper sensors, smarter AI, falling hardware costs, and record investment.
- Explosive growth ahead — the global robotics market is set to grow from $74B in 2025 to $373B by 2035 (17.5% CAGR), led by Asia Pacific and North America.
- Forces driving adoption — supply-side advances (+176% performance, –99.7% cost in 29 months) and demand-side pressures (labor shortages, incentives, supply chain resilience) are converging to accelerate adoption.
- Cross-industry impact — robots are already delivering measurable gains: 30% lower production costs in manufacturing, 21% fewer surgical complications, 20–40% lower logistics labor costs, and 90% less pesticide use in agriculture.
- A new platform shift — robotics will redefine business models much like the gig economy did, creating trillion-dollar ecosystems through Robotics-as-a-Service, AI-driven supply chains, and human–robot collaboration.
From Fiction to Function: Introduction to Robotics
When we hear the word robot, our minds often jump to images from science fiction—machines shaped like humans, performing tasks with mechanical precision. But what exactly is a robot in the real world?
According to the Oxford Dictionary, the term has three definitions:
- (Especially in science fiction) a machine resembling a human being and able to replicate certain human movements and functions automatically.
- A machine capable of carrying out a complex series of actions automatically, especially one programmable by a computer.
- A person who behaves in a mechanical or unemotional manner.
For our purposes, we can skip definition number three—we’re not here to discuss robotic personalities. Instead, we’ll focus on definitions one and two, which capture the essence of robotics as both science and technology.
Google’s AI Overview offers a more detailed description:
A robot is an autonomous machine, often computer-controlled, that can sense its environment, process information, and perform complex tasks in the physical world. Key characteristics often include programmability, the ability to execute actions autonomously, and interaction with the real world through sensors and actuators—following the classic “sense-think-act” model.
Core Characteristics of Robots
- Autonomy: Robots can operate and make decisions without constant human supervision.
- Physical Presence: Unlike software, robots exist in the physical world and interact directly with their surroundings.
- Sensors: They gather data about their environment—whether through cameras, microphones, or tactile sensors.
- Computation: Using onboard computers, robots analyze sensor data to make decisions.
- Actuation: Robots act on those decisions by moving, manipulating objects, or otherwise engaging with the world through motors and actuators.
- Programmability: Their behavior is driven by instructions or algorithms, allowing for complex and repeatable tasks.
A Brief History…
The word robot comes from the Czech word robota, meaning “forced labor” or “servitude.” It was first introduced in the 1920 play R.U.R. (Rossum’s Universal Robots) by Karel Čapek. The play’s artificial beings were designed to serve humanity, setting the stage for how we’ve imagined robots ever since.
The dream of human-like robots has been around for decades. Japan spearheaded much of the early work, most famously with Honda’s ASIMO in the early 2000s. ASIMO could run, dance, climb stairs, kick a soccer ball, and even recognize faces and voices. For nearly two decades, it was a celebrity in the robotics world before Honda retired the project in 2018.
Beyond Humanoids
While humanoid robots often capture the public imagination, the world of robotics is far more diverse. Today’s market features a wide range of robot types, each designed with specific applications in mind.Here are eight of the most prevalent:
| Robot Type | Description | Example Use-Case |
|---|---|---|
| SCARA (Selective Compliance Articulated Robot Arm)  | Compact, fast arm with horizontal movement ideal for assembly and packaging | Electronics Assembly |
| Delta Robot  | High-speed parallel robot for light material handling and sorting | Pharmaceutical Packaging |
| AMR (Autonomous Mobile Robot)  | Self-driving robots that navigate environments using sensors and AI | Hospital delivery |
| AGV (Automated Guided Vehicle)  | Path-following mobile robot using tracks, magnets, or markers | Factory pallet transport |
| Articulated Robot  | Multi-joint arm with 4–6 degrees of freedom, common in manufacturing | Welding |
| Cartesian Robot  | Robot with three linear axes (X, Y, Z) for precision tasks. | 3D printing |
| Cobot (Collaborative Robot)  | Designed to safely work alongside humans without barriers. | Quality inspection |
| Humanoid Robot  | Human-shaped robots for dynamic environments and interaction | Customer service |
The Forces Propelling Robotics Forward
The robotics market is experiencing unprecedented growth. To understand what’s fueling this surge, it helps to separate the forces at play into two categories: supply-side drivers (technological enablers that make robots more capable and affordable) and demand-side drivers (market pressures and incentives that accelerate adoption). Together, these factors explain not only why robotics is booming today but also where it is headed next.
Supply-Side Drivers
Sensor Cost Decline
Sensors are the eyes and ears of robotics—essential for perception and navigation. Once prohibitively expensive, sensor costs have plummeted thanks to scale, innovation, and heavy investment. For example, according to AutoNews, Waymo slashed the cost of its LiDAR sensors from about $75,000 in 2009 to just $7,500 by 2017. As sensors continue to improve in both performance and affordability, robots are becoming far more practical for widespread deployment.
AI Model Efficiency
One of the most important enablers of robotics today is the rapid improvement in AI model efficiency. As the chart below shows, models have advanced dramatically in just two years. In 2023, GPT-4 sat near the lower end of the capability frontier. By mid-2025, models like GPT-5 and Gemini 2.5 had reached the human PhD range on the GPQA benchmark, showcasing expert-level performance. This rapid climb in capability is giving robots far stronger abilities in perception, reasoning, and decision-making.
At the same time, the cost of using these models has collapsed. GPT-4 originally cost about $50 per million tokens, but by August 2025, GPT-5 Nano offered far greater capability at just $0.14 per million tokens — a 99.7% reduction in cost in only 29 months. In parallel, the overall capability frontier has seen +176% performance gains and over 90% cost reductions, making state-of-the-art AI accessible at scale and accelerating robotics adoption across industries.
Source: Mass Intelligence, August 2025, onessefultthing.org
This powerful combination—smarter AI at a fraction of the cost—is fueling robotics innovation at scale, making advanced perception, planning, and natural interaction more practical than ever before.
Falling Hardware Costs
As more manufacturers enter the robotics space, hardware costs are dropping steadily. Advances in materials, manufacturing techniques, and economies of scale have all played a role. According to ARK Invest, the price of industrial robots fell from about $47,000 in 2011 to $23,000 in 2023, with another 50–60% drop expected in the years ahead. As costs decline, adoption barriers fall, opening the door to wider use across industries.
Venture Capital & Corporate Investment
Capital fuels innovation. Robotics has attracted unprecedented funding, with investments topping $19 billion in 2024 (F-Prime Capital). The lion’s share has gone toward autonomous vehicles and vertical robotics (sector-specific applications such as warehouse automation, agriculture, and healthcare). As capital flows, so does momentum—helping startups scale, corporates commercialize, and researchers push boundaries.
Venture Capital Investment and Trends
As of 2025, venture capital is flowing steadily into robotics startups that blend AI with practical automation, particularly in sectors grappling with labor shortages such as logistics, healthcare, and defense. Despite broader pullbacks in the tech market, early-stage robotics has proven resilient, with investors gravitating toward capital-efficient companies solving real-world problems. VCs are especially prioritizing AI-powered robotics that leverage computer vision, reinforcement learning, and foundation models. Categories attracting the most funding include humanoids, collaborative robots (cobots), and vertical solutions such as warehouse and medical robotics. Top-tier backers—a16z, Microsoft, NVIDIA, ADIA, OpenAI, and Jeff Bezos—are signaling strong conviction in the sector’s growth potential. Two structural shifts are also shaping adoption: the rise of Robots-as-a-Service (RaaS), which lowers upfront costs for customers, and the steady decline in component prices, making robotics accessible to mid-sized businesses.| Company | Amount Raised | Round | Focus Area | Backers / Highlights |
|---|---|---|---|---|
| Figure AI | $675M | Series B (2024) | AI- powered humanoid robots | Microsoft, OpenAI, NVIDIA,Bezos; $2.6B Valuation |
| Physical Intelligence | $400M | Series B (2024) | AI “brain” platform for robotic systems | $2B+ valuation; platform-level play |
| Apptronik | $675M | Series B (2024) | Humanoid robots (“Apollo”) for logistics | Backed by B Capital, Capital Factory, Google etc. |
| Zipline | $675M | Series B (2024) | Autonomous drone delivery | Led by Temasek; $4.2B valuation |
| Shield AI | $675M | Series B (2024) | Defense-focused AI drones | $5.3B valuation; “Hivemind” autonomy platform; L3Harris, Andreessen Horowitz |
| Skydio | $230M | Series E (2023) | AI-enabled autonomous drones | $2.2B valuation; U.S. manufacturing investment; Andreessen Horowitz, NVIDIA |
| Agility Robotics | $150M | $150M | Bipedal humanoid robots for logistics | Backed by Amazon, Softbank, DCVC and Playground Global; builds "Digit" robots |
| Locus Robotics | $117M | Series F (2022) | Warehouse AMRs (Autonomous Mobile Robots) | Global warehouse deployment; Goldman Sachs, G2 Venture Partners |
| Dexterity | $95M | $95M | AI-driven robotic arms for logistics | Automating warehouse picking and loading; Lightspeed ventures |
| Outrider | $73M | Series C (2023) | Autonomous electric yard trucks | Backed by NEA, ADIA, NVIDIA |
Table 2: Notable VC Deals and Trends (2022–2025)
This shows robotics as more than a technology trend—it’s a cross-industry productivity engine. With costs falling, AI capabilities rising, and business cases proven, robotics is on track to reshape how work gets done across manufacturing floors, hospitals, farms, and even households.
Demand-Side Drivers
Labor Shortages
Source: OECD, Deloitte, FRED, Goldman Sachs Research
Robots are no longer just about efficiency — they’re about necessity. By 2030, the U.S. alone is projected to face a 2 million worker shortfall, driven by retiring baby boomers, declining birth rates, and geographic skill mismatches. As industries struggle to fill critical roles, robotics is stepping in as a workforce multiplier, filling gaps where human labor is scarce.
Government Incentives
Governments worldwide are prioritizing robotics as a pillar of economic growth and national competitiveness.
- China: A state-backed venture fund is targeting a $138 billion robotics investment by 2045 (IFR).
- United States & Europe: Policy efforts increasingly encourage automation and domestic manufacturing to secure supply chains and drive innovation.
These incentives create fertile ground for robotics startups, accelerate commercialization, and push adoption at scale.
Post-COVID Automation Push
The COVID-19 pandemic exposed vulnerabilities in global supply chains, especially around critical components. In response, many countries—particularly the U.S.—have emphasized reshoring manufacturing and investing in automation resilience. The result: robotics adoption has accelerated, not just as a cost-saving measure but as a strategic imperative for long-term stability.
In short, robotics is advancing because the technology has become cheaper, smarter, and better funded (supply side)—while at the same time market and societal pressures demand faster adoption (demand side). This convergence of forces is why robotics is no longer just a futuristic idea—it’s fast becoming an everyday reality.
The Shape of Robotics Market in 2035
The global robotics market is poised for significant expansion. We estimate it will grow from $74 billion in 2025 to approximately $373 billion by 2035, representing a compound annual growth rate (CAGR) of 17.5%. By region, Asia Pacific will lead the market, followed by North America.
Shifting Market Dynamics
A closer look at the market composition reveals important shifts:
- Software and Services on the Rise
By 2035, software and services will expand their share from 38% to 63%. This reflects the increasing importance of AI-driven control systems, cloud integration, predictive analytics, and ongoing support and maintenance—moving robotics beyond hardware into higher value-added capabilities.
- Service Robots Gain Ground, but Industrial Applications Dominate
The share of service robots is projected to grow from 30% in 2025 to 40% by 2035. That said, industrial robots remain the backbone of the robotics market. They dominate today—and will continue to hold the larger share in 2035—thanks to their proven track record in manufacturing and warehousing, where efficiency, productivity, waste reduction, and quality improvements are clear and measurable.
Robotics Across Key Verticals
The adoption of robotics is being driven by tangible efficiency gains and measurable cost savings across multiple verticals. Below are some of the most impactful sectors:
| Vertical | Key Use Cases | Efficiency / Savings Impact |
|---|---|---|
| Manufacturing  | Assembly line automation, welding, painting, material handling | 30% reduction in production costs; 16% productivity increase |
| Warehousing and Logistics  | Order picking, packing, sorting, palletizing, autonomous transport | Reduces labor costs by 20–40%; improves order accuracy to 99.9% |
| Healthcare  | Surgery assistance, patient care robots, hospital logistics, disinfection | Robotic surgery reduces complication rates by 21%; cuts hospital stays by 20% |
| Agriculture  | Precision farming, crop monitoring, planting, harvesting | Reduces pesticide use by 90%; improves yield by 15% |
| Public Safety and Defense  | Bomb disposal, surveillance drones, search and rescue | Cuts mission time by 30%; reduces risk to human personnel |
| Customer Service  | Reception robots, interactive kiosks, call centre automation | Reduces wait time by 40%; increases customer satisfaction scores by 15% |
| Inspection  | Industrial site inspection, infrastructure maintenance, hazardous area monitoring | Cuts inspection costs by 25–40%; reduces downtime by 15% |
| Education and Research  | Remote teaching assistants, lab automation, interactive learning | Frees up to 20% of teacher time; increases lab productivity by 25% |
| Home and Personal Use  | Cleaning robots, lawn mowing, personal assistants, elder care | Up to 40% of mundane chores could be automated within 10 years |
Table 3: Robotics Use-cases & Efficiencies by Industry Vertical
What Robots Need to Think, Move, and Connect
The robotics market represents not only a wave of technological innovation but also a strategic opportunity for telecom providers. As robots become more widespread across industries, they will increasingly depend on high-performance networks, distributed computing, and integrated services—areas where telecom operators are uniquely positioned to add value.
In practice, this means telecom players can drive new revenue streams (e.g., connectivity services, robotics platforms, AI-enabled solutions) while also expanding existing ones (e.g., cloud, edge computing, private 5G, IoT). However, to fully capture this opportunity, providers must dive deeper into the robotics business model and understand the compute and network requirements of different robot types.
These requirements are not one-size-fits-all—they vary dramatically based on design, function, and environment. Below are the key dimensions that shape compute and connectivity needs:
Factors Shaping Compute and Network Requirements
Latency Sensitivity
Some robots, like autonomous drones or surgical robots, require decisions in milliseconds to ensure safety and performance. Others, like warehouse inventory bots, can tolerate higher latency. Telecom operators must map workloads to the right infrastructure (on-device, edge, or cloud) to meet these demands.
Mobility
A stationary robot in a factory has predictable connectivity needs. By contrast, a mobile robot navigating a hospital or a drone operating outdoors requires seamless handoffs and robust coverage. Mobility shapes whether 5G, Wi-Fi, Satellite, or hybrid solutions are best.
Data Gravity
Robots generate vastly different amounts of data. Autonomous vehicles, for instance, stream terabytes of sensor data (video, LiDAR, radar), while simple service robots may only send telemetry. The heavier the data, the closer computation must be to the source—favoring edge computing solutions.
Connectivity Quality
Mission-critical robots require ultra-reliable connectivity, while consumer cleaning robots can tolerate intermittent links. Telecom providers can differentiate by offering SLAs around uptime, jitter, and throughput.
Privacy and Security
In sensitive environments like healthcare or defense, data may need to stay on-premises or on-device, while less critical use cases can leverage cloud processing. Telecom operators will need flexible architectures that balance regulatory, ethical, and customer requirements.
Safety and Reliability
Industrial robots in manufacturing or defense cannot fail without risking human lives or costly downtime. These scenarios call for redundant connectivity, failover systems, and edge intelligence to ensure continuity.
Scalability
Some applications involve a single high-value robot, while others require coordinated fleets of hundreds or thousands (e.g., AMRs in warehouses). The latter puts enormous pressure on orchestration platforms, bandwidth, and real-time coordination—all areas where telecom providers can add significant value.
Economics
Ultimately, deployment decisions hinge on cost. A successful model must balance infrastructure investments (private 5G, edge data centers, orchestration platforms) with operational savings that robots deliver. Telecom providers must demonstrate clear ROI.
Device Capabilities
Not all robots can host heavy computation locally. Smaller form factors (e.g., delivery drones, consumer robots) depend on network offloading to edge or cloud. Larger industrial machines may handle more processing onboard. This creates segmentation in telecom service opportunities.
The Bigger Picture: Robotics as the Next Platform Shift
For telecom companies, robotics is more than another connectivity use case—it represents a multi-layered platform opportunity. Networks, edge computing, and AI integration will form the backbone of tomorrow’s robotic ecosystems. Providers can position themselves as enablers of intelligent automation, delivering more than bandwidth:
Edge computing and private 5G/6G networks customized for industrial and mission-critical robots.
Cloud platforms and APIs that integrate AI models into robotic workflows.
Fleet management and orchestration services for scaling from dozens to thousands of autonomous machines.
Security, privacy, and compliance frameworks tailored to sensitive industries such as healthcare and defense.
Yet the implications go far beyond telecom. As intelligent robots expand from factory floors into logistics, healthcare, retail, agriculture, and even homes, the impact will rival past disruptions like the gig economy. Platforms such as Uber and Airbnb dismantled entrenched business models, displaced incumbents, and forced industries to reinvent themselves—while at the same time creating trillion-dollar platforms, new categories of services, and entirely new forms of work.
Robotics will follow a similar trajectory. Yes, some traditional jobs will be automated —particularly repetitive, high-risk, or low-skill tasks. But the larger story is the emergence of new business models and service layers:
Robotics-as-a-Service (RaaS), lowering barriers to adoption.
AI-driven supply chain orchestration, optimizing flows across industries.
Human–robot collaboration roles, blending human judgment with machine precision.
Integration and platform ecosystems—hardware, software, and services—that have yet to be fully imagined.
The robotics market is still in its formative stages, but its trajectory is unmistakable: from $74B in 2025 to $373B in 2035. The winners will not be those who wait, but those who experiment, invest, and build partnerships now.
For business leaders across telecom and beyond, the imperative is no longer if robotics will matter, but how fast and where. The organizations that act today will not just adapt to disruption—they will define the next trillion-dollar platforms of the intelligent machine age.
Authors:
Sangit Rawlley – Senior Partner and AI Practice Lead
Dhruv Mehendale – Intern
About JLA
JLA Advisors (www.jlaadvisors.io), is a boutique consultancy helping organizations navigate the complex and fast-moving world of AI. From AI strategy to automation, JLA’s AI practice specializes in turning AI disruption into competitive advantage.
If your business is wrestling with the same questions leaders across industries face— Which robotics use cases are viable today? How do we balance cloud, edge, and on-device compute? Where will robotics deliver the greatest ROI?—JLA can help you find answers and design a path forward.
📅 Let’s Connect
Schedule a call with Sangit Rawlley, our Senior Partner and AI Practice Lead, to explore how AI and robotics can drive meaningful, measurable impact in your organization.
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