Robots have long captured the public imagination, from science fiction fantasies to viral humanoid demos. But the real shift is happening far from the spotlight: in factories, fields, warehouses, and hospitals, where automation is delivering tangible, defensible ROI.

At b2venture, we’ve spent the last months diving into robotics. We’ve spoken with domain experts and founders, explored the evolution of the robotics stack, and mapped out where we believe the category is going next. One thing is clear: robotics is no longer a niche curiosity or distant vision. It is rapidly becoming a strategic lever in vertical industries, especially where labor is expensive, scarce, or dangerous.

This blog post outlines our current view of the market, the changes taking place, and the factors that distinguish a sustainable robotics company from a short-lived one.

Market Pulse: Robotics in 2025

The foundation is falling into place, technically and economically

• Hardware is no longer the barrier: The average cost of industrial robots has dropped from USD 47,000 to about USD 22,000 in the past decade and is predicted to be further halved in the next years. Other core technologies like LiDAR and servo motors have seen similar cost collapses due to economies of scale, manufacturing advances, and open-source designs. Founders benefit from what is referred to as “off-the-shelf components”, which are standardized, widely available parts like motors or sensors. These components can be integrated without custom engineering, which speeds up development and allows teams to focus on software.
  
  
• The robotics stack is unbundling: ROS2 supported by PX4, Ardupilot or similar solutions are becoming the Linux of robotics. Founders can now build vertical applications on shared middleware, autonomy APIs, and simulation environments, instead of reinventing the entire stack.
  
  
• AI is making robots more useful, faster: Foundation models like Covariant’s RFM and NVIDIA’s GR00T are powering perception and task execution with fewer demos and more generalization. On the other hand, Reinforcement Learning is proving essential for robotics tasks that involve high variability and can’t be solved with hard-coded rules  (e.g., Skydio’s drones or Boston Dynamics’ warehouse robots). By learning through trial and error, RL enables systems to handle edge cases, sensor noise, and dynamic conditions that traditional control methods struggle to manage.

How the market is responding to robotics

Verticalized use cases are scaling first

Rather than building general-purpose platforms that can theoretically do everything, many successful robotics companies are focusing on specific, high-ROI use cases. From bricklaying to warehouse picking to autonomous tractors, these solutions are designed for specific tasks within defined environments, which drastically lowers deployment friction and speeds up time-to-value. What they sacrifice in flexibility, they gain in adoption and capital efficiency. Robots like those from Carbon Robotics or Dexory are great examples: they do one job extremely well, integrate into existing workflows, and deliver measurable impact from day one.

The market will scale through coordination, not complexity

While robotics adoption today is being driven by specialized, high-ROI use cases, the next wave of market expansion won’t be shaped by increasingly complex sensors or humanoid prototypes, but rather by systems that can coordinate intelligently. The global robotics market is unlikely to scale through isolated point solutions. Instead, growth will come from interoperability, such as fleets of robots that share perception, align tasks, and operate collectively as distributed systems. Just as cloud infrastructure scaled through orchestration layers rather than chip-level advances, robotics will follow a similar path through shared autonomy, fleet-wide learning, and collaborative intelligence. Companies that begin with targeted deployments for strategic partners and gradually evolve into connected, multi-agent systems will be best positioned to capture this shift.

The robotics stack is unbundling

Mature middleware and rising application platforms have made it possible for startups to focus on distinct layers of the robotics stack. Instead of rebuilding the entire system from scratch, founders can now specialize in areas like planning (e.g. mission-level orchestration), perception (e.g. sensor fusion), or simulation. This creates new opportunities to build “picks and shovels” for the robotics ecosystem, much like how AWS created services for compute, storage, and networking. Tools for fleet orchestration, real-time remote operation, or sim2real transfer are emerging as valuable standalone platforms.

AI is accelerating robotics development

Pretrained multimodal models such as NVIDIA’s GR00T and Covariant’s RFM are increasingly compressing the time it takes to teach robots new behaviors. Instead of laborious task-specific programming, robots can now generalize across environments, adapt with fewer demonstrations, and even follow natural language instructions. This shift is unlocking applications in dynamic and semi-structured environments like warehouses, farms, or urban settings, where conventional rule-based systems struggle. In short: foundation models are moving robotics from hard-coded automation to adaptive intelligence.

Geopolitics is shaping the robotics supply chain

While innovation in software and autonomy is accelerating, the hardware backbone of robotics is still heavily reliant on China. From actuators to sensors to full robot assembly, China dominates both the volume and sophistication of global robotics manufacturing. The country is arguably far ahead in building the infrastructure for a robotics-driven labor economy (Source: SemiAnalysis). This creates growing strategic pressure on other regions to diversify,  not just to reduce risk, but to ensure long-term independence and resilience. For investors and founders, this opens up opportunities in localized manufacturing, dual-sourcing of critical components, and the development of parallel supply chains outside China.

The Robotics Stack

The autonomy stack can be understood as a bidirectional flow: raw sensor data moves upward through perception, mapping, and planning layers, while high-level commands flow downward into control and actuation. The visual reflects this architecture, from hardware at the base to application logic at the top, and helps clarify where different startups sit within the stack.

It seems like this stack is becoming increasingly modular, as companies specialize in specific layers (e.g., planning, sensor fusion, or task execution) rather than building full-stack solutions. This partly reflects the unbundling of cloud infrastructure and will eventually create space for specialized, infrastructure-focused approaches in robotics.

However, it’s important to note that perfect segmentation isn’t possible. Many companies span multiple layers, especially as they mature. A company offering perception today might move into planning tomorrow, or bundle hardware and software to reduce integration friction. That fluidity is a feature, not a flaw, and a key dynamic to track in this evolving ecosystem.

The Emerging Frontier: What Makes a Defensible Robotics Company?

A few concrete signals set apart truly durable robotics startups from those built around short-term novelty:

Signal 1: Deep integration into industry-specific workflows

Robots are no longer standalone tools. They’re the upcoming interfaces into complex operational environments. That means they must eventually interface with ERP systems, operate alongside humans, and navigate both structured and chaotic real-world scenarios.

A crop-weeding robot must integrate with planting layouts and weather models. A construction layout robot must sync with BIM files and site progress tracking. A surgical robot must interact with hospital EMR systems.

This deep workflow integration not only drives stickiness, but also builds in defensibility: switching costs rise, data advantage compounds, and value becomes easier to quantify.

Signal 2: Prove ROI with a trusted wedge

Robotics adoption rarely starts with mission-critical workflows. It typically begins in repetitive, lower-risk environments, where outcomes are measurable and payback periods are short.

Bear Flag Robotics, which was acquired by John Deere, focused on autonomous tilling before expanding. Dusty Robotics starts with printing layout plans directly onto the floors of job sites, before eventually taking over further tasks on the construction site.

Companies that find a high-frequency, low-trust-entry task, the trusted wedge, can establish credibility and build trust within large enterprises. From there, expansion into more critical use cases becomes both possible and profitable.

Signal 3: Out-of-the-Box functionality wins early

Robotics buyers, particularly in sectors like logistics, agriculture, or SMB manufacturing, aren’t hiring robotics engineers. They need solutions that just work. The difference between a sticky first deployment and a failed pilot often comes down to how quickly a system delivers visible value with minimal friction. Think of it less like selling software and more like hiring a contractor: customers want reliable, plug-and-play performance upfront, not a six-month co-development journey, with the option to customize later if value is proven.

This is why we prioritize startups that anchor their go-to-market around turnkey deployments. Pre-integrated workflows, hardware-software bundles, and clearly defined onboarding playbooks. Companies like Locus Robotics and Starship Technologies succeeded early by delivering self-contained systems that solved a pain point immediately, and only then layered in complexity or platform extensibility.

Of course, building this playbook takes iteration. Field testing is essential to define the “minimal repeatable deployment” and uncover the friction points that need abstraction. But the mindset matters: design for instant value, not infinite configurability. Let the platform emerge from proven use cases, not the other way around.

What comes next

The robotics landscape is no longer waiting for its breakthrough moment, it’s quietly scaling in the background. The hype cycles may still orbit humanoids and sci-fi demos, but the real momentum is with robots that do one thing well, can eventually plug seamlessly into existing workflows, and deliver hard ROI without heroics. That's where we see budgets being allocated in the market.

For founders, the opportunity is twofold: either build robots that earn trust through utility or build the tooling that lets others scale more safely, faster, and with less friction. Vertical depth is more valuable than horizontal ambition right now. The best companies we meet don’t just sell automation, they sell reliability, integration, and repeatable business outcomes.

As the stack continues to unbundle, and foundation models reduce the friction of autonomy, the next generation of robotics companies won’t win on novelty. They’ll win on delivery. And the winners will look less like science experiments and more like infrastructure.

If you’re building a robotics company grounded in real-world impact, we’d love to hear from you.

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