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What We Learnt From Robotics Experts - Dusty and Bedrock
Owen Drury
September 17, 2025 • Estimated Reading Time: 14 minutes
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What We Learnt From Robotics Experts - Dusty and Bedrock
Global robotics secured $6 billion in the first seven months of 2025, putting it on track to surpass last year's total. Yet adoption rates are actually dropping.
Recent conversations with Tessa Lau from Dusty Robotics and Kevin Peterson from Bedrock Robotics revealed why most companies fail to bridge the pilot-to-production gap.
Both executives lead companies that have cracked the adoption code. Dusty, recognized as the most implemented and highest-rated construction robotics solution in recent BuiltWorlds research, has already been deployed across 230 million sqft (21 million square meters) of construction sites. Bedrock, which emerged from stealth with $80 million in funding, is developing self-driving retrofit kits for existing construction equipment with ex-Waymo leadership.
The answer to adoption challenges isn't about better technology; it's about smarter business strategy.
Dusty Robotics’ FieldPrinter at work
TL;DR:
Robotics funding is booming ($6B in 2025 YTD), but adoption lags. Conversations with Dusty and Bedrock reveal why winners succeed:
Budget gap: Robots must deliver 10x better outcomes to justify new budgets, not fight for existing ones.
Usability: Power-tool simplicity beats PhD-level complexity.
Hidden strategy: Over-spec sensors today → recurring software revenue tomorrow.
Retrofit focus: Faster adoption comes from working with existing equipment.
Construction edge: Chaotic job sites are the perfect training grounds, accelerating tech maturity.
Tech convergence: ML, LLMs, and sensor fusion now make superhuman accuracy viable.
📌 For AEC: focus on labor-heavy problems with no budget line, design for retrofit, and build orchestration platforms, not just task automation.
The Budget Problem That Kills Robotics Companies
Valuable construction problems don't ALWAYS have line items.
Layout automation saves thousands of hours per project but appears nowhere on budget spreadsheets. When contractors see a $50,000 solution for a "free" process, they pass.
The companies winning contracts flip this dynamic completely.
Instead of incremental improvements, they target 10x better solutions that force new budget creation. Layout hasn't changed in 5,000 years. A robot delivering 10x speed, 10x accuracy, and unlimited information density doesn't compete for existing dollars.
It creates new ones.
Credit: Bedrock Robotics
The democratization factor matters equally. If your robot needs a PhD to operate, you've built a consulting business. The winners design robotics like power tools with iPhone-level usability.
This directly addresses construction's core challenge: only 11% of field workers have the information they need to do their jobs effectively.
The Hidden Revenue Strategy: Over-Spec Your Sensors
Most hardware companies obsess over cost optimization. The smartest robotics companies deliberately over-spec sensors, even when it seems wasteful.
This is not a matter of engineering indulgence. It involves revenue planning.
Embed unused sensors worth thousands per unit, and you create the foundation for future software applications without hardware recalls. Your installed base becomes a recurring revenue platform through software updates alone.
The build versus buy timing matters too. Top companies often start by prototyping with readily available components and then move on to custom hardware when they hit around 60 units. This gives us the right manufacturing know-how to train our contract partners well, all while steering clear of jumping into optimization too soon.
The retrofit versus new-build decision also shapes success. Companies targeting retrofit applications that work with existing drive-by-wire equipment can deploy faster than those requiring complete infrastructure replacement.
With 439,000 construction workers needed in 2025 alone, creating urgent automation demand, companies mastering sensor fusion achieve superhuman performance that justifies premium pricing.
Dusty Robotics printing something unusual at AU 2025
Why Construction Sites Are Perfect Training Grounds
Every construction site changes every 48 hours. Materials move, workers shift, and priorities evolve.
Most robotics companies see these modifications as a problem. The winners see it as their competitive advantage.
Construction sites contain every real-world scenario robots encounter elsewhere, compressed into a more challenging environment. Companies succeeding here can adapt their technology anywhere.
The key insight: embrace chaos as a feature. Design systems that learn from constantly changing conditions rather than fighting them. The most advanced platforms now use imitation learning to adapt behaviors based on human decision-making across thousands of similar scenarios.
Companies succeeding here solve problems that exist across multiple industries. If you can navigate plastic sheets moving in the wind, water bottles scattered across sites, and buried utilities with millimeter precision, you've mastered challenges that appear everywhere.
The companies bridging the pilot-to-production gap position themselves as intelligent orchestration platforms coordinating people, materials, and machines rather than just automating tasks. Industry research shows this growing sophistication: companies are moving from pilot programs to repeated implementation across multiple projects.
The Technology Convergence Moment
Three advances converged in the past 24 months to make construction robotics finally viable:
Machine learning techniques allow robots to mimic human expertise without hand-coding every scenario. Large language models enable natural language interfaces for non-technical workers. Sensor fusion reached the price-performance threshold where superhuman accuracy becomes cost-effective.
This timing matters because construction's constraints haven't changed. Projects still demand millimeter precision for prefabricated components. Sites still present unstructured environments with buried utilities and safety hazards.
The companies capitalizing on this moment share three characteristics: they solve problems consuming significant labor hours, they design for retrofit applications with existing equipment, and they target industries with acute labor shortages.
For robotics funding that reached record levels, this combination of workforce urgency and technological maturity creates unprecedented opportunity.
What This Means for AEC
Three patterns emerge from successful deployments:
Target problems that consume significant labor hours but lack dedicated budgets.
Design solutions requiring 10x improvement to justify adoption.
Build platforms that orchestrate multiple stakeholders rather than just automate individual tasks.
The bottom line: Companies mastering these principles position themselves as essential infrastructure for an industry undergoing its biggest transformation in decades.
Watch the episode with Tessa and Kevin here👇👇👇
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