QNX, a division of BlackBerry, has released a new research study, the Inside the Robot: Architecture Benchmark Report, examining how robotics development is changing as systems become more software‑driven, AI‑enabled, and increasingly deployed alongside humans at work and in daily life.
Based on a survey of 1,000 developers from around the world, the research reveals the most significant inhibitors to progress, the gap between system ambitions and current capabilities, and developers’ views on the industry’s future.
A new episode of QNX’s Code the Future podcast featuring Omdia chief analyst Lian Jye Su explores the themes and results in more detail.
Hardware advances are no longer the bottleneck
With almost one in three developers (27 percent), naming software architecture and integration as their biggest performance bottleneck, compared with just 16 percent who point to hardware, the research shows that future progress hinges less on new hardware and more on building systems that are predictable, secure, and capable of handling mixed levels of criticality.
As robots move more widely from controlled environments into dynamic, real‑world settings such as city streets and factory floors, developers are recognizing that software foundations are the deciding factor as to whether innovations succeed or stall.
Looking ahead, 85 percent of developers also expect software to play an even greater role in robotics over the next three to five years with teams anticipating their biggest investments will be in AI-driven decision making and cybersecurity (both at 51 percent), followed by operating systems and real-time control software (37 percent), further reflecting how software foundations are becoming strategic assets as robotics systems grow more complex, interconnected, and distributed.
Increasing deployment in human environments drives higher demands
Robotics teams are already feeling the impact. More than four in five respondents (83 percent) say their systems are now deployed alongside humans. Among those not yet deployed alongside humans today, two‑thirds (67 percent) expect they will be within three to five years.
This expanding presence in less controlled environments, from surgical suites to busy shop floors is driving higher expectations around reliability, safety, and predictable behavior, with nearly all respondents (95 percent) saying deterministic, real‑time execution is important to the systems they develop.
Surprisingly, despite this near‑universal requirement, most development teams continue to rely on software not designed for real‑time or safety‑critical use with the research revealing that 91 percent of respondents run these workloads, at least in part, on general‑purpose operating systems (GPOS), even though safety‑certified commercial solutions are rated as the best fit for their needs.
As a result, 86 percent of these GPOS users say they are open to changing their OS; a contrast that encapsulates the growing tension between flexibility and the need for predictable, guaranteed behaviour as robotics deployments scale.
Certification delays and security demands add new pressures
Regulatory and compliance demands further intensify these challenges. Two‑thirds of respondents (66 percent) report project delays due to certification processes, rising to around 70 percent in the UK and Germany. In contrast, only 56 percent report delays in China, where regulatory requirements are far less stringent.
These delays directly affect development costs, delivery timelines, and commercial risk. Cybersecurity (ie: ISO/SAE 21434) and functional safety standards (ie: ISO 10218) are among the most challenging areas to comply with, cited by 51 percent and 49 percent of respondents respectively.
High ambition meets uneven readiness for physical AI
Despite these pressures, ambition and optimism across the industry remain high. Physical AI is firmly on the roadmap, with 89 percent of respondents saying AI‑enabled robots that can perceive, reason, and act autonomously in the physical world will be critical to their organisation’s strategy over the next three to five years, with China leading the pack globally.
Confidence in the long‑term potential of Physical AI is strong, but readiness remains uneven. Only 29 percent of respondents feel “very confident” in their ability to make safe, predictable decisions in real‑world environments.
Jim Hirsch, global VP of sales, general embedded markets at QNX, says: “Robotics teams are clearly pushing toward more intelligent, autonomous systems, but the data shows they are also running up against the very real limits of architectures that were never designed for this level of complexity or accountability.
“Developers consistently cite four core challenges: integration complexity, certification delays, functional safety risks in human‑machine interaction, and ensuring predictable behavior when it matters most.
“The good news is that these are all solvable problems and by focusing on stronger software foundations, developers can set the stage for faster innovation and a new generation of safe, reliable, and highly autonomous robots.”
QNX provides high-performance foundational software that helps simplify the most complex challenges in industries such as robotics, automotive, medical devices, industrial controls, commercial vehicles, rail, and aerospace and defense.
QNX empowers organizations to unlock new possibilities in areas like high-performance computing at the edge, standards-based virtualization technologies, and cloud enablement.
Trusted in the world’s most critical systems, QNX continues to lead across a range of sectors, including robotics and healthcare, where its technology is deployed by nine of the top 10 medical device manufacturers.
