- Software architecture and integration have overtaken hardware as the main bottleneck in robotics development as systems become more AI-driven
- Developers face a gap between needs and tools with most relying on general-purpose operating systems despite demands for real-time, safety-critical performance
- Strong expectations for physical AI coexist with low confidence in readiness as teams navigate rising complexity, security requirements, and regulatory delays
- BlackBerry stock (TSX:BB) opened trading at $11.86
A new global study released by QNX, a division of BlackBerry (TSX:BB), suggests that software—not hardware—is now the principal constraint on robotics innovation, as advances in physical AI accelerate development across industries. The findings, detailed in the Inside the Robot: Architecture Benchmark Report, are based on a survey of 1,000 robotics developers worldwide and provide insight into shifting priorities in system design, performance, and deployment.
Software overtakes hardware as key constraint
According to the report, 27 per cent of developers identified software architecture and integration as the leading performance bottleneck in robotics systems, compared with just 16 per cent who attributed constraints primarily to hardware. The data signals a notable transition in the industry, where improvements in processing power, sensors, and mechanical systems have outpaced the development of robust software frameworks capable of supporting increasingly complex applications.
This article is a journalistic opinion piece that has been written based on independent research. It is intended to inform investors and should not be taken as a recommendation or financial advice.
As robots move beyond controlled environments into dynamic human settings—such as factory floors, healthcare facilities, and urban areas—the demands on software have intensified. Developers cited the need for predictable, secure, and scalable systems capable of handling mixed-criticality workloads, including real-time operations and AI-driven decision-making.
Strong investment expected in software capabilities
The shift toward software-centric development is expected to continue. Approximately 85 per cent of respondents indicated that software will play a growing role over the next three to five years. Planned areas of investment include AI-driven decision systems and cybersecurity (both cited by 51 per cent of respondents), followed by operating systems and real-time control software (37 per cent).
These findings suggest that organizations are increasingly viewing software infrastructure as a strategic asset, particularly as robotics systems become more interconnected and distributed across edge and cloud environments.
Rising deployment alongside humans raises stakes
The study highlights the expanding presence of robots in human environments. Currently, 83 per cent of developers report that their systems are already deployed alongside people. Among those not yet deployed in such contexts, 67 per cent expect to reach that stage within the next three to five years.
This trend is driving higher expectations for system reliability, safety, and predictability. Nearly all respondents (95 per cent) emphasized the importance of deterministic, real-time behavior, especially in applications where robots must operate safely alongside humans or respond to rapidly changing conditions.
Gap between requirements and current practices
Despite the near-universal need for real-time and safety-critical performance, the report identifies a significant gap between requirements and implementation. A majority of developers (91 per cent) reported using general-purpose operating systems (GPOS) for workloads that include real-time or safety-critical functions.
GPOS platforms, while flexible and widely adopted, are not typically designed to deliver deterministic performance or meet stringent safety certification standards. This mismatch appears to be increasingly recognized by developers, with 86 per cent of those using GPOS stating that they are open to switching to alternative operating systems better suited to their needs.
The findings underscore an industry-wide tension between the flexibility and familiarity of general-purpose platforms and the growing need for specialized, safety-certified systems that can guarantee predictable behavior.
Certification and compliance pose additional challenges
Regulatory and compliance requirements are further complicating robotics development. Two-thirds (66 per cent) of respondents reported project delays related to certification processes, with higher figures—around 70 per cent—reported in markets such as the United Kingdom and Germany. In contrast, 56 per cent of respondents in China indicated similar delays, reflecting differences in regulatory environments.
The most challenging areas of compliance were cybersecurity standards, such as ISO/SAE 21434 (cited by 51 per cent of respondents), and functional safety standards like ISO 10218 (49 per cent). These requirements are contributing to increased development costs and extended timelines, particularly as robots become integrated into safety-critical applications.
High expectations for physical AI, but confidence varies
The report also highlights strong confidence in the long-term impact of physical AI—robot systems capable of perceiving, reasoning, and acting autonomously in real-world environments. Nearly nine in ten respondents (89 per cent) stated that physical AI will be critical to their organization’s future strategy within the next three to five years.
However, the study reveals uneven readiness across the industry. Only 29 per cent of respondents said they feel “very confident” in their ability to build systems capable of making safe and predictable decisions in complex, real-world scenarios. This gap between ambition and capability suggests that while interest in physical AI is widespread, significant work remains to address foundational challenges.
Leadership insights
“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,” Jim Hirsch, Global VP of Sales, General Embedded Markets at QNX said in a media release. “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.”
Industry implications
The findings point to a broader transformation within robotics, where software infrastructure is becoming central to innovation. As systems grow more complex, the ability to manage real-time performance, ensure safety, and meet regulatory requirements will likely define competitive advantage.
QNX, which provides embedded and real-time operating systems used in sectors such as automotive, healthcare, and industrial automation, positions its offerings as addressing these emerging needs. The company notes that its software is currently deployed in critical systems across multiple industries, including by a majority of leading medical device manufacturers.
Methodology
The research was conducted online by market research firm OnePoll between February 25 and March 4, 2026. The survey included 1,000 software developers and engineers working in robotics across selected sectors worldwide. Participants were recruited through double opt-in panels and compensated based on survey complexity, with methodology aligned to Market Research Society standards.
Overall, the report suggests that as robotics continues to evolve, overcoming software-related challenges—particularly in system architecture, real-time performance, and regulatory compliance—will be essential to unlocking the full potential of physical AI.
About BlackBerry
BlackBerry Ltd. offers intelligent security software and services to enterprises and governments worldwide. The company leverages AI and machine learning to deliver cybersecurity, safety and data privacy solutions.
BlackBerry stock (TSX:BB) opened trading at C$11.86 and has risen 116 per cent since this time last year.
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