The space industry is entering a new phase of growth.

Novaspace’s 2026 Space Economy Report says the global space economy is positioned to grow from $626.4 billion in 2025 to $1.01 trillion by 2034, while the core space market is expected to expand from $236 billion to $323 billion over the same period. The distinction is important because much of the sector’s value is increasingly tied to space-enabled services, including positioning, navigation and timing, satellite-enabled connectivity and downstream applications.

At the same time, the World Economic Forum’s 2025 analysis of transformative space technologies points to advances in satellite monitoring, materials science, space-based solar power, mega-constellations, in-orbit servicing and propulsion systems.

This growth is creating new opportunities for commercial space companies, space agencies, aerospace and defense OEMs and the supplier ecosystems that support them. It is also placing greater pressure on how space programs are engineered, integrated, tested and sustained.

Those shared challenges include complex product architectures, long lifecycle requirements, multi-tier supplier networks, software-defined systems, cybersecurity demands and the need to collaborate across engineering, manufacturing, operations and sustainment. Space organizations know them well.

The difference is the operating environment.

Space systems must be engineered for conditions that leave little margin for error. NASA’s Glenn Research Center highlights space environment testing across atomic oxygen testing, near-ultraviolet radiation, low-temperature soak and thermal cycling, while NASA’s Space Environments Complex simulates high vacuum, cold environments and solar and thermal radiation.

In space, the cost of engineering failure is higher. A defect that might be manageable in another environment can affect mission performance once a system is in orbit.

That is why space organizations need faster development cycles built on stronger digital foundations.

From document-led engineering to model-led execution

Space programs are systems-of-systems by nature. Satellites, launch vehicles, payloads, ground systems, communication networks, autonomy software and mission operations must work together across a complex lifecycle.

Traditional document-led engineering can make that coordination harder. Requirements, design decisions, simulation outputs, supplier inputs and test evidence often sit in disconnected tools and formats. As complexity increases, those gaps can slow development, increase rework and make it harder to maintain a clear view of risk.

Model-based systems engineering (MBSE) provides a more connected approach. By representing requirements, architectures, interfaces, behaviors and verification evidence in digital models, engineering teams can create a more consistent source of truth across the lifecycle.

NASA’s 2025 MBSE material points to the growing role of AI-assisted modeling, digital twins for real-time system monitoring and advanced simulations for systems-of-systems engineering. For space programs, those capabilities are especially valuable because they allow teams to test design decisions earlier, simulate system behavior more comprehensively and improve confidence before physical integration begins.

Why digital twins matter in space

Digital twins can extend this model-led approach beyond design and into operations.

For space programs, a digital twin can help teams understand how a system is expected to perform, how it is performing and how changes in environment, mission profile or component behavior may affect outcomes. This matters most once a system is in orbit, where there is no physical access and every operational decision depends on remote telemetry, simulation and predictive insight.

A digital twin can support engineering validation, mission planning, anomaly investigation, performance optimization and sustainment. It can also help connect engineering and operations more directly, so lessons from mission performance feed back into future designs.

The value comes from connecting the digital twin to the wider engineering thread: requirements, product lifecycle management, software delivery, test data, configuration management and operational telemetry.

PLM as the enterprise backbone

Product lifecycle management (PLM) is central to this shift.

In space, engineering data must remain traceable across design, manufacturing, supplier collaboration, certification, launch, operations and sustainment. As space systems become more software-defined and more modular, organizations need a stronger way to manage configurations, parts, requirements, changes, risks and compliance evidence.

A modern PLM foundation creates that continuity. It gives engineering, manufacturing and sustainment teams a shared view of the product, while supporting the traceability needed for high-risk, high-complexity programs.

For aerospace and defense OEMs and suppliers moving into space, PLM also helps connect enterprise scale with program-specific execution. Common processes can be standardized across programs, while mission-specific requirements remain controlled at the business layer.

Cloud engineering and DevSecOps for mission speed

Space innovation is also becoming more software-driven.

Mission systems increasingly depend on software, AI, autonomy, data processing and secure connectivity. That changes how organizations need to build, test and deploy capability. Cloud engineering and DevSecOps can help teams improve collaboration, automate testing, embed security earlier and support faster iteration without losing control.

This is especially important as space programs move toward more rapid development cycles. The goal is to reduce avoidable friction while maintaining the discipline required for mission-critical systems.

Security also needs to be built into the engineering lifecycle. Space systems are increasingly connected, data-rich and strategically important, making cyber resilience a core requirement across software, infrastructure and supply chains.

Building the digital space enterprise

The digital space enterprise brings these capabilities together.

• MBSE helps teams define and understand complex systems
• Digital twins help simulate, monitor and optimize them
• PLM provides lifecycle continuity and traceability
• Cloud engineering enables scalable collaboration and data access
• DevSecOps brings security and automation into software delivery

Together, these capabilities create a digital foundation that can help space organizations reduce rework, accelerate decision-making and manage risk across the lifecycle.

For aerospace and defense companies with space divisions and for suppliers supporting commercial, civil and defense space programs, this foundation will become increasingly important.

The next era of space competition will be shaped by how quickly organizations can engineer complex systems, prove they will work in extreme environments and adapt as missions, technologies and threats evolve.

Space has always tested the limits of engineering. The organizations that lead the next era will be the ones that engineer the enterprise as carefully as the spacecraft.