MAKE DEFENSE INTEGRATED

In February 2026, KPMG Middle East was honored to fulfil the responsibility as knowledge partner for the World Defense Show (WDS26) in Riyadh, Saudi Arabia. This strategically important event brought together defense industry, academia, innovators, end users and decision makers to discuss and showcase the latest developments in technology, supply chains and workforce capability.

As official knowledge partner, KPMG played a central role by creating thought-leading publications and and facilitating over 25 panels and keynote addresses with more than 100 panelists and speakers. We thereby demonstrating our commitment, knowledge and experience in supporting Defense and Security clients as they face unprecedented ambiguity and challenges in the region and around the globe.

The analysis contained in this publication is the result of gathering the thoughts and insights from those who attended WDS26, from active panelist to influential keynote speaker or industry commentator. The aim of this report is to serve as a credible waypoint in pursuing the ambition of a regional defense eco-system that is resilient, innovative and agile.

The 2026 edition World Defense Show solidified the Kingdom’s positioning as an integral node in the global defense ecosystem – a convening regional and international power capable of shaping procurement policy and doctrine, building industrial partnerships, and facilitating technology-transfer. The observations emitted from Riyadh in February 2026 were unmistakable: defense integration across military, government, industry, and technology players is an operational imperative.

Chris Moore

Head of Defense and Security

KPMG Middle East

AI, autonomy, and data-centric warfare

AI, autonomy, and data-centric architectures are rapidly transforming the character of modern warfare. Military advantage is increasingly determined not only by platform capability but by the ability to collect, process, and act upon vast volumes of data in real time. Advances in machine learning, autonomous systems, and distributed computing are enabling new operational concepts that promise greater speed, precision, and adaptability on the battlefield.

WDS26 demonstrated that many of these technologies are now transitioning from experimental pilots to early operational deployment. Capabilities such as AI-enabled intelligence fusion, automated logistics optimization, and machine-assisted planning are beginning to influence force design and operational planning. However, the path from prototype to scalable battlefield integration remains uneven, with critical gaps in infrastructure, doctrine, and system readiness.

The primary constraint is not the sophistication of AI models themselves, but the enabling architecture required to operationalize them. Sovereign data pipelines, resilient communications networks, trusted AI assurance frameworks, and effective human–machine teaming doctrine are essential to translating technological potential into reliable operational capability.

This chapter examines the emergence of AI-driven and autonomous systems within modern defense ecosystems. It explores the operationalization of data-centric warfare, the governance frameworks required to build trust in AI-enabled decision systems, and the critical distinction between deployable capability and technological hype in shaping future defense investment.

WDS26 demonstrated meaningful progress in moving autonomous systems from controlled demonstrations to early operational deployment that deliver capability to meet adaptive threats. Swarming, AI-enabled planning, scenario building, intelligence fusion, and autonomous logistics were presented not as laboratory concepts but as capabilities entering force design and structures. However, the gap between prototype maturity and scalable operational integration remains significant. The gap is particularly acute in transitioning low technology readiness levels (TRLs) into delivery and achieving system readiness levels (SRLs).

The critical bottleneck is not the AI models themselves but the integration infrastructure: sovereign data pipelines, software defined radios (SDR), quantum computing at the tactical level, security accreditation for AIaugmented decision systems, and the doctrine governing human-machine teaming under operational conditions. Mission ready AI applications and use cases were a key topic of discussion at WDS26, leading to a safe use of AI approach that has the potential to reduce planning cycles and scenario building by scales of magnitude.

The governance conversation has matured but remains unresolved. Multiple panels at WDS26 addressed the need for AI assurance frameworks that establish trust in autonomous decision making – not abstract ethical principles but operational frameworks that enable commanders to rely on AI recommendations under combat conditions. The consensus is emerging that AI governance must be embedded at the design stage, not applied retrospectively, and those nations that establish credible assurance frameworks first will gain a regulatory and export advantage. AI governance is key but must not overtake the innovation and technology advantage currently enjoyed. Of concern, national defense ecosystems appear to prioritize governance over capability interests.

A candid assessment distinguishes three tiers to deliver deployable capability that meets the threat and has the agility to adress emerging volatility. Mature deployment includes AI enabled ISR processing, planning and scenario building, predictive maintenance, and automated logistics optimization. Emerging-operational capabilities include autonomous swarming, AI-augmented command support, radar, quantum, and cyber and electromagnetic convergence. Hype-exceeding-reality includes fully autonomous lethal decisionmaking, quantum-enabled battlefield networks, and seamless crossdomain AI orchestration.

Much discussion over quantum underlines a security spiral that has the potential of upending sovereign ecosystems. Quantum could accelerate cybersecurity risks, attack economic stability, and provide precision targeting at low cost to predatory actors. The investment implication is that capital should flow toward integration infrastructure and governance frameworks rather than headline-grabbing platform capabilities that lack operational scalability or adaptability.

Building these mature joint enabling architecture(s) into complex defense ecosystems are a key determinant of strategic advantage. Modern defense ecosystems must grapple with uncertainty and prioritize IROI that balances tangible cash and the intangible benefits required of sovereign security as a public good.

Ecosystem gaps and strategic friction points

Legacy system integration

Every defense force operates on a foundation of legacy. Systems designed decades ago for single purposes, by different suppliers working to different standards, cannot simply absorb modern AI tools, predictive algorithms, or shared data models. They require translation layers, data cleansing, security accreditation, and frequently, political navigation around existing procurement agreements. The fusion layer concept is the right architectural response, but implementing it across heterogeneous, safetycritical environments remains the single largest technical challenge in defense transformation.
Talent scarcity

The workforce constraint is real and binding. Shortages in CEMA, systems engineering, AI, and data analytics are global phenomena, but they are particularly acute in defense markets undergoing rapid expansion. Saudi Arabia has welcomed institutional investments through NAMI, GAMI, SAMI, and SDAIA are strategically sound, but the pipeline from education to operational proficiency requires years to mature. In the interim, the gap between technology acquisition and workforce readiness risks creating expensive underutilization of advanced platforms.
Certification and standards fragmentation

Defense systems are safety-critical. Every integration point must be tested, evaluated, and certified. When platforms from multiple OEMs, designed to different standards, must interoperate within a national or coalition architecture, the certification burden multiplies exponentially. There is no global standard for AI assurance in defense, no universally accepted framework for autonomous systems certification, and insufficient institutional capacity in most markets to conduct the required testing at the pace modernization demands. For example, cyber and electronic warfare (EW) ranges are key to developing tactics training and procedures (TTPs), countermeasures, ensuring force protection (FP) and safety critical systems, and yet there are no recognized standards to fulfil.
The prototype-to-field gap

Innovation ecosystems are producing capable prototypes at unprecedented speed. Converting them into fieldable, sustained, and scalable capability that addresses prevailing threats remains slow. Acquisition frameworks written for hardware procurement are poorly suited to software-defined capabilities with continuous update cycles. Until procurement doctrine evolves – and the institutional incentives around it change– the gap between what is technically possible and what is operationally deployed will persist.
Governance and data trust deficits

Interoperability depends on data sharing. Data sharing depends on trust , sovereignty and above secret data sharing. Trust depends on governance frameworks and regulatory compliance that define ownership, access conditions, classification protocols, and accountability. In environments where coalition partners, government agencies, and private industry must all access shared data, these frameworks are underdeveloped. Without them, the most advanced architecture remains operationally isolated . The gap between business-space and battlespace in these areas is particularly acute.