The global defense industry is facing unprecedented pressure. As armed forces worldwide race to scale up, requirements grow increasingly complex, cybersecurity becomes paramount, and artificial intelligence (AI) is unavoidable. This dynamic threatens to slow design cycles, jam manufacturing, and delay delivery – precisely when speed matters most. Yet, paradoxically, AI itself, especially „agentic” AI, is poised to change the game.
AI, The Acceleration Engine: From Data to Critical Decisions
AI acts as a catalyst, removing friction from the entire workflow. It sifts through mountains of data to pinpoint precise requirements, runs simulations through „digital twins,” and identifies more efficient logistics paths. But speed alone isn’t the goal. Practical AI integration demands careful change management, ensuring data trustworthiness and enabling people to make critical decisions based on clearer, better information.
Experts highlight that in a turbulent geopolitical environment, demand for defense clients is enormous, leading to significant backlogs. This situation generates immense pressure, forcing them to increase their speed to market, cut costs, and maintain resilience. A unique aspect of the defense industry is the consortium model – the predominant form of collaboration – which multiplies the operational and logistical complexity of the supply chain.
Doubling Output with Fewer People: Technology’s Role
Data, AI, and related technologies are becoming crucial to help companies address these challenges. Many clients aim to double or even triple their output in the coming years, with fewer people and in a far more complex world.
The situation has dramatically evolved in Europe, where nations are now investing up to ten times more in defense than before. This sudden surge compels companies to deliver much more material, much faster. Simultaneously, battlefield technology is evolving rapidly. New products require advanced engineering, time to market must shrink, and production needs to scale massively. All of this occurs amidst raw material shortages, from microchips to components and subcomponents.
Drones serve as a prime example. From a relatively small market segment, they have become a decisive factor on the battlefield, and their manufacturing is arguably the most dynamic part of the industry, yet facing challenges at every turn. Although budgets are high and funding is not a bottleneck, many companies still struggle to keep up with demand.
Generative AI: The Solution to Overwhelming Documentation
Military requirements have transformed. While nations once defined their own standards, these are now integrated into massive documents, thousands of pages long, not dozens. An engineer must sift through everything, seeking relevant information and eliminating redundancies. This is where generative AI (GenAI) makes a significant difference, drastically cutting down this effort. An engineer can simply ask, „Show me all requirements related to laser technology,” and instantly obtain the necessary information.
In defense manufacturing, AI’s real impact isn’t just about automation. It’s also about enabling trusted, federated decision-making across consortia. Data must remain secure within „zero-trust” environments, but AI can surface the most relevant insights while adhering to security policies. This is the essence of real interoperability, allowing companies across Europe and globally to get to market faster.
Data Quality and the Human Factor: Obstacles to AI Adoption
Challenges surrounding AI persist. „Hallucinations” in GenAI raise similar questions for agentic AI, especially when systems operate autonomously. Data quality is the primary hurdle: if data is poor, the agent will fail. The real risk emerges when agentic systems operate autonomously. If something goes wrong, rapid detection is crucial to prevent unintended processes from being triggered. The impact of poor data quality is now far greater, as automation reduces human interaction points, allowing problems to escalate before detection.
Another major hurdle is operating AI within the security context of the defense industry. Not everything technically possible is acceptable from a security perspective. Defense companies cannot experiment as freely as others, risking the external exposure of sensitive information.
Furthermore, a persistent myth suggests AI will replace a large number of employees. The reality is that AI offers greater value in supporting people and eliminating time-consuming, repetitive tasks. However, this presents a challenge: employees need to be upskilled to take on more analytical, decision-focused roles. This is where change management becomes critical, as human readiness for AI is essential. Without acceptance and integration of AI by management, operations, and frontline workers, the technology will not deliver on its promise.
Necessity, Not Option: Investing in Change
Change management requires an investment at least equal to that in AI technology itself. There are still mixed messages among clients: Is AI just a buzzword, or does it hold real value? The answer lies in starting with small projects that yield quick wins, while also addressing change management properly, engaging stakeholders early, and investing proactively.
The real opportunity is to go big but remain focused, selecting one or two projects, implementing GenAI correctly, end-to-end. The challenge is to drive real change and clearly demonstrate value, not just in terms of resistance (fear of replacement), but also in building the momentum, governance, and trust required for AI to function within the organization. AI is incredibly powerful, yet also disruptive.
This represents a fundamental shift. Clients have moved from merely observing AI’s benefits to asking, „How do I execute this? How do I make it real?” It is no longer an option. At this point, it is a necessity.
