Farnborough Airshow 2026 and the increasing relevance of AI in manufacturing, aerospace and defence

Big show, participating IT players and a very special event concept

The Farnborough Airshow is really an amazing show. If you are sensitive to noise, you should definitely bring your noise-cancelling headphones. Attached to the airshow is a fairground with 4 halls where various vendors from manufacturing, aerospace and defence show their latest technologies. In 2026, autonomous systems like drones were among the most interesting exhibits. PAC attended the Farnborough Airshow in July 2026 to discuss with vendors the growing role of AI in manufacturing, aerospace and defence. Several software and IT service providers were present at the show, including, for example, TCS, Capgemini, Accenture, Deloitte, KPMG, BCG, Siemens, Dassault Systèmes, Cognitus (an IBM company) and Belcan (a Cognizant company). What makes this airshow somewhat special is the Chalet concept, which means that many of the above-mentioned vendors have a private place to talk to customers and follow the airshow. This concept makes the show a more closed system, which fits well the small and sensitive customer group they serve but limits the ability to interact openly with as many different vendors as possible in a short period of time.

Humans and AI will increasingly work hand in hand, in IT and in “grey factories”

TCS was so kind to invite us to a full briefing at the event to share its perspective on AI, physical AI, digital engineering and sustainability. For TCS, AI is not just another service line, as it impacts all existing service areas. The company envisions a future where 600,000 TCS employees will work together with a similar number of AI agents to deliver internal and external services. This shows how fundamental the scaling aspect quickly becomes within the AI context, not only in the IT space but also in manufacturing. Similar to its own transformation, TCS believes in a future where humans and physical AI agents work hand in hand in the factories. The so-called “grey factories” will be automated to around 80%, while humans take care of the remaining 20% of work. PAC believes that this is a very realistic scenario for many manufacturing subsectors. Similar to autonomous driving, automating the last 20% will be hard to do in many cases. This means that, while we increasingly observe AI supporting workers in their daily tasks, we will also see workers help AI deal with its limitations in the physical world.

Why POCs are a common problem in scaling industrial AI projects

TCS shared some of its early lessons learned about introducing AI in the manufacturing industry. According to TCS, only one-third of AI projects reach the scaling stage, and POC projects are often part of this issue. This is due to the fact that POCs often ignore the difficult aspects of data access, integration and context. Although AI can help overcome data silos in manufacturing, companies should not underestimate the complexity of building the data foundation and a company-wide knowledge graph. To achieve this, companies should not just digitize their processes and harmonize their data; it is also essential to simplify processes first to reduce complexity. TCS believes in a bottom-up approach to gradually realize this and focus on use cases that provide a clear RoI. To support clients on this journey, TCS has already developed more than 350 industrial AI solutions for many different use cases, especially around vision AI, warehouse and SCM. Examples include AI-based robodogs (also called quadrupeds) for welding inspection, digital twin simulations for factory layout optimization, AI-based HR operations for reduced cost per new hire, and AI-based DevSecOps (coding/testing) for the development of aircraft engines. This underlines that the availability of AI solutions is often not the limiting factor; instead, the issue is the readiness of data and processes to scale AI across the company to maximize RoI.

Command and control systems are becoming more software-defined to embed an increasing number of AI-based and autonomous systems

Collecting data and insights, combined with effective decision-making, has always been crucial in the military space. To address this issue, command and control systems (C2 systems) have existed for years. However, the landscape is becoming ever more complex, and decisions have to be taken in real-time. Armed forces need big data analytics in the cloud to understand the bigger picture of the conflict, edge AI to support troops on the frontline, AI-based autonomous systems to replace humans in dangerous missions, and software-defined systems to combine all these elements in an open and flexible, but also tightly integrated system. To realize this, software-defined systems require something like a joint operating system. More and more vendors are entering this space. In addition to more specialized vendors, like Anduril Industries and Shield AI, we also saw at the event that IT service providers like Capgemini have started positioning themselves in this field. Capgemini presented its connected defence platform, OmniAware, at the airshow. If you are interested in how digital technologies are reshaping the defence sector, see PAC’s report on the latest activities of leading vendors in this space: Smart Defence Vendor Landscape.