The Business of AI in UK Defence and National Security
Al Bowman
General Manager, Defence & National Security, Mind Foundry
Over the last few years, we've observed how discussions around adopting AI almost invariably default to focusing on data, model types, and the architecture of the deployment methodology, in other words, the technical meat of the solution. However, the harder problem is navigating the business of AI.
As was noted in the recently published report, Developing AI capacity and expertise in UK defence, “too often AI is still treated as a novelty rather than as something that will soon be a core part of defence’s toolkit.” If we can unite the UK’s currently disjointed AI landscape in Defence, we can create a wider tech ecosystem with vastly increased robustness against the inevitable uncertainty and challenges of the immediate and long-term future.
Partner, Partner, Partner
The types of problems that AI can help solve are invariably complex and require a range of skills. Mind Foundry is not an expert in building hardware, nor are we a systems integrator. The good news is that we don't have to be because that expertise already exists. Through partnerships with the end-user community, the MoD, and the ecosystem of suppliers, the full weight of the combination of different skills can be brought to bear on these hard problems, culminating in a solution that is greater than the sum of the parts.
With all the partner building blocks in place, we can build a prototype or proof of concept in weeks; this isn't the time-consuming part of the process. What takes time is lining up all the right stakeholders, suitably incentivised to engage alongside a suitably identifiable problem.
Listen to the User, Not the Technologist
Given the above context, it can be easy to lose sight of the end goal of AI adoption; it is not to accelerate AI development or explore new technology. Rather, the priority is to make highly trained end-users more effective in their roles and to deliver critical insight at the speed of mission relevance. The goal is to accelerate the speed and precision of decision-making by introducing AI into the human decision-making loop.
A challenge in ensuring that the developed capability aligns with user needs is the requirement documents. User Requirement Documents (URD) and other references for capability development are often unwieldy and inflexible, not written with software in mind, and can be one step removed from the end-user community. What seems at first to be a key user priority when writing a URD can rapidly evolve, pivot, or even be replaced as a result of further research and development.
Closing this gap between what the process asks for and what an operator actually needs produces insight that drives capability and product development in a very different and more variable way. Any URD and supporting process should allow adaptation and evolution based on user feedback as new requirements are discovered and existing requirements change.
Show, Don't Tell
AI in action is very different to AI in theory. When you can demonstrate AI in action, delivering insights using models trained on complex data to deliver insight at a pace unimaginable under current constraints, then that can be transformative - it can bridge the gap between the theory of AI and the reality of where we are now. Let the technology speak for itself rather than you speaking for it.
UK Sovereign AI for a More Secure Future
Too much has been written about the possible futures that AI could support, yet not enough time and effort has been spent building them. By solving some of the problems of the business of AI rather than over-indexing on the technology itself, we will get closer to bringing some of the possibilities to life.
The UK is a global leader in AI, and its defence sector should reflect that strength by embracing innovation in the wider technology ecosystem. By simplifying processes, sharing resources, and fostering partnerships, the defence sector can turbocharge innovation, ensuring value gets to end-users more quickly.
