Contributed by George Carter
Founder of Darter Ltd, a technology strategy consultancy firm, and a strategy advisor to the MOD and private sector. His background includes AI strategy development and implementation with businesses of all sizes to advance AI adoption, data leadership within the RAF and private sector, and time at Dstl researching and consulting on warfare in the information age, digital and data.
The opportunities for the Defence and National Security sectors to deploy Artificial Intelligence and Machine Learning technologies are numerous and potentially game changing. There is much written about how AI enabled systems can, and increasingly are, being used to make sense of large amounts of intelligence data, support decision making in autonomous platforms, drive wargaming and simulation, along with a whole host of other operational use cases.
Civil Industry has been demonstrating opportunities for AI exploitation for many years and AI continues to have profound impact on the way the world conducts its business. Examples like OpenAI’s ChatGPT showing the potential of Large Language Models (LLMs) or Amazon’s Supply Chain Optimisation Technology (SCOT) which forecasts customer demand and uses this to distribute stock to warehouses close to likely shoppers have radically changed the way we work and live.
As such, AI will undoubtedly be a focus area for the on-going Strategic Defence Review, launched by Prime Minister Keir Starmer on 16th July. Indeed, one of the key themes will be “The opportunities for modernisation and transformation, and greater productivity, including through the rapid and consistent application of Digital Age technologies.” However, within this assessment, is there a risk that by being distracted by use cases and opportunities, the building blocks to securing future innovation and agility might be missed?
Getting it right
So what does “getting it right” look like? The key components common across businesses fully capitalising on the development on AI can be narrowed down to five things:
- Strategic vision
- Access to data
- The agility to develop, test and deploy at pace
- Workforce & Culture
- The ability to scale and secure.
This is where Defence must focus if it is to capitalise on the opportunities offered by AI.
Strategic Vision
In 2022 Defence published its AI strategy which describes a vision to become “the world’s most effective, efficient, trusted and influential Defence organisation for its size, in terms of AI’.
Two years on, and there are some examples of good progress, particularly in the domain of proofs of concept, technology trials and small-scale deployments. This includes a number of high-profile success stories, including those under the oversight of Dstl as part of the AUKUS Pillar II programme that deployed on a US P8 Maritime Patrol Aircraft (MPA) in order to accelerate the processing of sensor data. The Royal Navy have acquired XV Patrick Blackett, a trials vessel built by Damen Shipyards specifically as a trials and autonomy development ship. In the land domain, the TORVICE trials saw the UK, Australia and the US trialling the integration and networking of different land assets across a series of mission sets.
More centrally, and potentially most critically, in 2022 the Defence AI Centre (DAIC) was formed. Tasked to facilitate closer collaboration in the field of AI across the Defence enterprise, the DAIC is becoming the key focal point to drive this innovation.
Nonetheless, the MOD doesn’t seem to be clear about where it will invest if it is truly committed to becoming a data enabled fighting force. Alongside continued innovation pilots, which do play a key role in determining the art of the possible, the government must now state its priority investment areas and follow through with more strategic and significant funding. This enables industry to confidently invest their private capital in research and development of new capabilities where it will have the most significant impact, ultimately offering the best capability where it is needed.
Data
UK Defence is not short of data, with almost 500,000 people employed directly in the armed forces, civilian roles and broader industry. Across the ecosystem, Defence is managing personnel, running airlines and medical practices, developing and building vehicles, and operating complex logistics chains, all of this generating mountains of valuable data. The challenge for Defence is that this data is often locked away behind complex commercial agreements, data classification requirements and a multitude of other restrictions that prevent information being moved from where it is created to where it can be exploited.
Agility
On top of the data access challenge, there is the agility challenge. Due to the increasing technical complexity of programmes, challenges in accessing the skills and the speed of delivery required, more and more work is contracted through complex commercial agreements with third party Defence partners. These commercial agreements rarely adequately define dataflows and often create commercial blockers and misaligned incentives without the flexibility to inject innovation or challenge the traditional ways of working. It is critical that Defence moves to more flexible contracting that incentivises a collaborative approach to data and enables innovation to be introduced at each level of the enterprise.
Workforce & Culture
Delivering adoption at the scale required in any sector, but even more so one as complex as Defence, requires a whole force approach. Developing the workforce within Defence that will drive AI adoption requires a three-pronged approach.
• Firstly, those setting requirements for future capabilities must develop the skills to identify and articulate not just the problem at hand, but also the potential of AI solutions and the need for freedom to innovate throughout the life of assets.
• Secondly, building trust and adoption among personnel is crucial. Efforts should focus on clear communication, education, and demonstrably responsible AI use cases.
• Finally, fostering a collaborative environment is key to driving up the available skill base.
Building strong partnerships with industry and nurturing internal AI talent through targeted training programs will create a skilled workforce capable of driving Defence's AI ambitions.
Scale & Secure
Experts across the world have highlighted that while advancements in algorithms are crucial, the real challenge for Defence lies in building the complex infrastructure needed to deploy AI across its existing networks at the scale required. This includes targeted investment in the network infrastructure, cloud capacity and support personnel.
This often overlooked, but ultimately crucial investment must be accelerated if Defence hopes to deliver exploitation of AI beyond the experimental scale and ultimately transform the fighting force.
Conclusion
The Strategic Defence Review is a fantastic opportunity to make generational change in Defence, but that change will not come from simply “doing more AI”. Defence must focus on naming its top priorities for development, find new ways of working flexibly and innovatively with commercial partners, unlock access to data, train its staff to direct, adopt and build solutions and put agile technologies in place that connect the solutions with real operational users.
If all this can be achieved, industry will be in a much stronger position to direct the significant private venture investment available to accelerate change - ultimately delivering the transformative effect needed in a more dangerous world.
