Artificial intelligence is reshaping how organisations operate, compete and deliver value at speed. The question is no longer whether to adopt AI, but how to do so responsibly, at scale, and with people at the centre.

To lead this charge, NCS created a new role: Chief AI Officer - the first in the company's 45-year history. Appointed to the position in 2026, Edward Chen brings with him a career spanning cyber operations, digital transformation and national security.

In this Q&A, Edward shares what the role entails, how NCS is building and deploying AI capabilities across its clients and operations, and what the rapid rise of AI means for the future of work.

1. What prompted the creation of the Chief AI Officer role at NCS? 

AI is fundamentally changing how businesses operate and compete. As an AI-led tech services company, dedicated leadership helps NCS drive its AI strategy with greater focus, speed and coordination.

The Chief AI Officer role was created to accelerate how NCS develops and brings AI platforms and products to market, while scaling AI adoption and transformation across our clients and operations. I lead NCS' new AI Central team, whose mission is to develop secure, scalable and enterprise-grade AI platforms and products, deliver AI solutions at speed, and translate client needs into measurable business outcomes.

More importantly, AI Central helps clients move from experimentation to operationalisation. Many organisations today are still exploring AI through isolated pilots. The real challenge and opportunity is embedding AI into core business processes in a way that is trusted, repeatable and scalable.

2. How does your background in cyber operations, digital transformation and national security inform how you approach this role? 

There are three ways I would put it.

First, talent is capability - whether in cyber or AI. At the Digital and Intelligence Service, I helped build cybersecurity capabilities from the ground up: recruiting the right talent, building the right culture, and creating teams that could move quickly while operating in high-stakes environments. I take a similar approach in building AI capabilities at NCS. In fast-moving technology domains, the differentiator is rarely just the technology itself. It is the quality of the people, how well they work together, and how quickly they can turn ideas into operational outcomes.

Second, users are at the heart of every transformation effort. Technology transformation only succeeds when users trust and adopt it. The best systems are the ones people actually use, integrate into operations, and rely on every day. Many of NCS' clients operate in regulated and mission-critical sectors such as government, defence, healthcare, financial services and telecommunications, where AI must deliver both speed and trust.

Third, AI and cybersecurity are increasingly inseparable. Much of my work in my last few years at DIS and CSA involved understanding how AI is changing the threat landscape - from generative AI-enabled disinformation to AI agent security - and how we can also use AI to defend more effectively. That perspective shapes how we build AI products at NCS: secure-by-design, with the assumption that nefarious actors will probe these systems as well.

Ultimately, the role is about translating technology into mission and business outcomes. That is a discipline I have practised throughout my career, and it is what many organisations are looking for as they move AI from experimentation into production. 

3. How has the appointment of a Chief AI Officer changed how AI initiatives are managed and coordinated across NCS? 

The CAIO appointment gives clients faster access to proven AI solutions adapted to their specific industry challenges. AI Central develops reusable AI platforms, products and governance frameworks centrally, while our industry groups rapidly customise and deploy them for each client's operational context. This means clients benefit from solutions that have already been tested and refined across multiple deployments, with enterprise-grade security and governance built in from day one.

More importantly, the appointment helps align AI efforts across the organisation around a common strategy, operating model and set of platforms. AI belongs to everyone in NCS - it is not solely the responsibility of one team or one leader. For AI to be truly woven across a large organisation like NCS, it must be driven top-down through leadership, bottom-up through innovation, and horizontally across the enterprise through close collaboration between teams. The role of the CAIO is therefore not to centralise all AI work, but to create unity of effort across the organisation so teams can innovate quickly while building on common platforms, governance and engineering standards. 

4. Many organisations talk about deploying "AI at scale", but what does it actually mean in operational terms? 

"AI at scale" means moving beyond pilots and experimentation into proven, repeatable capabilities that deliver real outcomes across clients, sectors and internal operations.

Operationally, this requires standardised methods, reusable platforms and common engineering building blocks so solutions can be deployed faster, more consistently and more securely across different environments. It also involves automated systems to build, test, monitor and continuously improve AI solutions, while embedding AI directly into everyday workflows and core business systems.

AI at scale cannot operate without trust. Responsible AI must be built in from the start - with strong privacy and security controls, governance, risk management and continuous cost monitoring to ensure solutions remain reliable and deliver measurable business value over time. Ultimately, AI at scale is not about having more prototypes. It is about operationalising AI in a way that is trusted, repeatable and sustainable.

5. Looking ahead, how do you see the way people work with AI evolving, and what does that mean for how we all need to adapt? 

Within the last year, we have seen AI mature significantly, especially in the area of code development. Previously, when using AI in its early state, you could typically only rely on it for a few minutes before needing to intervene and check the code. Now, coding agents can work autonomously for hours.

This means we need to learn how to work very differently. We are very used to coding and typing code ourselves, but now we need to think about how to delegate effectively, so that multiple agents can work for us simultaneously while we take on the role of supervisor.

I am an AI optimist, so I believe we are heading somewhere exciting. I hope AI will become ambient, just as spreadsheets are in finance or GPS is in driving. You do not think about using those technologies; they are simply part of how you work. In five years' time, I hope people will not think about using AI per se. It will simply be part of life.