Highlights
Clients are pragmatic about AI, and enterprises are moving on two tracks. First, AI for technology: embedding intelligence into software engineering and IT operations, including agentic service management that reduces manual work and supports more autonomous operations.
Second, AI for business: using contextual knowledge to shift AI from decision support to a co-architect across supply and value chains. With 65% of companies citing human intuition and creativity as their edge, success depends on empowering people and redesigning roles not just deploying tools.
We reflect this in our own journey, investing in talent, infrastructure, and partnerships to become the leading AI-led tech services company and deliver maximum customer value.
CEO's often ask me how to modernise legacy systems that were not built for what comes next.
Becoming AI-first requires a modern tech stack. We focus on mainframe exits and application rationalisation, so heritage systems do not block innovation. We also drive efficiency to release capital for modernisation.
Research conducted with AWS found that while 75 per cent of manufacturers expect AI to be a primary margin driver by 2026, only 21 per cent describe themselves as fully AI-ready. Modernisation is the bridge that sustains the present, while transformation builds the future.
In Europe, sovereign cloud has matured beyond compliance into supply chain security.
Sovereignty is an extension of control. If an enterprise depends on global hardware, software, or operations, it remains exposed to external shocks.
Designing for data residency and regional jurisdiction reduces strategic dependency and strengthens continuity. The World Economic Forum’s Global Cybersecurity Outlook 2026 reports that 66 per cent of organisations have adapted their technology strategies due to geopolitical volatility.
Sovereignty is no longer just about where data sits. It is about which workloads require residency, what requires local control, and how compliance can be turned into resilience.
Cyber risk is evolving as fast as AI. 94% of executives see AI as the biggest driver of cyber risk change. While ransomware still matters, focus is shifting to cyber-enabled fraud and AI-driven social engineering, with 77% reporting increases. A human-only defence model is no longer viable.
Risk is amplified by ecosystems 65% of large organisations cite third-party and supply chain vulnerabilities as their top resilience challenge.
The focus must shift from defence to resilience. Security should be built into systems, with fast detection, containment, and recovery. AI helps prioritise signals, predict attack paths, and speed up response.
Sustainability should be a core outcome, not a side initiative. Delivering it requires a clear net-zero strategy, built on accurate measurement, transparent reporting, and full supply chain integration.
Through our pace ports and net zero consulting, we help clients translate sustainability goals into operational reality, address Scope 3 complexity, and improve transparency.
Our own science-based commitment to net zero by 2030 reflects this approach, aligning technology with purpose to turn environmental mandates into a business advantage.
When clients ask me how to become faster and more efficient, the answer is structural optimisation. Consolidating infrastructure, applications, and vendors reduces cost and complexity, but the bigger lever is operating-model redesign. We are moving from meetings designed for discussion to environments designed for co-creation and execution.
To support better decisions at speed, we have introduced Intelligence Choice Architecture, informed by collaborative research with MIT. It combines generative and predictive AI to generate options, identify missing information, and test likely outcomes. This shifts AI from a back-office tool to a boardroom partner compressing strategy cycles from months to days.