Our Voice

AI use itself is not the problem. Unmanaged AI use is the problem. The organisations that create value from AI will not be the ones that simply give everyone access and hope judgement appears by magic. Hope, as usual, remains a poor operating model. The winners will be the organisations that make AI useful while keeping control over data, security, accountability, quality and decision-making.

Agentic AI represents the next stage. It is not simply a better chatbot. It is a different way of applying AI to work. Instead of waiting for a user to ask one question and then producing one answer, an AI agent can work towards an objective, plan the steps required, use tools, check progress and move a task forward across a workflow.

Employees are using AI to draft content, summarise meetings, analyse documents, review data, generate ideas, support customers, write code and automate routine work. In many organisations, this is already happening before leadership has agreed which tools are approved, what data is safe to use, where accountability sits and how AI-supported outputs should be checked.

The issue is not that people want to use AI. That is understandable. People are under pressure, work is fragmented, and AI can remove some of the manual load. The issue is that many organisations still do not have a clear view of where AI is being used, which tools are approved, what data is being shared, who owns the risk and how AI-supported outputs are being reviewed.

It usually begins quietly. Someone uses a public AI tool to rewrite an email. Someone else uploads meeting notes for a summary. A manager uses a browser extension to improve a proposal. A team adopts an AI note taker because it saves time. An analyst pastes spreadsheet data into a tool to get a quick answer.

AI changes the cyber security conversation because it connects productivity, data, identity, systems and decision-making in new ways. A poorly governed AI tool is not just another application. It can become a route into sensitive information, a mechanism for oversharing, a source of unreliable outputs or a workflow layer acting across systems without enough control.

Enterprise scalability is not achieved by making everything larger. It is achieved by making the operating model repeatable, governable and adaptable. That is why modular-by-design architecture matters.

Why Scaling An Unstable Environment Makes Everything Worse Most organisations want to scale before they have stabilised. That is understandable. Scale sounds strategic. Stabilisation sounds like cleaning up.

Many organisations believe they have disaster recovery covered because backups exist, replication is configured somewhere and a document labelled “DR Plan” sits in a folder nobody has opened since the last audit. This is comforting in the same way a locked fire exit is comforting. It looks useful until the moment it is needed.

Most organisations do not struggle with technology delivery because people are not working hard. They struggle because work moves through too many disconnected stages, with unclear ownership, inconsistent testing, weak release control and limited evidence of what actually changed.

At its simplest, Infrastructure as Code, or IaC, means defining infrastructure through code rather than building it manually through portals, tickets, scripts and human memory. Networks, virtual machines, storage, identity settings, databases, security rules, monitoring, policies and application environments can be described in version-controlled files, reviewed, tested and deployed through controlled pipelines.

The problem is not that supply chain teams lack effort. Most are already working hard. The problem is that too much of that effort is beingn access AI tools. In most cases, they can. Microsoft Copilot, ChatGPT, embedded AI in productivity platforms, automation tools and emerging AI agents are now available to businesses of almost every size. The barrier is no longer access. The barrier is whether the organisation knows how to turn access into better work.

The question is no longer whether they can access AI tools. In most cases, they can. Microsoft Copilot, ChatGPT, embedded AI in productivity platforms, automation tools and emerging AI agents are now available to businesses of almost every size. The barrier is no longer access. The barrier is whether the organisation knows how to turn access into better work.