Our Voice

Think of it as a conductor leading an orchestra. Each instrument plays its part at the right time. The result is harmony. In IT, this harmony translates to:

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.

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.

Forecast meetings get blamed for a lot. They are too long. Too vague. Too optimistic. Too subjective. Too focused on the same deals. Too full of phrases like “still confident”, “good engagement” and “waiting on feedback”, each of which should probably be treated as an early warning signal rather than a sales update.

AI has become the answer to almost everything. Convenient, really. Businesses apparently needed another way to avoid defining their actual problems.

Shadow AI is not always reckless behaviour. In most cases, employees are trying to work faster, reduce admin and improve output. The problem is that they are doing it through tools the business cannot see, govern or secure.

Shadow AI happens when employees use unapproved AI tools to move faster, write better, summarise information or solve problems without a formal business route.

AI adoption is moving faster than most businesses can govern it. Employees are already using AI to draft, summarise, research, analyse, rewrite and automate

Agentic AI is becoming one of the most talked-about areas in business technology. Predictably, that means it is also being misunderstood at speed.

Most businesses do not have an AI problem. They have a business discipline problem. AI has simply made it harder to hide.

Most organisations think AI governance is about compliance. It isn’t. It’s about preventing your business from quietly breaking while everyone believes things are improving. The uncomfortable truth about AI adoption AI is already in your business. Not because you approved it, but because your people are using it. They are writing emails with it. Summarising documents. Generating proposals. Uploading content into public tools. Some of it is useful. Some of it is risky. Most of