AI Is Already in Use Across Your Business. Governing It, Testing It, and Seeing It Is the Work That Comes Next.

AI Is Already in Use Across Your Business.

Governing It, Testing It, and Seeing It Is the Work That Comes Next.

Most organisations across Ireland and the UK now have AI in active use, and in a lot of cases it arrived without anyone formally deciding to bring it in. People started using AI tools because they made the work faster and easier, and adoption spread through teams long before policy, security testing, or monitoring had a chance to catch up. The technology has quietly become part of how the business runs.

The challenge is that AI has moved into the organisation faster than the governance around it. Staff are putting company information into tools that have never been reviewed, copilots are being switched on across departments, and in a growing number of cases AI is now taking actions on people's behalf. The value is genuine, and so is the exposure. The gap between how widely AI is used and how well it is understood and controlled is exactly where the risk sits today.

 

AI Adoption Has Moved Faster Than the Rules

The pace of change has been striking. Employees bring their own tools to work, leaders actively encourage experimentation, and the tools themselves keep getting more capable. Chatbots became copilots, and copilots are becoming agents that can retrieve data, make decisions, and trigger workflows with limited human oversight. Each step forward has delivered something useful, which is why adoption has been so quick and so broad.

Governance has had a harder time keeping up. In many organisations there is still no clear policy on what staff can and cannot use, no agreed position on what data is safe to share, and very little visibility into where AI is already operating. That is understandable given how fast everything has moved, and it leaves a recognisable problem behind it. Sensitive information flows into tools nobody has assessed, business decisions get shaped by systems nobody has tested, and the compliance picture becomes harder to explain to a board, a regulator, or a customer with every month that passes.

 

What the Data Actually Shows

The research paints a consistent picture. A global survey of more than 48,000 professionals carried out by KPMG and the University of Melbourne found that 57 percent of employees admit to hiding their use of AI from their managers, and close to half had entered company information into freely available public AI tools. Other workplace studies through 2025 found that while a clear majority of employees now use AI in some form, only around a third of organisations have a formal AI policy in place at all.

These findings matter because they describe a situation most leaders will recognise in their own organisation. AI use has become normal while clear governance around it remains rare, and that combination is precisely what turns everyday productivity into quiet, unmanaged risk. For an end user organisation, it means data and decisions are exposed in ways the business cannot yet see. For a partner advising those organisations, it represents one of the clearest service opportunities to emerge in years.

 

Three Challenges That Tend to Arrive Together

When organisations start to take AI seriously, three challenges usually appear at the same time.

The first is governance and policy. Regulation is tightening, with the EU AI Act and the ISO 42001 management standard setting clearer expectations for how AI is used, documented, and overseen. Organisations need a defensible position on AI that satisfies regulators and reassures customers, and they need it written down rather than assumed.

The second is a new category of vulnerability. The AI systems themselves, including chatbots, copilots, and agentic workflows, can be manipulated in ways that traditional security testing was never designed to catch. Techniques such as prompt injection, where an attacker feeds hidden instructions into a system, and excessive agency, where an AI is given more freedom to act than it should have, are genuine weaknesses that call for dedicated testing.

The third is visibility. Shadow AI spreads through departments in much the same way that unapproved software once did, and most organisations have very little insight into where AI is being used or what data is flowing into it. Without that visibility, governance and testing can only ever cover the part of the estate the business already knows about.

 

The Cost of Getting It Wrong Is Rising

Part of what makes this conversation urgent is that the consequences of inaction are growing. Regulation is moving from guidance towards enforcement, and the organisations that have given AI no thought will be the ones scrambling to respond. Real world incidents are already showing that untested AI systems can be exposed, misused, or made to behave in ways their owners never intended.

For partners across the channel, the pressure and the opportunity arrive together. Customers are starting to ask harder questions about how AI is governed and secured, and the providers who can answer those questions with a clear, structured approach will be the ones trusted to lead. Building AI governance, testing, and monitoring into a service offering is quickly becoming a way to deepen customer relationships and stand apart from competitors who are still treating AI as somebody else's problem.

 

A Smarter Approach: Govern It, Test It, and See It

The encouraging part of all this is that the path forward is reasonably clear. Securing AI works best when it is treated as a continuous programme that brings policy, testing, and monitoring together and keeps them current as the technology evolves.

It starts with a defensible AI policy aligned to recognised standards such as ISO 42001, and organisations that already hold ISO 27001 have a real head start because so much of the underlying discipline is already in place. From there, the AI and LLM systems in use can be tested specifically for the new vulnerabilities they introduce, in the same way that networks and applications have long been tested for theirs. Monitoring and detection then give the business the visibility to find shadow AI, understand where it is being used, and keep watch over AI activity as it grows.

Brought together, these three disciplines turn AI from something happening to the organisation into something the organisation governs. That is the case for treating AI security as a discipline, whether you are protecting your own business or helping your customers protect theirs.

 

Upcoming Webinar

Renaissance and DigitalXRAID are hosting a session on governing, testing, and seeing the AI that is already in use across modern organisations. The session is built for two audiences at once: organisations that want to secure their own AI use, and partners who want to build AI security into what they offer their customers.

Chris Leppard, Head of Consultancy at DigitalXRAID, will join Michael Conway, Managing Director of Renaissance, to explore the consultancy, testing and SOC engineering considerations across all three parts of the challenge.

In the session we will cover:

• Why AI already in use across your organisation makes governance an immediate priority.
• How the EU AI Act and ISO 42001 apply to organisations in Ireland and the UK, and why holding ISO 27001 gives you a head start.
• Why AI and LLM systems bring a new class of vulnerability, from prompt injection to excessive agency, that needs dedicated testing.
• How real-world incidents show that untested AI is already being exposed.
• How to detect shadow AI and build the visibility to monitor AI activity right across your environment.
• Why securing AI works best as a continuous programme spanning policy, testing, and monitoring.

The session takes place on Tuesday 29th September at 11am, to register now follow the link https://renaissance.renaissance.ie/c/456978/