Securing AI

Employees and business teams can introduce AI tools before security and governance arrangements are established.

Without a clear view of usage, your organisation may struggle to determine which systems hold sensitive information, who is responsible for them or whether they have been assessed.

This creates uncertainty around acceptable use and makes it harder to apply consistent controls. Security needs to be part of adoption decisions from the beginning and remain involved as use cases develop.

An AI assistant that generates text presents different risks from an agent that can run code, modify records or initiate business processes.

As capabilities expand, you need clear boundaries around permitted actions and access. Ownership must remain identifiable, particularly where several teams or systems are involved.

Human approval, logging and other controls should reflect what could happen if the agent makes an error or is manipulated. Greater autonomy requires careful consideration of the consequences.

AI security includes the application, its data, connected tools and supporting infrastructure.

Weak access controls or insecure integrations can expose information. Manipulated instructions may cause an application to behave in unintended ways. Changes to models, prompts and connections can also affect how existing controls perform.

Your organisation needs a repeatable way to assess these risks and test whether protections remain effective.

Our advisory services help you review current arrangements, identify gaps and establish an approach to governing AI.

We support work relating to the EU AI Act, NIST AI RMF and ISO/IEC 42001. The appropriate approach depends on your activities and requirements, with a clear distinction between regulatory obligations, voluntary frameworks and management system standards.

We help translate these considerations into responsibilities and processes that your teams can apply.

Our AI Identity Framework consultancy addresses the identities behind AI agents and related services.

We help define ownership, classification and lifecycle controls, alongside access to information and tools. This includes considering the authority an agent needs and where additional approval should apply.

Clear identity governance helps your organisation manage AI as a business capability with accountable owners, rather than an unmanaged collection of integrations.

AI can make existing information more accessible, so weaknesses in data protection need attention before deployment expands.

Our AI Data Security Assessment examines risks associated with connecting AI to business information. We help identify inappropriate access and other exposures that could undermine secure adoption.

Findings support a practical remediation plan and more informed decisions about which data an application should use.

We help implement tools and controls for safe employee use of AI and for agentic applications operating within your organisation.

Guardrails should reflect the intended use case, the information involved and the actions available. They also need to support clear escalation when activity falls outside acceptable boundaries.

These controls work alongside governance and access management, helping your organisation apply its decisions in practice.

Our services support the secure use of AI coding agents and the implementation of AI applications and agentic frameworks.

We help you consider security across the application and its integrations, including the access and capabilities given to development tools.

This supports teams introducing AI into software delivery while maintaining attention to the systems and information those tools can reach.

Our AI Security Posture Management tooling and services help you manage the security of cloud-hosted AI applications.

This work connects with the protection of underlying cloud infrastructure, recognising that an AI application depends on the configuration and security of the environment around it.

Ongoing visibility helps teams identify weaknesses and prioritise improvements as deployments change.

Our AI penetration testing assesses weaknesses in your own AI applications.

Agentic and frontier AI attack simulation provides additional testing using relevant tools and techniques. The scope is agreed around the application, its functionality and the risks you need to understand.

Findings help you validate controls and prioritise remediation before weaknesses cause wider consequences.