AI Security & Data Protection

Protect the identities, data, applications and actions AI depends on.

Extend established cybersecurity controls to the new risks created when employees, copilots, models and agents can access information and act across business systems.

AI Security
AI security control model
Visibility Shadow AI
Identity Access
Data Protection
Apps & agents Control
Questions we help answer

Start with the decisions that shape the initiative.

Where is approved and unapproved AI already being used?

Which information can AI retrieve, infer, generate or expose?

How are human, workload and agent identities governed?

Can applications or agents be manipulated into taking unintended actions?

What we do

Structure the work around decisions and outcomes.

01

AI-use visibility & access

Review approved and unapproved AI services, browser/SaaS exposure, identities, permissions and current control coverage.

02

Data protection

Assess sensitive data exposure, information classification, DLP/DSPM, retrieval paths, prompts, context and outputs.

03

AI application & agent security

Review APIs, RAG, connectors, MCP/tools, agent privileges, AI-generated code, testing, logging and runtime controls where relevant.

04

Monitoring & incident readiness

Extend detection, investigation, escalation and response procedures to AI misuse, agent actions and AI-related incidents.

Our approach

Discover. Prioritize. Deliver.

Each engagement follows the same decision path while adapting the scope to the business problem.

Discover

Establish context.

Business objective, current state, stakeholders, data, technology, risk, dependencies and existing providers.

Prioritize

Make the decisions clear.

Value, feasibility, risk, control needs, architecture options, sequencing and measures.

Deliver

Move the priority forward.

Advisory, training, design, implementation planning, specialist delivery and ongoing operations as required.

What you leave with

Clear decisions, documented next steps.

  • AI security and control findings
  • Shadow AI / approved-use priorities
  • Identity and data-protection actions
  • AI application / agent security requirements where relevant
  • Monitoring and incident-response priorities
Standards & guidance

Grounded in recognized frameworks and platform guidance.

We use relevant standards to organize risk, controls and evidence while keeping recommendations aligned to the organization and initiative.

NIST CSF 2.0NIST AI RMFOWASP guidanceISO/IEC 27001
Next step

Review your AI security posture.

We’ll help determine which existing controls can be extended first and where a genuine security gap may justify additional technology.

Get in touch →