Give AI deployment clear security ownership
ETT provides specialist security leadership for organizations introducing AI into business operations. Identify risks, define controls and give leadership a clear view of the decisions needed before and after deployment.
Who this service is for
CISOs and security leaders
Understand and manage the risks introduced by AI, LLMs and automated workflows.
CTOs and technology leaders
Oversee AI architecture, integrations, platforms and technical delivery.
Compliance and risk teams
Prepare for audits, regulatory reviews, AI policies or sector-specific compliance requirements.
CX and contact center leaders
Deploy voice AI, chat automation or customer-facing AI that handles sensitive interactions.
Executive and board stakeholders
Need clear visibility of AI risk, governance maturity and control priorities.
What you would be buying
Named security leadership for the AI work you are introducing, with the risks, controls and decisions written down and reviewed.
What you receive
- AI risk register covering the systems in scope
- Governance responsibilities: who decides what, and who is accountable
- Control priorities, sequenced against risk
- Review of data and integration boundaries
- Incident playbooks for the AI-specific failure modes
- Executive reporting at an agreed cadence
What you provide
- The AI systems and use cases in scope
- Existing security policy and control framework
- Access to the technology and risk owners
- Any regulatory obligations that apply to the deployment
How success is measured
- Risks identified, then accepted, mitigated or transferred, with the decision recorded
- Control coverage against the priorities agreed
- Time to close the issues raised
- Quality of the evidence available when a reviewer asks for it
ETT provides advisory leadership and helps you reach readiness and alignment. We do not award certification, we do not guarantee compliance, and an advisory engagement does not include unlimited incident response.
What can hold it up
- Access to the systems and the people who run them
- A decision-maker who can accept a risk on the organization's behalf
- Agreement on scope: which AI systems the engagement covers, and which it does not
After it goes live
The three support levels set out how much time and authority each engagement carries. Their exact review cadence, allocated advisory time, reporting and escalation rights are defined in the engagement letter before work begins.
Deliverables and measures describe the standard shape of this engagement. Exact scope, duration and commercial terms are agreed and confirmed in writing before work starts.
How we do the work
AI security risk assessment
We assess the security, privacy and operational risks connected to AI systems, LLMs, voice automation and agentic workflows.
AI governance framework
We help define policies, responsibilities, controls and decision-making structures for safe and accountable AI use.
LLM and prompt security
We assess risks such as prompt injection, output manipulation, hallucination, data leakage and model misuse.
Data classification and policy review
We review how sensitive data is identified, protected and governed before it is used in AI systems or automated workflows.
Compliance readiness
We help assess AI-related compliance considerations across frameworks such as GDPR, HIPAA, PCI-DSS, SOC 2, ISO alignment and sector-specific obligations.
Incident response and breach readiness
We help define response plans for AI-specific incidents, including model misuse, unsafe outputs, data exposure and compromised integrations.
Executive risk reporting
We provide clear reporting for leadership teams, helping boards and senior stakeholders understand AI risk, control maturity and priority actions.
Why this matters
AI changes the security conversation.
As LLMs, voice automation and AI agents become part of business operations, they create new risks around data exposure, model behavior, automated decision-making, customer interactions and system access.
Traditional cyber controls still matter, but they are not always enough on their own. AI systems can be vulnerable to prompt injection, output manipulation, hallucination, data leakage, insecure integrations and weak governance around model use.
ETT helps organizations address those risks before they become barriers to adoption. Our vCISO for AI service provides the security leadership, governance structure and practical oversight needed to scale AI with greater confidence.
Why AI needs specialist security oversight
AI systems do not simply store or process information. They interpret, generate, recommend, retrieve and, in some cases, trigger action. That makes oversight more complex.
A poorly governed AI system may surface sensitive information, produce inaccurate outputs, follow manipulated prompts or connect to workflows in ways the business has not properly controlled. Voice and conversational AI can introduce further risks around customer data, payment information, recordings, transcripts and regulated interactions.
Specialist AI security oversight helps organizations understand where those risks sit and what controls need to be in place: policy, governance, technical testing, incident planning, data protection, model risk management and executive visibility.
How much time and authority the engagement carries
Each level is defined in the engagement letter before work begins: the review cadence, the allocated advisory time, the reporting, and who can escalate what.
Teams preparing for AI deployment or reviewing early-stage AI use.
- AI security risk assessment
- Data classification and policy review
- Regulatory gap analysis
- Threat modeling for LLMs and voice AI
- AI use policy guidance
Teams operating AI, LLM or voice automation systems in production.
- Regular vCISO strategy sessions
- API and integration security review
- Prompt injection, manipulation and hallucination risk review
- Incident response playbooks
- Security scorecards and priority actions
Enterprise teams building AI into critical operations across multiple systems, regions or business units.
- Executive risk reporting
- Board-level briefings
- Data sovereignty advisory
- Model update and rollback governance
- Custom AI governance framework
- Ongoing AI security roadmap
AI-specific risk areas
LLM safety and output control
We assess how models generate, retrieve and present information, reducing the risk of unsafe, inaccurate or unsupported outputs.
Prompt injection and manipulation
We test and strengthen AI systems against malicious prompts, instruction manipulation and attempts to bypass intended controls.
Data leakage and privacy risk
We identify where sensitive data could be exposed through AI workflows, retrieval systems, voice interactions or connected applications.
Voice and payment security
For customer-facing automation, we assess risks around voice data, recordings, transcripts, payment flows and regulated interactions.
API and integration security
AI systems often rely on APIs and third-party connections. We review the security of those integration points before they become weak links.
Model governance
We help define how models are approved, updated, monitored, rolled back and reviewed over time.
AI incident response
We help prepare for AI-specific incidents that traditional breach playbooks may not fully cover.
Specialist add-ons
DPO-as-a-Service
Ongoing data protection officer support for organizations that need privacy leadership around AI, data use and regulated processing.
ISO 27001 alignment
Help aligning AI security controls, governance and documentation with ISO 27001 expectations.
AI red teaming
Structured adversarial testing of AI systems to probe prompts, outputs, integrations and failure modes before they reach production.
How we build security into AI deployment
Orient
We assess AI use cases, data flows, model behavior, integrations, compliance exposure and current security maturity.
Prove
We validate the control approach against a real AI workload, confirming risks are understood and mitigations work before scale.
Govern
We define the governance model, policy framework, control requirements, escalation routes and security architecture for safe AI use, aligned to standards such as ISO/IEC 42001.
Scale
We support the implementation of controls, testing, monitoring and incident-response processes around AI systems moving into live operation.
Compound
We provide ongoing oversight, reporting, review and improvement so AI security keeps pace with changing models, workflows and risks.
Often delivered alongside
Timing, cost, access and ownership
How long does this take?
Advisory engagements run over a period rather than to a delivery date. The support level sets the review cadence, the allocated advisory time and the reporting rhythm, and those are fixed in the engagement letter before work begins.
What drives the cost?
The support level, the number of AI systems in scope, and the regulatory obligations that apply. An engagement covering one internal workflow is a different proposition from one covering a customer-facing deployment in a regulated market.
What access do you need?
The AI systems and use cases in scope, your existing security policy and control framework, and time with the technology and risk owners.
Do you certify us, or guarantee compliance?
No. We provide advisory leadership and help you reach readiness and alignment. Certification is awarded by an accredited body, not by ETT, and no advisory engagement can guarantee a compliance outcome. Any commitment on incident response is defined and bounded in the engagement letter rather than implied.
What happens next?
A conversation about the specific process or decision you have in mind. If there is a workable opportunity we will describe a scoped first engagement; if there is not, we will say so and explain why. Requesting a session does not commit you to anything.
About this service
What is a vCISO for AI?
A vCISO for AI provides specialist security and governance leadership for organizations deploying AI, LLMs, voice automation or agentic systems. The role helps assess risk, define controls and support safe adoption.
Why does AI need specialist security oversight?
AI systems introduce risks around prompts, model outputs, sensitive data, integrations, automated workflows and governance. These often require controls beyond traditional cybersecurity measures.
What is prompt injection testing?
Testing whether an AI system can be manipulated through malicious or unexpected instructions. It helps identify weaknesses in how the system follows prompts, accesses information or performs actions.
How does vCISO for AI support compliance?
It can help review AI use against relevant requirements, policies and frameworks such as GDPR, HIPAA, PCI-DSS, SOC 2, ISO alignment and sector-specific obligations.
Does AI governance slow innovation down?
Good governance should support adoption by creating clearer rules, controls and accountability. It helps organizations scale AI with more confidence rather than blocking progress.
Can your AI systems scale with trust?
Request an AI session to explore the security, governance and compliance controls needed to deploy AI, LLMs and automation safely across your organization.
Around four minutes. Indicative guidance based on your answers.