AI security services in Dubai, UAE
Our AI security services identify the AI tools in use across your organisation, agree with you which are approved, restricted or blocked, and inspect what is sent to public AI services so that company data does not leave in a prompt.
What AI security gives you
The service provides four outcomes. The fourth is the record that the first three were completed.
AI tools are often in use before a policy exists
Public AI tools are available through any browser, so staff can begin using them without a procurement decision. A document pasted into a chatbot for summarising is a common example.
Data entered in this way does not appear in any procurement record. It is held by a service the organisation has no contract with, under terms that have not been reviewed, and it cannot be recalled.
The service addresses this by identifying what is in use, providing a sanctioned tool that meets the need, and inspecting what is sent to the services that are not approved.
AI security services we deliver
Engagements begin with discovery, so that the policy decision is made on a list of the tools in use.
AI application discovery
Which AI services are in use, by which departments and at what volume, established from network and identity telemetry.
Risk assessment per tool
What each service does with the data it receives, where the data is processed, and what its terms allow, assessed for each tool individually.
Data exposure review
What has already been sent to AI services, so that the existing exposure is understood before a new policy is written.
Embedded AI review
The assistants inside software you already own, which inherit user permissions and can return the contents of an over-shared folder.
Access control and policy enforcement
Which people may use which tools, granted by role through your identity provider so that access can be reviewed and revoked.
Data loss prevention for AI
Inspection of what is sent to public AI services, with the categories you define blocked and the rest allowed.
Sanctioned tooling
A small approved set of tools with enterprise terms and tenant controls, so that staff have an approved route for their work.
Permission remediation
Over-broad sharing is corrected before an assistant is enabled, because the assistant will return whatever the user can already reach.
AI application testing
Prompt injection, insecure output handling and data exposure through retrieval, tested against the running application.
Tool and agent permissions
What an AI agent is allowed to call and with whose authority, which determines the damage a single error can cause.
Model supply chain review
Where models, plugins and extensions come from, and what they are permitted to reach once installed.
Vulnerability management
The infrastructure the AI stack runs on, kept in the same patch and remediation cycle as the rest of the estate.
User behaviour monitoring and coaching
A policy trigger produces a short explanation to the user at the time it happens, together with the name of the sanctioned alternative.
Responsible AI training
What staff may use, what must never be entered into a public tool, and why, delivered in the terms of their own work.
Reporting and compliance auditing
Usage, blocks and exceptions reported monthly, in a form that supports the decision about what to allow next.
Policy review
The approved list is reviewed on a set cycle as new tools appear and existing tools change their terms.
Why choose iConnect for AI security
The list comes before the policy
Discovery is the first step, so that the decision about what to allow is made on the tools in use.
A ban is not the default recommendation
Blocking every tool can move the work to personal devices, where the organisation has no visibility. A sanctioned route with controls is recommended instead.
Embedded AI is included
Copilot and in-app assistants inherit user permissions. Sharing is reviewed and corrected before the feature is switched on.
Applications you build are tested
Prompt injection and over-permissive agent access are tested against the running application as well as reviewed at the design stage.
Calibration before enforcement
Policy is tuned in monitor mode first, so that the switch to blocking does not generate a large number of service desk requests.
Mapped to existing obligations
The PDPL and your sector rules already apply to AI use. Controls are mapped to those frameworks instead of to a separate AI standard.
How an AI security rollout runs
What is in use is established from telemetry, which is more complete than a survey.
- Network and identity telemetry reviewed for AI service traffic
- Usage attributed to departments, so that each business unit sees its own figures
- Embedded AI features in existing software inventoried alongside the standalone tools
Each tool is assessed on what it does with the data it receives.
- Processing location and retention read from the terms that apply to your account and plan
- Use of submitted data for model training established per service and per plan
- A recommended position on each tool: approve, restrict or block
The approved set is agreed with the business units, so that the policy reflects how the tools are used.
- A small sanctioned set with enterprise terms and tenant controls
- Access mapped to roles in your identity provider so that it can be reviewed
- A written position that staff can read in a few minutes
Inspection runs without blocking first, so that the rules are tested against real traffic before anyone is stopped by them.
- Data categories defined for your business
- False positives removed from the rules before enforcement begins
- Permissions and sharing corrected before in-app assistants are enabled
Blocking is switched on in phases, with an explanation shown to the user at the time of the block.
- High-risk categories enforced first, the rest staged behind them
- Users prompted at the time of the block, with a sanctioned alternative named
- An exception route that is documented and used, so that the policy is not bypassed
The approved list and the rules are reviewed on a set cycle, as the tools change frequently.
- New services appearing in discovery assessed as they appear
- Repeat policy triggers examined as a process issue and addressed with the department
- Reporting written for the decision about what to allow next
Where AI security meets UAE obligations
There is no single UAE AI statute yet. Data protection law already applies, and entering personal data into an AI service is processing in the same way as any other.
UAE Personal Data Protection Law
Federal Decree-Law No. 45 of 2021 governs the processing of personal data. Sending it to an AI service is processing, and the lawful basis, transfer and retention requirements apply.
DIFC and ADGM
Entities in the financial free zones are subject to their own data protection regimes, with their own rules on automated processing and cross-border transfer.
Sector regulators
The Central Bank and the health authorities set requirements on outsourcing, confidentiality and where regulated data may be processed, and an AI service is treated as a processor.
ISO/IEC 42001
The management system standard for artificial intelligence, which provides a certifiable structure for organisations that need to evidence AI governance.
Sectors we secure AI for
What may be entered into a public model differs by sector, and so does the consequence of an error.
Government
Public records and citizen data, with residency requirements that determine what is permitted.
Banking and Finance
Client confidentiality and regulator requirements on outsourced processing.
Healthcare
Patient data that cannot be sent to a general service, and clinical staff who need approved tools.
Manufacturing
Designs and process knowledge that are the core of the business.
Retail and E-commerce
Customer records and pricing, with AI features embedded across marketing platforms.
Education
Student data and rapid adoption of AI tools by students and staff.
What our clients say
“Whenever an issue arises, iConnect is there immediately: quick, efficient and proactive in keeping everything running without disruptions. iConnect has become a crucial part of our operations.”
Head of IT Infrastructure and Network SecurityDragon OilAI security questions
Shadow AI is any AI tool used in the business that IT has not approved and cannot see. It matters because data entered into such a tool leaves the organisation's control at that point. Blocking every tool is not the usual recommendation, because the work still needs to be done and staff may use unmanaged alternatives. Identifying what is in use is the first step to allowing it under controls.
Yes. Traffic to public AI services can be inspected and the data categories you define can be blocked, in the same way data loss prevention works for email and file sharing. The rules are calibrated in monitor mode first, so that legitimate work is not blocked and staff are not driven to unmanaged alternatives.
No. The recommended position is a small set of approved tools with enterprise terms, access granted by role, and monitoring of what is sent to them. This gives staff a sanctioned route that meets their needs, and it keeps the data under contract terms the organisation has reviewed.
There is no single AI statute yet. What already applies is the Personal Data Protection Law, the DIFC and ADGM data protection regimes for entities in those free zones, and sector rules from the Central Bank and the health authorities. Entering personal data into an AI service is processing, and the existing obligations apply to it. ISO/IEC 42001 provides a certifiable management system for organisations that want one.
Copilot in Microsoft 365, assistants inside a CRM, and summarisation in a support platform each inherit the permissions of the user, so an over-permissive file share becomes content the assistant can return. Permissions and sharing are reviewed and corrected before those features are switched on.
Applications you build need testing as well as policy. Prompt injection, insecure output handling, data exposure through retrieval and over-permissive tool access are tested against the running application. The OWASP Top 10 for large language model applications is used as the starting scope.
Which tools are in use and by which departments, which data categories were blocked and how often, which users repeatedly trigger policy, and how these figures change month to month. The report is written to support the decision about which tools to allow next.
Discovery and a risk assessment are scoped at two to three weeks and produce a list of tools in use, the data being sent to them, and a recommended position on each. Enforcement follows in phases, with rules run in monitor mode first, so that a full policy set is not switched on in one step.
Talk to our team about your requirement
We’re happy to answer any questions you may have and help you determine which of our services best fit your needs.
Our Value Proposition
- Tailored Solutions for Your Organization
- Unbiased Expertise
- Proven IT Competence
- Outcome-Driven Approach
- Proactive Problem-Solving
- Transparent Processes
What happens next?
We’ll arrange a call at your convenience.
We do a discovery and consulting meeting
We’ll prepare a detailed proposal tailored to your requirements.