Adopt AI safely
Most organisations can benefit from incorporating AI solutions to increase productivity. However, AI also introduces several risks, such as the exposure of sensitive data. At AI STRIDER, our mission is to help organisations find the right balance between AI-driven productivity and data security, enabling you to avoid data breaches that could harm your reputation and result in significant fines.
Securing your AI Journey
Whether you have already embarked on your AI journey or are about to start with AI we can provide appropriate services to ensure safety and align your AI solutions with important regulations and standards.
Known AI Security Needs
Recent surveys have shown that over 40% of organisations need to:
- Prevent sensitive data from being uploaded to AI
- Log all activities in AI tools for investigations or incident response
- Block user access to unauthorised AI tools
- Train employees on secure AI tool use
- Identify risky users based on queries into AI
But this is not yet happening. Many of these organisations need help.
AI Governance Frameworks and AI Regulations
There are now several AI Governance Frameworks available and various emerging AI Regulations to consider.
01
NIST AI RMF
The NIST AI Risk Management Framework is good place to start with AI governance. This framework includes 72 controls across four domains; Govern, Map, Measure, Manage; to provide a comprehensive framework to secure AI solutions.
02
The EU AI Act
To comply with the EU AI Act organisations need to address numerous technical, human and ethical issues.
03
ISO/IEC 42001
This standard is specifically intended to provide direction for those seeking to strike the balance between rapid AI adoption and secure AI.
04
MITRE ATLAS
This is a valuable insight into the Adversarial Threat Landscape for Artificial-Intelligence Systems (ATLAS). It documents 115 AI system attack vectors whilst suggesting 26 mitigations.
05
The AI Strider Framework for Microsoft Copilot adoption
We provide a highly pragmatic Microsoft Copilot and AI adoption approach secured via Microsoft Purview.
Data Governance Frameworks
The most effective AI Agents and productivity solutions are grounded on your unified enterprise data.
Significant data governance is required in order to achieve accuracy and to avoid inappropriate disclosure of sensitive data.
Below are some of the key Data Governance reference frameworks available.
01
DAMA DMBOK
A popular data governance framework from the Data Administration Management Association. For more details see: internal://cf7a02c4-cdf2-4efd-9527-e62baf3163e7
02
Microsoft Cloud Adoption Framework for a unified Data Platform
Microsoft publish an adoption framework for a unified data platform based on the Microsoft Fabric OneLake and enhanced with AI and analytics. For more details see: internal://cf7a02c4-cdf2-4efd-9527-e62baf3163e7
03
AI Strider Data Governance Framework
We have devised a highly pragmatic data governance framework to enable the safe & secure adoption of AI grounded on your data. It is based around Microsoft Fabric using Microsoft Purview and adapted from the Microsoft Adoption Framework. For more details see: internal://cf7a02c4-cdf2-4efd-9527-e62baf3163e7
Regulatory compliance
GDPR Fines for serious data breaches, which could be related to the use of insecure AI tools, is up to £17.5 million or up to 4% of global turnover.
Non-compliance with the EU AI Act could cost organisations up to 35 million EUR or 7% of global turnover.
This should provide an incentive to organisations to get their AI house in order - so to speak.
Does your organisation need assistance with AI Security ?
Consider your organisation's requirements carefully and get in contact with us if you wish to discuss how we might be able to assist your on your safe AI journey.