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The ATHENA Framework: AN Objectively Grounded Approach to AI Risk Management

ATHENA Strategic AI Risk Intelligence Framework provides SMEs with an objectively grounded assessment tool to identify and help SME mitigate critical AI-related risks. The development of this tool has been rigorously researched and developed in an unbiased way. By leveraging our framework, clients can proactively address potential negative exposure. The tool is developed specifically for SME and grounded for many sectors, including manufacturing, construction, financial services, technology, education, retail and others. The framework is aligned to the National Institute of Standards and Technology NIST, the International Organisation of Standardisation ISO, but is a comprehensive development of what we consider to be the most fundamental risks relevant to small business and where, if managed proactively, small business can significantly reduce potential risks of financial loss, fines, reputational damage, and ethical and environmental impact risks. Click on the link to book the package that suits your business and your business budget. Book a Package

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COMPLIANCE

Through our risk management strategy we strive to be an ethical business, focusing on ethical and societal impact as well as adopting an Environmental, Social, and Governance (ESG) strategy. Review our ESG activity.

We prioritise the development of AI systems that align with the highest standards of ethics, responsibility, and regulatory compliance. We take cognisance of the UK’s key regulations, including UK GDPR through the Information Commissioner’s Office (ICO), Data Protection Act 2018, and Network and Information Systems Regulations 2024 (NIST), as well as industry guidelines such as those provided by the British Standards Institution and National Cyber Security Centre (NCSC) and others. As we continue to evolve our AI risk management strategy, we embed these regulatory frameworks principles at its core, ensuring that our work not only adheres to, but also anticipates emerging needs in this dynamic field.