Artificial intelligence is advancing faster than the frameworks surrounding it. Between Quebec’s Bill 25, the European Union’s AI Act, and international standards like the NIST AI Risk Management Framework and ISO/IEC 42001, organizations adopting AI without a governance structure expose themselves to real risks: privacy breaches, undetected biases, decisions made without clear accountability, and loss of intellectual property.
We provide a framework for AI adoption to ensure it remains responsible and compliant, without hindering your teams’ momentum. In concrete terms, this translates into an internal AI policy tailored to your specific situation, the establishment of an AI governance committee (mandate, composition, arbitration mechanisms), a registry of your use cases, and a mapping of the legal and regulatory context specific to your sector.
This framework is not a theoretical exercise that ends up buried in some obscure corner of your intranet. It is linked to your actual decisions: which tools to adopt, what data can circulate, who is responsible for what, and how to react when usage deviates from the intended framework. It is also a mechanism for evaluating the performance and impact of your tools, developing a community of practice, a feedback mechanism, and a communication and deployment plan.
Good governance isn’t a hindrance. It becomes the catalyst for trust, enabling your teams to move faster and with full legitimacy in the eyes of your clients, partners, and board of directors.
This work often follows naturally from a strategic workshop, where initial governance observations already emerge. It can also be undertaken as a standalone project for organizations already actively using AI and now required to be accountable to a board of directors, clients, or regulators.
Need a robust and actionable AI governance framework, rather than a document gathering dust in some obscure corner? Let’s discuss your obligations and risks.
