Trustworthy AI Strategy and Governance Framework

In this infographic, we review a framework to show how to extend your organization’s existing Strategy and Governance structures and frameworks to address the specific requirements of Artificial Intelligence regulations, rules, laws and standards as well as AI Products.

At the strategic level, organizations should consider how AI principles can support and enhance their go-to-market strategy. This involves creating a vision and mission, developing a strategic direction, and optimizing the return on investments (ROI). From a governance perspective, the focus is on providing oversight, allocating resources to optimize value, and managing risks. A key element at this level is tying AI strategy and AI governance together.

The tactical level focuses on individual business units and AI initiatives. This includes creating AI roadmaps, securing funding, and setting key performance indicators (KPIs). Governance at this level involves determining the right methodologies, policies, and practices for each AI initiative and assigning accountability to teams.

The operational level is about integrating AI into daily operations. This involves incorporating AI topics into IT architecture steering and working groups and approving AI evaluations and deployments to ensure alignment with strategy and KPIs. Governance at this level requires monitoring AI initiatives and implementing controls to ensure compliance and minimize risks such as data privacy infringements, security issues, drift, and hallucinations.

AI Centre of Excellence (COE) can be used by all teams to accelerate AI adoption. A COE helps gather lessons learned and apply common methods in change management, allowing teams to understand priorities, requirements, and best practices for deployment and maintenance. It can also revise AI principles to enhance security and minimize threats like theft and adversarial inputs.