AI Governance – Framework and best Practices

In the early 2010s, Artificial Intelligence (AI) adoption surged across a myriad of industries and sectors. With its increasing integration, there is also an increasing need for proper governance of AI systems to reap the benefits and manage the risks.

Governance — encompasses “the combination of processes, principles, structures and relational mechanisms implemented by the governing body in order to inform, direct, evaluate and monitor the activities of the organisation toward the achievement of its objectives”.

AI governance encompasses oversight mechanisms that address risks like bias, privacy infringement and misuse while fostering innovation and trust. AI governance seeks to facilitate constructive use of AI technologies while protecting user rights and preventing harm.

Some academics suggest that AI governance be a subset of corporate, IT and data governance (since AI depends on data) that helps align the use of AI technologies with organisational strategies and legal and ethical requirements coming from the operating environment. King IV makes it clear that governing IT and data is a governing body responsibility.

How to start building your own AI Governance Framework

A governance framework has become an essential for modern governance and legal operations. A strong governance framework organises operational, risk management,

reporting and financial processes to ensure the governing is continually updated.

As per the academic’s recommendations, an AI governance framework should also be part of an IT and data governance framework that is deployed using a mixture of various structures, processes and relational mechanisms.

Structures are responsible for defining roles and responsibilities. Committees are an example of those structures composed of directors, managers and executives, in other words, people responsible for decision-making in the organisation.

Processes refer to the formalisation and institutionalisation planning and strategic decision making of AI monitoring based on good practice including techniques and appropriate tools to align business and AI for a good performance.

Relational mechanisms are all about two-way communication and a good participation/collaboration relationship between the business and IT for attaining and sustaining business/AI alignment.

By implementing a formal framework, organisations strengthen decision-making, accountability and risk management. With an effective governance framework, organisations define standard policies and procedures, and establish mechanisms to monitor and control activities. Because a governance framework is a flexible methodology, it is best customised to meet the unique needs of a specific industry.

What are the best practices for implementing an IT governance framework?

• Clearly define business goals and objectives. Before you implement an IT governance framework, make sure that the organisation’s business objectives and goals are clearly defined. This includes identifying key priorities, determining desired outcomes, and selecting a way to measure success.

• Involve key stakeholders. Engage with your key stakeholders in both thedevelopment and the implementation of the AI governance framework, ensuring that the framework captures all requirements and gains buy-in from those impacted.

• One size does not fit all. Approach the implementation and planning process with an innovative approach to find the best solution for your organisation’s unique needs.

• Set Key Performance Indicators (KPIs). Define and establish relevant KPIs to measure and monitor the performance and efficacy of an AI governance framework. When setting KPIs, ensure that these align with the company’s overall business goals and objectives. Make time to regularly measure and report on these KPIs at least monthly— identifying new possibilities for improvement and demonstrating the overall value of AI governance.

• Review and update. Building an AI governance framework and approach is an evolving process. As organisations grows and changes, the AI governance framework should shift as well. Set time to regularly review and update the framework each year to ensure alignment with new innovations in technology, business requirements, and industry standards.

Parting Shorts

With an effective AI Governance Framework, organisations can establish clear lines of responsibility, define standard policies and procedures, and mechanisms to monitor and control AI activities. AI Governance Frameworks can—and should—be tailored and customised to meet the specific needs of your clients.

Clear and unambiguous definitions of the roles and responsibilities of the involved parties are a crucial prerequisite for an effective AI Governance framework. It is the responsibility of the governing body to make sure that they are clearly understood throughout the whole organisation.

There is no one size fits all, feel free to share your thoughts on an  AI Governance Framework as well as good practices that could be considered.