Six steps to deploy in establishing AI governance

Good article from IBM watsonx providing C-suite perspective as well as steps to establish robust AI governance practice inside an enterprise inspired me to share some thoughts of my own. The three steps outlined in this article are:

1. Build the foundation for AI oversight by assessing the organization's AI maturity and defining goals.

2. Document your ethics by codifying enterprise-wide ethics and values around AI.

3. Adapt existing governance structures for AI by incorporating AI governance 

into current practices. AI governance is an ongoing process that requires adaptation and evolution to meet changing needs.

A few points of my own:

➡ Organizations that are implementing AI governance now are in a great position to gain a competitive edge by establishing trust early on with their users, employees and customers, mitigating risk (reputational and regulatory) and ultimately maturing their AI adoption. 

➡ Leadership commitment (sponsorship) in AI governance is a critical factor to AI governance implementation across an enterprise. 

➡ Establish human oversight to ensure AI systems are performing as expected, especially in AI auditing and accountability processes for which there's no mature AI framework that details the sub-processes for monitoring and auditing AI systems. 

I will expand a little more how to best tackle AI governance implementation in an upcoming blog. Stay tuned.