With AI rapidly evolving, organisations looking to deploy AI and automation technologies within their business must consider the safety, security and governance of these new tools. Business and technology leaders must address the governance of AI within their own business, to monitor and manage AI activities, including AI model documentation and auditing pipelines to show how AI is trained and tested before it is deployed.

AI governance is increasingly important across a range of industries, but particularly within heavily regulated sectors, such as banking and financial services, insurance and healthcare. All organisations should be completely transparent with their use of AI models. To limit risk, auditability must be well documented so businesses avoid penalties and can expand on their capabilities in the future.

There are a range of different techniques of AI governance to ensure the secure and effective development and implementation of AI technologies. Whilst transparency is vital, businesses must also adopt ethical guidelines to outline how AI will be utilised within a business. Rules of behaviour must include informed consent, privacy protection, bias mitigation, responsible content generation, regular audits and stakeholder collaboration.

Alongside these actions, it is pertinent for businesses to create a robust enterprise data governance plan to train all AI models within the same environment, as well as understand the legal frameworks of AI. Businesses must continue to stay abreast of the latest AI regulations to ensure they conform with any future rules set in place by a governing body. 

The governance of AI is everyone’s responsibility within a business, so having a set of cohesive guidelines to follow will ensure regulatory compliance, security and adherence to your organization’s values. Ultimately, AI leadership will be the guiding beacon for AI governance.