For companies in healthcare and other regulated industries, improving data quality and defining access rights are critical steps to meeting performance, privacy, and safety standards, says Sunil Venkataram, head of product at Wellframe, a HealthEdge company. “Organizations should leverage leading practices, tools, and trusted partners for data validation, auditing, monitoring, and reporting, as well as for detecting and mitigating potential biases, errors, or misuse of AI-generated data.”
One of the key areas to address with employees is specifying what AI tools they can use in workflow, research, and experimentation. In addition to identifying the tools, a strong AI governance policy should specify what capabilities to use, what functions to avoid, who in the organization can use them, and what business processes should avoid using AI.
CIOs aim to standardize AI tools and avoid shadow IT, costly tool proliferation, and additional risk when employees share company data in tools without contracts defining the required data security. Policies should also define a process to enable employees to recommend new tools and capabilities for evaluation.
