Navigating Legal Risk and Data Governance in the AI-Driven Business World

According to an article on the Stoel Rives website, as data becomes a core commercial asset, companies are confronting a complex landscape involving legal risk and data governance.

The increasing reliance on data-driven systems and AI technologies has created many opportunities, but it also amplifies exposure to privacy, intellectual property, and contractual liability risks.

Companies that manage or process data must now adopt compliance strategies that take into account privacy laws, data ownership, and ethical considerations.

These strategies for dealing with legal risk and data governance should be implemented concurrently with the initiation of data collection and use. The foundational stage of data creation involves both legal and ethical obligations.

Collectors must obtain informed consent when handling personal information, comply with regulations such as GDPR and HIPAA, and, where possible, de-identify data.

Ethical diligence encompasses respecting intellectual property rights and mitigating bias risks in training datasets. Establishing review processes to detect and mitigate discriminatory or skewed data ensures model reliability and limits future legal exposure.

When purchasing or licensing third-party data sets, the terms of the agreement become central to risk management. Parties must clarify ownership of derivative data, define the scope of the license, confirm warranties regarding data provenance, and negotiate liability caps and indemnities for potential breaches or infringements.

Cybersecurity measures, privacy compliance, and post-termination data rights are equally critical components of a sound contract framework. Lawyers should ensure compliance with applicable privacy laws, review license and source terms, and implement governance procedures for data vetting.