Using AI tools like Midjourney or DALL·E to create business content doesn’t guarantee ownership. IP laws hinge on tool terms, not just creation. Risks include licensing disputes, takedowns, and infringement claims. Companies must check terms of service, avoid style mimicry, and prove rights to use content. Using AI prompts for legal review is helpful, but always confirm with counsel. Treat AI content as real IP to safeguard your brand as it scales.

AI agents that mimic real people—digital replicas—raise major legal issues, including rights of publicity, copyright, and consent. U.S. laws vary by state, and consent alone isn’t enough to avoid risk. EU and global regulations are emerging, adding complexity. Brands must secure clear licenses, define usage, manage outputs, and ensure transparency. Legal strategy isn’t optional—it's essential to protect trust, reputation, and avoid costly liabilities in this fast-evolving space.

AI is transforming how businesses use data, raising new legal and licensing challenges. Traditional licenses often lack clarity on machine use, exposing risks. Companies must assess their data flows, clarify rights for machine learning, and implement use-based frameworks addressing AI training, output rights, ethics, and traceability. Updating data licenses is essential for responsible, scalable innovation in the AI era.

Explore how AI is reshaping innovation incentives and challenging traditional IP frameworks. WIPO's Economic Research Working Paper No. 77 offers an economic perspective on AI's impact on intellectual property. Essential reading for AI entrepreneurs and IP professionals.

Examines the increasing concern over deepfakes and the legislative efforts at both federal and state levels to address the challenges they pose. It discusses various proposed and enacted regulations aimed at mitigating the risks associated with deepfake technology which of course includes AI.

Offers an in-depth examination of how artificial intelligence is evolving and its implications for the legal profession. It addresses questions about legal accountability when machines make autonomous decisions with financial consequences and explores how laws are adapting to these new realities. This guide is essential for understanding the intersection of AI and law.