Artificial Intelligence Today: Managing Risk, Access and Compliance Without Clear Industry Standards*

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Artificial intelligence is being deployed faster than the rules governing it are being written. In the absence of clear, uniform industry standards, organizations are making high-stakes decisions around access, control, compliance, licensing and liability with incomplete guidance and evolving regulatory pressure. The result is uneven risk exposure, fragmented governance, and contractual and compliance frameworks that are often backward-looking.

This panel examines how organizations are managing AI risk in real time—while continuing to deploy and scale AI across core business functions. Panelists will discuss practical approaches to governing access to models and data, allocating responsibility for AI-driven outcomes, and building compliance programs that can adapt as regulatory expectations emerge at the federal, state, and international levels.

The conversation will address issues including data rights and provenance, model transparency, bias and accountability, auditability, third-party risk, maintaining core business assets that must remain secret, and the growing role of contracts as de facto standards. Panelists will also explore how companies can avoid over-engineering controls that slow innovation while still maintaining defensible positions with regulators, partners, and investors.

Materials

The AI Ethics Waterfall: Disclosure, Governance, and Who’s Really Responsible
U.S. Chamber Report: Small Businesses Rapidly Adopting AI Despite Regulatory Concerns
Eight Tips for Navigating the Complex World of AI Licensing
Where Trade Secrets and Data Privacy Strategies Overlap
Strategies for Licensing Software that Leverages Artificial Intelligence

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Source

Artificial Intelligence Today: Managing Risk, Access and Compliance Without Clear Industry Standards* – IPWatchdog.com