Between 2023-25, venture capital funding for artificial-intelligence (AI) companies surged well into the billions. This investment has produced two distinct categories of companies that could be vulnerable to bankruptcy: (1) those AI-washing (inflating AI capabilities to attract investment); and (2) businesses with operational dependencies on AI infrastructure, but perhaps without full ownership or control. While many responsible AI companies work tirelessly to advance technology, with more entrants to the market, more AI-involved bankruptcies are likely as new business models emerge in the era of advanced AI and decentralized frameworks — the fourth Internet evolution.

When capital markets tighten and performance expectations sharpen, both company types face heightened restructuring risk. For bankruptcy practitioners, this convergence presents novel challenges. How do you value training datasets with contractual restrictions? What happens when a debtor’s primary asset is access to a third-party model governed by anti-assignment clauses? Can a debtor-in-possession (DIP) monetize AI infrastructure built on licensing arrangements?

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