AI Company Bankruptcies: Navigating Ownership, Valuation, Licensing, and Other Unique Complexities
Property of the Estate, Assumption and Assignment of Executory Contracts, Licensee Protections, Section 363 Sales
About the Course
Introduction
This CLE webinar will discuss key issues in AI company bankruptcies such as identifying property of the estate, assumption and assignment of executory contracts under Bankruptcy Code Section 365, licensee protections, and Section 363 sales that counsel should consider when representing investors, customers, lenders, debtors, or potential purchasers of AI assets.
Description
Although AI company valuations are at historic highs, these valuations may be difficult to approximate if the company files bankruptcy. Factors to consider include the typical drop after filing, the complexity of the assets, fragmented ownership, data privacy considerations, and potential post-sale liability.
Counsel should be aware that unlike the assets of traditional technology companies, AI companies have interconnected and "integrated systems" that "challenge traditional concepts of property and transferability," valuation, and monetization. The debtor usually does not "own" anything but uses IP and other rights under contract with third parties. The terms of those contracts and licenses determine if rights can be assumed and assigned, and if they cannot, they may have little value.
Even if assets can be sold, privacy and other laws may limit a buyer's ability to use the data, making a purchase risky. While the sale of structured data might be attractive, the risk of unknowingly transferring privileged, confidential, or proprietary data could result in third-party liability.
Listen as our panel of esteemed AI and bankruptcy practitioners discusses evaluating AI assets, executory contracts involving AI companies, licensee protections, and Section 363 sales of AI data and assets.
Presented By
Mr. Ewing represents clients in complex and high-profile cybersecurity, privacy, blockchain, artificial intelligence, and other technology-related litigation and arbitration matters with a focus on resolving disputes as early as possible through a mix of practical legal acumen and technical fluency. A diligent counselor, he also guides strategic business operations and best practices, developing sophisticated cybersecurity policies, privacy compliance programs, licensing frameworks, and technology contracts. With clients ranging from Fortune 100 companies to non‑U.S. sovereigns to small businesses and individuals, Mr. Ewing has served as a strong and agile representative before diverse national and international legal venues. These include the International Trade Commission and the International Centre for Settlement of Investment Disputes, in addition to U.S. courts and arbitration tribunals.
Mr. Holley is a dedicated business attorney representing creditors, receivers, trustees, and other clients in bankruptcy, restructuring, and non-bankruptcy insolvency matters. He has a strong background in commercial litigation, adeptly handling legal matters related to business transactions, contracts, and commercial disputes. Mr. Holley also has experience representing clients in matters before Nevada administrative agencies, including the Nevada Board of Pharmacy.
Mr. Kissner's primary practice is advising clients with respect to novel and complex insolvency issues, with a particular focus on cross-border and governmental restructurings. He has represented debtors, ad hoc groups, official committees, and individual investors in large chapter 11 and chapter 15 filings, including matters involving digital assets and digital asset companies, as well as disputes and litigation arising from M&A, venture capital and financing transactions in the blockchain and digital asset sector. Mr. Kissner is also currently a member of the International Insolvency Institute’s NextGen Leadership Program.
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This 90-minute webinar is eligible in most states for 1.5 CLE credits.
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Date + Time
- event
Tuesday, October 27, 2026
- schedule
1:00 PM ET/10:00 AM PT
I. Reason AI companies are in distress
II. Identifying which AI assets are property of the estate under Section 341
III. Section 365 assumption and assignment of contracts
A. Protectable IP: 365(c)
B. When debtor is licensor: 365(n)
IV. Section 363 asset sales
A. Valuation drivers
B. Training data
C. Large language models
D. Unstructured data
E. Consumer privacy obligations under the Bankruptcy Code (363(b), 332)
F. State and other data privacy obligations (e.g., California Consumer Privacy Act, GDPR)
G. Concerns with unstructured data: privileged, confidential information, trade secrets
H. Limitations on "free and clear" transfers; successor liability
V. Plan confirmation and valuation challenges
The panel will discuss these and other important issues:
- What is causing the increase in AI company distress?
- What constitutes AI assets in a bankruptcy estate, and how can they be monetized?
- What are the challenges of selling a trained LLM? Unstructured data?
- What are best strategies for dealing with a consumer privacy ombudsman?
- What are the most important terms in licensing agreements governing access to training data?
- How might an AI company structure its privacy policies to allow maximum flexibility in the event of insolvency?
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