M&A in the AI sector is redefining deal risk, especially when sensitive data is involved. As AI companies power breakthroughs in biotech, healthcare, defense, and critical infrastructure, the stakes for companies acquiring businesses handling proprietary data, biotech research, medical records, trade secrets, critical technology or government intelligence have never been higher. In an era where a single data breach or compliance failure can derail innovation and shatter market trust, due diligence has evolved from a legal checkpoint to a mission-critical strategy for safeguarding value in a rapidly disrupting landscape.

Government Contracts and Defense

AI companies servicing defense sector clients with government contracts must rigorously evaluate their obligations under regulations such as the International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR). It’s vital to examine transactions that may affect critical infrastructure or defense for clearance by the Committee on Foreign Investment in the United States (CFIUS). A prospective buyer’s due diligence process should include thorough analysis of customer contracts and internal compliance, especially in cross-border sales involving national security concerns, to ensure compliance with vital regulatory requirements.

Biotech Research

In biotech research, AI plays a crucial role in analyzing large datasets like genomic and clinical data, with predictive models aiding drug discovery. The data used in this research must adhere to the U.S. Food and Drug Administration (FDA) guidelines on data integrity, encompassing ethical standards, study validity, and accuracy. Detailed due diligence by a prospective buyer of adherence to these guidelines is imperative to adhere to regulations, ensuring companies advance innovation responsibly in the biotech sector.

Data Protection and Privacy

A top priority when assessing AI companies dealing with sensitive information is compliance with data protection regulations for both customer data and user data. Due diligence should thoroughly examine how companies structure policies to ensure adherence to regulations such as the Health Insurance Portability and Accountability Act (HIPAA) for medical data, the General Data Protection Regulation (GDPR) for EU-based data, and the California Privacy Rights Act (CPRA) for California user data. These evaluations safeguard sensitive information while bolstering trust in partnerships and operations.

Technological and Security Assessments

Robust cybersecurity measures are essential for AI companies to safeguard sensitive data against breaches. Due diligence should entail examining security protocols, vulnerability management strategies, and incident response plans, and evaluating technologies like encryption and secure coding practices. Ensuring an organization is equipped against cyber threats protects its most valuable assets. AI companies also need to be mindful of maintaining confidentiality standards of their proprietary IP when collaborating with government bodies or during regulatory reviews relating to their industry sector. Buyers will review those arrangements to evaluate whether a potential target has allowed for unintended disclosures of its proprietary algorithms. 

Conclusion

The M&A landscape for AI companies managing sensitive data demands comprehensive due diligence across regulatory compliance, intellectual property protection, foreign investments, and cybersecurity. A thorough evaluation of these facets enables informed decision-making, securing sensitive information and aligning strategies in the rapidly evolving AI sector. An AI company undergoing a sale or seeking opportunities should act deliberately to strengthen its position in the above areas.

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Tiernan Still also contributed to this article.