The landscape of mergers and acquisitions (M&A) in the Artificial Intelligence (AI) sector is poised for significant growth as the technology and its ecosystem continue to mature. This growth brings with it a unique set of legal and regulatory challenges that must be carefully managed.

With the rapid development of AI and its position as one of the most profitable investments for venture capital, the market expects continued growth in M&A activities within this field. The transformative potential of AI across various industries has attracted substantial investment from technology giants and venture capitalists. As AI companies strive to consolidate and strengthen their market positions, we anticipate a rise in M&A activities within the AI ecosystem.

LEGAL AND REGULATORY CHALLENGES

Acquiring an AI company entitles certain challenges.

  • Antitrust: As AI becomes more integral to business strategies, regulators are likely to scrutinize M&A transactions more closely for antitrust concerns. This is particularly true as leading tech companies partner with promising AI startups. Additionally, given the strategic importance of AI technologies to national security, cross-border transactions may face increased government oversight.
  • Comprehensive Due Diligence: Acquirers must conduct thorough due diligence to accurately assess the value and risks of AI targets. For companies providing AI infrastructure, standard due diligence procedures apply, with additional focus on AI capabilities. However, for AI-centric businesses, due diligence should be tailored to address specific AI-related risks. Key Areas of Focus in Due Diligence:

1. Intellectual Property (IP): Ensure that the target company has clear ownership of its IP and that there are no pending disputes or potential infringements.

2. Data Privacy and Security: Verify compliance with data protection regulations and assess the robustness of cybersecurity measures.

3. Regulatory Compliance: Understand the regulatory landscape and ensure that the target company complies with all relevant laws, including those specific to AI. Moreover, taking into account recent regulations in Europe related to AI.

4. Technical Evaluation: Assess the technical capabilities of the AI systems, including the quality of the training data and the performance of AI models.

  • Tailored Representations and Warranties While many risks associated with AI companies, such as intellectual property (IP) rights, data privacy, and cybersecurity, are similar to those in other high-tech sectors, acquirers are increasingly demanding AI-specific representations. This is particularly relevant where AI technologies involve unique risks or unsettled legal standards, such as the use of web-scraped data for training AI models.
  • Recourse Mechanisms. Standard representations cover common risks, but AI-specific representations may be treated as “fundamental” with longer survival periods and higher caps. Special indemnities and representation and warranty insurance (RWI) can also provide financial protection against undisclosed risks.

STRATEGIES FOR RECOURSE:

  1. Special Indemnities: Tailored indemnities for AI-specific risks uncovered during due diligence.
  2. Extended Survival Periods: Longer survival periods for key representations and warranties related to AI technologies.
  3. Representation and Warranty Insurance (RWI): Coverage to protect against financial losses arising from undisclosed risks.

Conclusion

The M&A landscape in the AI sector presents unique challenges that require specialized legal and regulatory approaches. As AI technologies continue to evolve, so too must the strategies for conducting M&A transactions within this dynamic sector. Comprehensive due diligence, tailored deal terms, and appropriate recourse mechanisms are essential for navigating these complexities.

This article is provided by GNS Law for educational and informational purposes only and is not intended as legal advice.

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