Navigating the Risks of AI M&A: Understanding Algorithm Ownership, Regulatory Uncertainty, Revenue Concentration, and Cybersecurity

M&A activity in the AI sector is booming, with Israeli-founded startups leading the way. However, acquiring an AI company presents unique challenges due to algorithm ownership ambiguity, regulatory uncertainty, revenue concentration, and cybersecurity risks. To mitigate these risks, dealmakers are using smarter diligence and tailored protections, including Representations & Warranties Insurance (RWI) for unknown breaches of key contractual representations.

The AI sector is experiencing a surge in M&A activity, with Israeli-founded startups at the forefront. However, acquiring an AI company presents unique challenges. The complexities of algorithm ownership, regulatory uncertainty, revenue concentration, and cybersecurity risks require a nuanced approach to mitigate potential pitfalls.

Algorithm Ownership Ambiguity
One of the key challenges in AI M&A is the ambiguity surrounding algorithm ownership. AI models often draw on a mix of proprietary code, open-source tools, customer data, and academic research, making it complex to determine who owns the resulting model and whether the company has the rights to commercialize and license it. Disputes over IP ownership, licensing limitations, or unclear contributions can undermine the value of a deal if not thoroughly vetted [1].

Regulatory Uncertainty
AI regulation is evolving rapidly, with the EU AI Act, US policy proposals, and new frameworks emerging globally. Many AI companies, especially early-stage startups, lack formal compliance structures. Buyers need to assess not only current compliance but also the company’s ability to adapt to future legal and ethical standards. This mismatch between today’s diligence and tomorrow’s liability makes regulatory risk a growing concern in AI transactions [1].

Revenue Concentration
Unlike more mature SaaS companies, AI startups often depend heavily on a handful of customers or pilot projects. Any misrepresentation about the status, renewability, or terms of key contracts can have an outsized impact. Understanding the durability of those relationships and their legal enforceability is essential [1].

Cybersecurity Risks
Ironically, companies specializing in cyber-AI may themselves be exposed to cybersecurity issues. Past breaches, poor data governance, or overstated claims about compliance with security standards can lead to unexpected liabilities. It’s critical to go beyond surface-level checks and assess whether security practices align with customer expectations and legal obligations [1].

Mitigating Risks with Smart Diligence and Tailored Protections
To navigate these complexities, dealmakers are responding with smarter diligence and tailored protections. One tool increasingly used in this space is Representations & Warranties Insurance (RWI), which can offer recourse for unknown breaches of key contractual representations, including those tied to IP, regulation, and cyber. This insurance helps mitigate risks associated with the unique challenges of AI M&A [1].

Looking Ahead: The SentinelOne Acquisition Rumors
The recent rumors of SentinelOne being acquired by Palo Alto Networks highlight the growing interest in the cyber-AI sector. SentinelOne, an Israeli cybersecurity company, has experienced a challenging period since its IPO in 2021, with its stock delivering a negative return of 57% for investors. However, the company’s market capitalization stood at less than $6 billion at the start of trading, presenting an attractive entry point for an interested buyer. A deal between SentinelOne and Palo Alto Networks could be valued at between $8 billion and $10 billion, reflecting the significant potential of the cyber-AI market [2].

Conclusion
As AI and cybersecurity sectors increasingly overlap, the surge in cyber-AI M&A is expected to accelerate. Successful AI M&A requires more than just traditional deal-making; it calls for a cross-disciplinary approach that blends legal, technical, and commercial insight. For those who get it right, the upside is significant, but the challenges are substantial. With careful navigation of risks and the use of innovative tools like RWI, dealmakers can mitigate the complexities and unlock the potential of AI M&A.

References:
[1] https://en.globes.co.il/en/article-ai-ma-differs-from-other-ma-deals-but-risks-can-be-minimized-1001517337
[2] https://www.calcalistech.com/ctechnews/article/kfqzwg5wr