How Attorneys Shape Corporate Value, Risk, and M&A Readiness
The use of Artificial Intelligence (AI) in the corporate world has evolved from a trend into a core strategy. Businesses are no longer just experimenting with chatbots, they are integrating both proprietary and consumer AI as strategic assets to drive bottom-line results. AI tools are being adopted to improve productivity, increase efficiency, create autonomous workflows, improve forecasting, provide for faster customer support and target new customers.1 As AI becomes more entrenched in business, it also becomes a more prevalent topic in M&A valuation and litigation, and attorneys must be able to spot risky AI contract terms.
A company’s “AI maturity” is now a metric used in mergers and acquisitions. Companies with higher AI maturity are more attractive to certain investors who are looking at documented AI governance procedures, permissioned data sets, and clear AI contract language as indicators of a healthy, lower-liability enterprise. An analysis of the 100 largest corporate M&A transactions from 2025 showed that ~33% described AI as part of the impetus for the deal.2 AI maturity is often treated as “intangible capital.” According to a World Research of Business Administration Journal article, acquirers typically evaluate four key diligence features: data infrastructure, model autonomy, auditability, and regulatory readiness. While 79% of organizations have adopted some level of AI, only 21% have mature governance models (arXiv, 2026). While implementing AI can have benefits, it is important to simultaneously mitigate risk. Attorneys must now actively analyze and redraft contract language to manage risks related to algorithmic autonomy, intellectual property, and liability.
Below are some key legal considerations related to AI liability.
AI in Contract Drafting
Under traditional legal frameworks, computer programs are viewed as mere tools of their users. However, the increasing decision-making capacity of AI systems raises questions about whether these entities should be recognized as discrete legal entities (Taylor & Francis, 2026). With AI-formed contracts, a user might try to claim a misunderstanding based on an error made by their AI tool. However, courts are increasingly skeptical of this “fundamental mistake” defense, arguing that because users know AI can produce inaccurate outcomes, an “unexpected” result does not necessarily constitute a legal mistake. Essentially, “I didn’t understand how my own tool worked to generate this error” is probably not a winning argument to void the agreement. If you use an AI tool to help create a contract, the user is responsible for the outputs, even if they are detrimental.3
Liability for Algorithmic Errors
As dispute resolution shifts from legal institutions to corporate IT platforms, there is a growing risk of ambiguous liability when an autonomous system fails to perform or produces a harmful output. Traditional theories of product liability law, such as manufacturing defects, design defects, failure to warn and negligence could all be applied to disputes related to AI tools.4 While potential harmful outputs are most often discussed in the context of medical AI, likely due to the concrete human injury that is an unfortunate consequence, the risk of AI error is present in every industry.
Contractual Liability
A large amount of potential AI-related liability comes from contract terms that govern the allocation of risk. Some vendors include “as-is” disclaimer clauses with their products, disclaiming responsibility for the accuracy, reliability, or fitness for purpose of the AI output in order to limit their liability for any inaccuracies. Vendors might also cap their liability at a certain dollar amount, which may or may not adequately cover any resulting damages. Some larger companies may offer indemnification for AI outputs, but others specifically exclude coverage for claims arising from the outputs of AI tools. A 2025 study found that only 17% of vendors provided warranties related to regulatory compliance, while 88% of vendors included liability caps in their contracts. These numbers indicate that vendors are shifting the responsibility for the use of AI tools onto the user.
Attorneys should be aware of the myriad ways AI terms and clauses are impacting risk allocation and the potential valuation of a business. The use of unapproved AI tools (shadow AI) that utilize company data is a major concern for corporate buyers. Due diligence requests now often ask for AI use policies and purchase agreements often include warranties regarding the use and disclosure of sensitive information within an automated system. Ultimately, the integration of AI is no longer a technological luxury but a core business competency, and companies that prioritize sophisticated governance will secure a distinct competitive and legal advantage in the future.
To manage these evolving risks, businesses should conduct an audit of their own AI use to identify: internal and external tools, the data sources and data ownership for those tools, output ownership, whether sufficient human controls have been interspersed through the AI pipeline, and compliance with existing contractual terms and potential disclosure risks. Regularly reviewing and updating terms of service can also limit liability and increase a business’s AI maturity. These steps can be completed prior to a transaction or could be part of an overall strategy for management, quality assurance, and ethical use of AI. Attorneys should be prepared to function as both legal architects and risk auditors, serving as human guardians of corporate AI maturity.
Footnotes
1 Singla, Alex, et al. “The state of AI in 2025: Agents, innovation, and transformation.” 11/5/25. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
2 Levy, Brian. “Global M&A industry trends” 1/27/2026, https://www.pwc.com/gx/en/services/deals/trends.html
3 Szczepanski, Kevin. “When AI Gets It Wrong: Managing the Legal Risk of Hallucinations in Business Decision-Making” Cybersecurity Law & Strategy March 31, 2026 https://www.lawjournalnewsletters.com/2026/04/01/when-ai-gets-it-wrong-managing-the-legal-risk-of-hallucinations-in-business-decision-making/?srsltid=AfmBOorRYaqn3jmwdnYGYp3l4bo648l6KNKm1KoYdy3ELWUSDbzrtdFz&slreturn=20260429145525
4 “Liability for AI Errors: Who Is Responsible When an AI Gets It Wrong” April 8, 2026 https://www.analaw.com/blog/liability-for-ai-errors
Originally published by Hennepin Lawyer, 21 July 2026
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