AI & Machine Learning Contracts

Legal Frameworks for a Technology That’s Rewriting the Rules

Artificial intelligence isn’t a future consideration — it’s a present reality reshaping how businesses operate, compete, and allocate risk. And the legal frameworks haven’t caught up. The contracts governing AI development, deployment, and procurement are being written in real time, often by parties who don’t fully understand the technology or its implications. John Montague has been advising technology companies on complex transactions for over fifteen years, and AI and machine learning contracts have become one of the fastest-growing areas of his practice. His technology transactions foundation — built at Locke Lord LLP (now Troutman Pepper Locke), an AM Law 200 firm — gives him the structural sophistication to draft agreements for technology that doesn’t fit neatly into existing legal categories.

From John Montague: The hardest question in AI contracting isn’t about the technology — it’s about the data. Who owns the training data? Who owns the model outputs? Can the vendor use your data to improve models that serve your competitors? These aren’t edge cases. They’re central to every AI procurement decision, and most standard vendor agreements don’t address them adequately.

How We Help

Montague Law advises both AI companies and enterprises deploying AI solutions on the contractual frameworks that govern these relationships. John Montague’s work includes drafting and negotiating AI development agreements that address model ownership, training data rights, output IP, and performance benchmarks; structuring AI-as-a-Service procurement agreements with appropriate provisions for data handling, model transparency, and vendor lock-in mitigation; advising on data licensing agreements for machine learning training, including rights scope, usage restrictions, and regulatory compliance; negotiating AI partnership and joint development arrangements between technology companies and enterprise clients; counseling companies on the intellectual property implications of AI-generated content and AI-assisted inventions; and advising on emerging AI regulatory compliance, including the EU AI Act’s risk-based framework and evolving U.S. state and federal guidance.

Why AI Contracts Need a Different Approach

Traditional software licensing assumes a static product — you license version X, and the terms govern that version. AI models are fundamentally different. They learn, they evolve, and they produce outputs that neither party fully controls or predicts. This creates contracting challenges that existing templates weren’t designed to handle.

Consider a basic scenario: an enterprise procures an AI solution from a vendor. The vendor’s model was trained on a proprietary dataset, but the enterprise feeds its own data into the system during use. Over time, the model improves based on usage patterns across all customers. Who owns the improved model? Can the enterprise extract its data if it switches vendors? Is the vendor using the enterprise’s proprietary data to benefit competitors? These questions require contract provisions that most standard software agreements simply don’t include.

John Montague approaches AI contracting from first principles, building agreement frameworks that address the unique characteristics of AI systems rather than force-fitting them into traditional software licensing structures. His work as a visiting professor of Entrepreneurial Law at the University of Florida keeps him connected to the emerging technology ecosystem, and his venture capital practice means he regularly advises AI startups on how to structure their commercial agreements for scale.

Florida’s growing technology sector — particularly in fintech, health tech, and logistics — has produced significant demand for AI-capable legal counsel who can work at the intersection of technology and commerce. Montague Law’s offices in Fernandina Beach and Coral Gables serve AI companies and enterprise adopters across the state and nationally.

Frequently Asked Questions

Who owns AI-generated outputs?

Ownership of AI-generated outputs is one of the most unsettled areas of intellectual property law. Under current U.S. law, copyright generally requires human authorship, which creates uncertainty about the protectability of purely AI-generated content. In practice, the contractual allocation of output rights between AI vendor and customer is often more important than the underlying IP law — which makes the contract drafting critical.

What data rights should I negotiate in an AI vendor agreement?

At minimum, you should address ownership of input data you provide to the vendor, restrictions on the vendor’s use of your data for model training or improvement, data portability and return upon termination, data security and breach notification obligations, and compliance with applicable privacy regulations (CCPA, GDPR, HIPAA if relevant). John Montague typically advises enterprise clients to negotiate explicit prohibitions on the vendor using customer data to train models that serve competitors.

How does the EU AI Act affect U.S. companies?

The EU AI Act applies to AI systems deployed in the EU market, regardless of where the provider is based. U.S. companies that offer AI products or services to EU customers need to assess their obligations under the Act’s risk-based classification system. High-risk AI applications face significant compliance requirements around transparency, data governance, and human oversight. John Montague advises companies on navigating these cross-border regulatory requirements.

Related Practice Areas: Technology Transactions | SaaS & Cloud Services | Data Privacy & Compliance

Need help with an AI contract? Call 904-234-5653 or schedule a consultation.