Artificial intelligence (AI) is not just a buzzword; it’s the driving force behind innovation across industries. From autonomous vehicles to predictive healthcare solutions, AI is reshaping the business landscape. But when it comes to mergers and acquisitions (M&A), particularly those involving AI, there’s a critical aspect that often gets overshadowed by flashy tech demos: intellectual property (IP) due diligence. Let’s break this down in plain English so you—the tech leaders and private equity professionals—can navigate this maze effectively.

Why Should You Care About IP in AI Transactions?

Imagine buying a high-performance sports car only to discover that the engine is leased and the manufacturer’s logo infringes a trademark. That’s what can happen in an M&A deal if IP due diligence is ignored. AI assets—like the algorithms, training data, and software behind cutting-edge solutions—are the engines driving today’s innovation. If ownership or usability issues exist, your shiny new acquisition could stall.

Question: Would you buy a house without checking who owns the land it’s built on? No? Then let’s talk about how to dig into AI IP.

Key Focus Areas in IP Due Diligence

1. Ownership and Inventorship

The first step is verifying that the target company owns what it claims. This means reviewing employment contracts, IP assignments, and any third-party agreements that might grant others rights to the technology. Pay special attention to:

• Employment agreements with developers: Do they assign all IP rights to the company?

• Collaboration agreements: Are there co-owners lurking in the shadows?

• Encumbrances: Are there liens or other claims on the IP?

Real-World Example: A fintech startup claimed sole ownership of its AI fraud detection algorithm. Turns out, a former contractor held a key patent. Cue legal nightmare.

2. Patentability and Validity

AI patents live in a gray area. U.S. law currently requires inventors to be human (sorry, robots). But what happens if AI was heavily involved in creating the invention? This is uncharted territory.

Checklist for Patent Review:

• Are the inventions patentable under Section 101?

• Are the patents valid, or could they be invalidated by prior art?

• Do the patents adequately cover the core functionality of the AI product?

Pro Tip: If your target relies on AI-generated inventions, brace for a legal rollercoaster. Laws are evolving, and you’ll need to adapt.

3. Freedom to Operate (FTO)

Owning a patent doesn’t mean you’re in the clear. You’ll need to confirm that the target can actually use its technology without infringing on someone else’s rights. Skipping this step can result in costly litigation.

Watch Out For:

• Third-party claims

• Lack of indemnification agreements 

4. Open Source Software (OSS) Concerns

Most AI systems incorporate OSS. While OSS can speed up development, it comes with strings attached: licensing obligations.

What to Check:

• Are there any “copyleft” licenses (e.g., GPL) that could require public disclosure of proprietary code?

• Are license terms being followed?

Real-World Example: A company had to re-engineer its flagship AI product after failing to comply with OSS licenses. Don’t let this be you.

5. Data Ownership and Privacy

AI needs data, and lots of it. But who owns the data, and was it collected legally? Privacy laws like GDPR and CCPA could make or break your deal.

Questions to Ask:

• Does the target have rights to the training data?

• Was the data collected in compliance with privacy laws?

• Are there any ongoing regulatory investigations?

Tip: Compile a list of all datasets and review their origins and usage rights.

The Unique Challenges of AI in M&A

AI isn’t like traditional software. It evolves. For example, AI systems that adapt in real time (think autonomous drones) may raise additional regulatory questions.

Key Considerations:

• Regulatory Compliance: Has the AI been cleared for its intended use (e.g., FDA approval for medical AI)?

• Interdisciplinary Insight: You’ll need lawyers, engineers, and data scientists to evaluate AI assets thoroughly.

• Future-Proofing: How will evolving laws on AI inventorship and liability affect your investment?

Lessons from the Trenches: Insights from Industry Reports

McKinsey: Generative AI can disrupt markets, but only if companies have the infrastructure to scale it. Assess scalability during due diligence.

Accenture: Traditional M&A playbooks won’t cut it in the AI era. Look for synergies, retain top talent, and think ecosystem, not silos.

Practical Tips to Avoid IP Pitfalls

1. Use a Detailed Checklist: Cover everything from patents and trademarks to OSS and regulatory compliance.

2. Document Everything: Keep a clear record of your due diligence findings.

3. Engage the Right Experts: This isn’t a one-person job. Bring in interdisciplinary teams.

4. Think Long-Term: Will the IP still hold value in five years, or is it at risk of becoming obsolete?

5. Don’t Overlook Integration: Ensure the AI solution can mesh with your existing systems.

Unified Law: Your Partner in AI IP Due Diligence

At Unified Law, we’ve seen it all—from startups with murky IP ownership to established firms grappling with OSS missteps. Our team combines deep legal expertise with a practical understanding of technology to guide you through these challenges.

Why Work With Us?

• We cut through legal jargon to provide actionable advice.

• We collaborate with your team, ensuring no stone is left unturned.

• We’re as invested in your success as you are.

Final Thought: Navigating IP due diligence in AI isn’t just about avoiding risks; it’s about unlocking value. With the right approach, you can turn IP into a competitive advantage. So, are you ready to dive into the AI goldmine? Let’s talk.