Part 2: AI, Risk, and Reps: A Practical Guide for German Start-ups Raising International Venture Capital - From Model Docs to Market Reality

As artificial intelligence reshapes industries, venture capital documentation has to evolve quickly to address new risks and opportunities. The latest iterations of both the NVCA Model Documents and BVCA standard forms introduced sophisticated AI-related representations and warranties that reflect investors' growing focus on AI governance, data usage, and regulatory compliance.

For German founders raising capital from international investors - or simply preparing for future rounds and that desired big-ticket M&A exit - understanding these new requirements isn't optional.

Drawing on our experience advising on both sides of the Atlantic, including direct involvement in the BVCA working group that shaped the latest UK standards, this two-part mini-series provides German entrepreneurs with practical insights into navigating the new AI representation landscape. In the Anglo-Saxon legal world, people draw an astonishingly fine line between "representations" and "warranties" – a distinction that tends to cause puzzled looks in German contract negotiations and usually ends up tossed into the same synonym bucket during translation. Since we don’t intend to venture into the murky depths of Common Law here, and German practice typically lumps both terms together under "guarantees" anyway, we’ll simply refer to them as "warranties" for the sake of sanity – very British, very pragmatic.

We'll decode what these clauses actually mean, why investors care, and how to position your company for success in an increasingly AI-conscious funding environment.

This Legal Ninja Snapshot …

This two-part mini-series is structured as follows:

• Part 1 presents the new AI warranties in the BVCA and NVCA model documentation and how they are redefining venture capital due diligence

  • I. The New Due Diligence Reality: AI Risks Investors Can't Ignore
  • II. Decoding the Three Clusters of AI Risk
  • III. The Purpose of Warranties
  • IV. NVCA vs. BVCA: How Do Their AI-Related Warranties Stack Up?
  • V. Same, Same, But Different? Why AI-Specific Warranties Matter

• Part 2 gives German founders guidance on how to future-proof their start-ups for US investors' and buyers' due diligence

  • VI. The German Twist: Why Copy-Paste Won’t Cut It
  • VII. Wrap-up and Future Proofing

…and Much More in OLNS#9 and OLNS#13

For comprehensive background information on raising capital from investors and M&A processes, we refer you to our OLNS#9 – Venture Capital Deals in Germany and our OLNS #13 – M&A in German Tech.

VI: The German Twist: Why Copy-Paste Won’t Cut It

By now, it’s clear why AI-specific warranties are no longer optional – and how the NVCA and BVCA have set the global tone. But before you copy-paste those polished Anglo-American templates into your next German deal, pause for a reality check: what works in Silicon Valley or London can quickly hit a wall in Berlin, Munich, or Hamburg (one of these cities has an amazing football team…).

German law and market practice come with their own set of quirks, requirements, and (let’s be honest) bureaucratic delights. Founder liability, data protection, and the ever-watchful eye of German regulators mean that simply translating NVCA or BVCA warranties is rarely enough. Instead, think of those playbooks as your compass, not your GPS: they’ll point you in the right direction, but you’ll need to chart your own path through the local legal landscape.

Here’s why local adaptation is essential – and how to make it work:

1. EU AI Act and GDPR – The Regulatory Doppelwumms

Operating in Germany means you’re not just playing by German rules, but by the EU’s as well. The new EU AI Act is the world’s first comprehensive legal framework for AI, classifying systems into four risk categories – each with its own compliance hurdles. Investors and buyers will want to know exactly where your AI fits in this framework, and how you’re addressing the relevant obligations.

• Unacceptable Risk: prohibited AI practices including behavioral manipulation, social scoring, and real-time biometric identification in public spaces
• High Risk: AI used in critical areas like healthcare, education, employment, and law enforcement faces extensive compliance obligations including risk assessments, data governance, and human oversight
• Limited Risk: AI systems like chatbots must be used transparently, meaning users must be informed they are interacting with AI
• Minimal: AI that doesn't fall under the previous categories, for example spam filters, faces no specific regulations

If you want a deeper dive, we recommend our Key Takeaways for Companies Using and Developing AI. Here's the brief version.

Unlike the BVCA, the NVCA warranties don’t mention the EU AI Act explicitly, but any promise of “legal compliance” will be read through a European lens if you’re operating here. If your investor or buyer wants to put more emphasis on these compliance risks, the respective reps may require you to make a clear statement about which risk category your AI falls under and how you comply with relevant obligations.

Next to the EU AI Act, the GDPR is a cornerstone of AI system compliance. Every processing of personal information in AI must be lawful. This means you need user consent or another justification as a valid legal basis for collecting and using personal information. But here's the catch: consent can be revoked at any time. If you've used data containing personal information to train your AI, it's nearly impossible to isolate or remove it from the neural network once embedded. This creates a real challenge for founders using AI tools that heavily rely on training data. If your AI processes data of sensitive nature, such as information about political opinions, religious beliefs, health, or sexual orientation, requirements are even stricter. The law demands extra safeguards, and the risk of non-compliance is much higher. This is why you need to carefully craft your warranties to address GDPR compliance if you want to satisfy investors' concerns about AI data usage.

2. Be Prepared: Map Out Your Risks

Prevention trumps cure every time. It's especially true for your AI setup. Whether looking at the NVCA or the BVCA AI-related warranties as a starting point, you need to map out your AI landscape and document what is required.

Before you negotiate warranties and can make proper disclosures against them, audit your AI landscape. Use the three-cluster framework – training corpus, system, output integrity – to organize your internal review:

First, assess your training corpus integrity. Be rigorous about the data you use to train your AI:

• Is it scraped, purchased, or user-generated?
• Do you need consent to use it? If yes, do you have consent?
• How sensitive is your training data and how do you avoid inadvertent disclosure of business-critical information?

Then, continue with your system’s integrity:

• Make sure your output doesn't infringe on anyone else's rights.
• If you are provider of AI systems, identify the regulatory requirements applicable to you and your business and check for any compliance issues.

Finally, don't neglect your output integrity:

• Track what your AI produces. Is it protected? If yes, who owns the IP?
• Make sure you can prove ownership and that your output doesn't infringe on anyone else's rights.

Be honest about your data sources, your governance practices, and your IP position and don't fall into the trap of so-called "AI-Washing", meaning overstating your AI capabilities to look good (if you are curious, we elaborate on "AI-Washing" in our AI Horizons Conversations series).

3. Draft Your Warranties and Prepare Your Data Room

When it comes time to negotiate with investors or buyers, every warranty you give is a promise you'll be held to. Here's the dilemma: the requirements are tough, and it's not always possible to know for sure if every aspect of your AI usage is fully compliant with all your legal obligations. So, you need to be careful about what you promise in your warranties. If things go wrong, you will be liable.

The winning strategy? Find the sweet spot between showing you understand the risks and avoiding promises you can't keep.

Remember, the model warranties shall provide you with orientation. Given their authors, they reflect investors' sentiment and are pretty too extensive, so you need to negotiate and adjust where appropriate. Here are some key considerations to factor in:

How "AI-heavy" is your start-up? The more important AI is for your business, the more you need to cover it in your warranties.

Are your warranties covering all three "buckets"? Are they covering all potential risks, especially regarding data privacy, cybersecurity, and IP?

Who is your audience? Are you talking to investors from the USA or from Europe or from MENA?

A few goalposts when looking for the "right" AI-specific warranties:

• If you want to explicitly state that you comply with EU legislation, the BVCA wording is better suited.
• If you focus especially on documentation and governance, the BVCA warranties are a better fit.
• If you want to limit the scope of your liability, the BVCA warranties may offer more flexibility in the form of optional knowledge qualifiers.
• If you want to attract US-based investors, keep in mind they are accustomed to the NVCA warranties.
• Regardless of whether you are working with the NVCA or the BVCA documents: do not consider the AI-specific reps in isolation but always in conjunction with the general reps on related topics such as IP, IT, data privacy and material agreements to ensure consistency and avoid AI-related liability "through the backdoor".

Investors and buyers will not only rely on promises, they will also require a data room. If you've done a thorough audit of how you use AI as summarized above, your diligence will pay off because it will facilitate putting together all relevant data. This includes AI documentation: data sources, compliance records, risk assessments, IP registrations, and third-party licenses.

Think also if you are better placed using your time disclosing against AI warranties, instead of negotiating their content – think about the message this might send to an investor. Are you a start-up that has considered AI risks and complexities and done its best, or have you had your head in the sand and as a result can’t stand behind the promises made in the investment agreement?

VII. Wrap-up and Future Proofing

The war for AI-powered start-up talent and capital is fierce, and the companies that master these risk management frameworks today will often have significant advantages in tomorrow's funding and M&A markets.

We've established that AI is no longer just disruptive technology benefiting your business, but also a new field for due diligence that investors and potential buyers will take seriously. Hence the NVCA and the BVCA have drafted model warranties covering AI specific risks that are centered around three clusters: the integrity of your training data, the integrity of your AI systems and the integrity of their output. The risks themselves revolve all around privacy, cybersecurity, IP as well as fairness and equity.

To help future-proof your start-up, the following can act as a generic road map that should be tailored to each specific case at hand:

• Map out your AI landscape and truly understand your risk profile.
• Familiarize yourself both with the NVCA and the BVCA warranties so that you know what Anglo-American investors and buyers will consider "market-standard" and where the German drafting practice will likely head as well.
• Check if and to what extent you could give such warranties today without the need to disclose certain facts and circumstances that could render such warranties untrue, incomplete or misleading. Then address these gaps proactively and stay abreast of the international developments in contract drafting.

Audit early, promise only what you can deliver, and prepare your data room. For many start-ups perfect compliance will not be achievable. But start somewhere. Have a solid foundation and build from there.