GERMANY Trends and Developments Contributed by: Felix Blobel and Sascha Leske, Noerr
being adopted also within the venture capital process itself. Firms are deploying AI tools for automated deal sourcing, competitor bench - marking, legal document analysis, and portfolio monitoring. Natural language processing (NLP) tools, for instance, are used to process large volumes of pitch decks, contracts, and market reports – helping investment teams flag risks, identify opportunities, and accelerate decision- making processes. Predictive analytics are also used to evaluate start-up health based on indi - cators such as cash burn, team dynamics, hiring trends and market signals. The growing adoption of AI in VC operations raises critical legal and regulatory issues as well as ethical questions. The EU AI Act, expected to take effect in phases from 2026, will classify AI systems into risk categories: unacceptable risk, high risk, limited risk, and minimal risk. Depend - ing on the classification, AI systems will be sub - ject to mandatory requirements such as trans - parency obligations, data governance audits, and human oversight. VC firms using AI inter - nally will need to ensure that these tools meet relevant standards – especially if they involve automated decision-making or personal data analysis. High-risk applications may include AI systems that assess founders, evaluate cred - itworthiness, or process personal employment information as part of the diligence process. Moreover, AI-based VC tools often intersect with data privacy regimes, particularly the GDPR. Automated processing of personal data – even in a commercial diligence setting – triggers heightened compliance obligations, including data minimisation, lawful basis assessment, and data subject rights management. Firms must establish internal policies to manage how data is sourced, stored, and used by AI tools. Some firms are developing internal AI ethics commit -
tees and adopting cross-functional governance structures to evaluate the risks and benefits of AI adoption. These frameworks will likely become standard in VC firms operating in regulated sec - tors or working with sensitive datasets. The GP perspective Fundraising In 2024, German VC general partners (GPs) faced a challenging fundraising environment marked by several key factors. • Recent fund returns have, in some cases, fall - en behind expectations, making it harder for GPs to attract investors. Many funds from the 2020–2021 boom have yet to deliver signifi - cant value, leading to fewer distributions for limited partners (LPs). This underperformance leaves LPs hesitant to commit to new funds. • The exit environment is constrained, directly curtailing the ability of LPs to recycle capital into new funds. With fewer IPOs and exits, longer holding periods and the rise of contin - uation funds, the liquidity for LPs is reduced. Lower distributions from prior fund invest - ments make LPs less inclined to invest in new funds. • Higher interest rates have altered the fund - raising landscape. With central banks raising rates, safe assets now offer attractive yields, creating competition for LP capital. Institu - tional LPs are rebalancing portfolios away from illiquid venture funds and into lower-risk, higher-yielding asset classes. German GPs must therefore make a stronger case that their funds can outperform these alternatives. Emergence of sector-specific and thematic funds Recent years have also seen the emergence of highly specialised VC funds targeting sectors such as climate tech, industrial automation, digi -
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