How will IT megatrends and Legal Tech technologies influence the future IT strategies of law firms in Germany? : an AI-enhanced real-time Delphi study

Abstract

The findings of the study highlight the importance of Legal Tech for law firms in Germany, emphasising its critical role in boosting profitability and competitiveness while ensuring relevance in Germany’s rapidly evolving legal landscape. While Legal Tech is particularly important for large law firms, it also offers significant advantages to small and medium-sized law firms. The study’s participants agree that the integration of Legal Tech will bring substantial benefits to all involved stakeholders, be they clients or partners. Although these technologies need only to perform at 80% of human capability in terms error rate to gain acceptance, they are expected to lead to an increase in law firm spin-offs, empower smaller firms to handle larger cases, and facilitate the entry of third party providers into the market. Legal Tech is relevant to all fields of law and is set to democratise access to legal services, shifting power towards consumers and significantly enhancing ‘Access to Justice’. The thesis investigates the impact of IT Megatrends and Legal Tech clusters on the IT strategies of law firms in Germany, utilising the real-time Delphi method. Out of the emerging technologies (IT Megatrends), ‘Generative AI’ (=7.47 on a scale of 0-10), ‘Quantum Computing’ (=5.75/10), and ‘Neuromorphic Computing’ (=5.2/10) will have the highest impacts in 10+ years on the legal sector, according to the study’s results in 2024. The Legal Tech clusters ‘Legal and Compliance Analytics’ (=7.41/10), ‘Risk Management’ (=7.21/10), ‘Document Automation’ (=7.5/10), ‘Software for Legal Practices Management’ (=7.17/10), ‘Privacy Management Tools’ (=7.06/10), and ‘E-Discovery Solutions’ (=7.0/10) will have a high impact. The thesis also answers how these Megatrends and Legal Tech Clusters (will) influence the IT strategy of law firms in Germany, providing practical advice for CEOs and CIOs in the legal sector. This thesis also offers a new approach to using the (real-time) Delphi method enhanced by Artificial Intelligence. Integrating an AI’s “opinions” and “comments” into a Delphi study to “simulate” an (engaged) human expert could prove a powerful enhancement for traditional round-based and real-time Delphi studies and should be further researched. Only a fraction of the participants recognised the AI's “participation” during the study. This work also contributes to the method of Delphi studies by presenting statistical findings that elucidate various aspects of participant behaviour in Delphi studies on the experts’ opinion change behaviour. Enriching the academic debate, contractionary to Gnatzky et al. (2011, p.10), the so-called ‘Initial condition effect’ was substantiated across all participant groups in this study. This finding is consistent with Battin et al. (2023), who also observed a difference in how participants recruited early to the study amended their ratings of the outcomes compared to those recruited later. In line with the findings of Hussler et al. (2011), most participants did not significantly alter their initial ratings, and changes were exceptionally rare across all groups. Makkonen et al.’s (2016) observation that demographic factors such as age generation and professional experience do not significantly influence opinion change during the Delphi processes could be confirmed.