Many of today’s students who are training to be traditional professionals will, in due course, be engaged as knowledge engineers. These new professionals will specialize in designing certain kinds of online service—we call this the ‘knowledge engineering’ model” – Richard Susskind, The Future of the Professions: How Technology Will Transform the Work of Human Experts (1st Ed. 2015)
What Richard Susskind envisioned in his publications (e.g. Tomorrow’s Lawyers, 1st Ed. 2013), slowly became reality: Professionals have become builders and system-thinkers.
Especially with the recent shift to generative AI and with various low- and non-code platforms achieving significant market shares, for example BRYTER (Telefónica Germany’s Legal Service Portal | BRYTER), legal engineering has become pivotal for the professional success of law firms and in-house legal departments.
In this entry I want to evaluate the current situation of and highlight the risks and opportunities associated with digital solutions in the legal context. Secondly, I would like to propose a framework for the implementation and deployment of such products and services, especially in a corporate environment. Furthermore, I want to take a look at relevant use cases, with a focus on the benefits that legal engineering can achieve.
Conclusively, I want to highlight Telefónica Germany’s emphasize on privacy engineering as subset of legal engineering and its importance for a data-driven infrastructure business model.
LegalTech from business enablement function to direct business driver
The recent advancement moved Legal Technology (LegalTech) from a supporting function to a cross functional operation task helping to shift GRC strategy to more monolithic approach for legal problem-solving and critical analysis:
This involves a governance change from colloquial ‘box-ticking’ of compliance requirements, beyond legal risk reduction, to a more refined service, helping business units directly, especially for business models situated in highly regulated environments, through boosting solution-oriented efficiency and productivity. Another big advantages of using integrated systems are additionally the improvement of transparency and (internal) accountability.
Therefore, Legal engineering involves complex problem solving. Particularly, this requires deep understanding of underlying legal frameworks (jurisdictional specifics i.a.) and directly translated requirements on the one hand, technical understanding and business knowledge, e.g. theories on socio-economic decision making, on the other.
Accordingly, legal engineers need to bring a lot to table, navigating through ‘different professional worlds’ by understanding and speaking different professional terms and ultimately, by combining cross-functional expertise with ownership and program management tools & techniques.
In accordance with every technological adoption there are specific risks and threats to be addressed, for example ethical concerns and technologically distributed biases. Particularly, in the deployment phase it is crucial to engage change management theories to smoothen and resolve any frictions.
Advanced Framework for development and deployment
In every corporate setting, even with a mature governance system in place, legal engineering draws on significant challenges and is usually depending on the personal responsibility for end-to-end process supervision. This is a perfect example for the organizational structure of ‘Team of teams’. Accordingly, it is vital to understand the organization’s culture and needs:
- Why? Explaining the vision, refined in a strategy, detailed in SMART goals.
- Who? …are the relevant stakeholders? In accordance with a RACI-matrix.
- What? Definition of benefit-driven KPIs to measure success and leave room for pivotal optimization. Additionally, more concrete questions: ‘Building from scratch’ for a specific pain-point or use a proprietary third party-application?
- How? Which legal engineering measures are already in place? Are there company-specific lessons learned? Which tools & techniques are applicable and cost-efficient?
Finally, this requires a stringent evaluation on each use case basis with a layered approach, searching for the best-in-class solution:
Pressure testing & relevant use-cases
At the forefront, the prevalence of legal engineering will generally produce the most significant benefit in data-driven-economy sectors (such as Finance, Medicine or Telecommunications), and currently, this means the highest ROI where there are big data elements, shared points of abstraction, common factors and reduced complexity, for example as part of:
Legal analysis:
- (Preliminary) legal assessments in a confined setting with limited constellations,
e.g. claims of passenger rights (Regulation (EC) No 261/2004) through Flightright. Another example would be legal APIs for the Microsoft Office suite with access to specified folders or the option of directly imported databases, for example in preparation of Due-Diligence audits (e.g. Noxtua ‘Matrix analysis’, Legora ‘tabular review’).
The depth and complexity of these assessments will drastically increase through the collaborations between LegalTech start-ups with established legal-oriented publishing houses, e.g. for Germany: Noxtua & C. H. Beck; Libra & Otto Schmidt or internationally: HARVEY & Lexis Nexis / Wolters Kluwer
- Automatic digital audits, e.g. monthly cookie and digital services check-up on websites in accordance with the GDPR (Regulation (EU) 2016/679);
- Formulation of more refined eDiscovery frameworks and applications to achieve the highest compliance status;
- AI Agents for legal research for the combined use of separated research platforms (e.g. HARVEY Assistant as Legal Co-worker or Legal);
Legal collaboration:
- Contract management platforms, with integrated contract approval workflows and stakeholder engagement platforms, digital signature enablement, secure documentation standards and automatic notification options;
- Smart contracts on blockchain basis, in regard to contract renewal or standardized compensation,
- Template generators for standardized contracts, e.g. NDAs or Privacy Notices.
- AI chatbot for training and policy enforcement purposes, e.g. how to handle data subject requests;
- ‘Vibe coding’ for Lawyers using Lovable, Replit or vibecode.law for designing compliant applications with legal prompt-engineering.
Legal action:
- Support through digital solutions of pro-bono work or law clinics to democratize access to justice,
- AI-based legal education tools, e.g. automatic and accessible exam reviews.
Another valid use-case would be aggregation, consolidation and subsequent analysis of publicly available court and / or authority material for making informed strategic litigation decisions, i.e. data-enhanced forum-shipping, especially in common law jurisdiction.
This should only serve as food-for-thought as the underlying technologies are still evolving and growing and adapting to the legal context.
Conclusion & Privacy Engineering as early example of legal engineering
Especially in a corporate setting, it is important to turn Legal engineering from data-centric to a human-centric opportunity, achieving integrated workflows, alleviating pain-points and aiming for cross-functional productivity.
A good example is defined per lege lata in Article 25 and Recital 78 GDPR as the principle of ‘Privacy by design and default’. This can also be used as best practice for other regulatory statues like Health Insurance Portability and Accountability Act of 1996, US (HIPAA):
This legal stipulation forced data protection professionals early on to combine legal expertise with technical knowledge and application, e.g. requirements engineering for software development and IT security standards for confidentiality (CIA-triad). Ultimately, this led to prolific establishment and use of Privacy enhancing techniques (PET), like differential privacy or federated learning or homomorphic Encryption. For further reference: Kassem / Müller / Esterhyse et. al., The EPI framework: A data privacy by design framework to support healthcare use cases – ScienceDirect.
The same PET are gaining now importance for AI safety and alignment research and by excelling digital trust. ‘Knowledge engineers’ as Richard Susskind put it, are receiving growing responsibilities in established legal professions and are at the forefront transforming the legal landscape.
