Whether we are talking about legal AI or AI applied to law, the use of generative AI is now emerging as a strategic issue for corporate lawyers and SME managers, who are faced with the need to adopt it while managing the risks. But in practical terms, how should this be done? Discover a secure 5-step implementation methodology, use cases and concrete solutions to transform AI into an ally for your legal practice. An overview with Olivia Papini, an expert in emerging technologies applied to the legal sector.
Artificial intelligence is profoundly transforming the legal profession. Since the rise of generative AI in late 2022, you must quickly adapt your professional practices. The Senate report «Generative Artificial Intelligence and the Legal Profession: Act Rather Than Suffer» (December 2024) confirms this: these technologies represent both a considerable opportunity and a major challenge. As demonstrated by the strong reaction of the legal profession to the launch of the «I.Avocat» application in January 2024, the development and use of so-called «generative» artificial intelligence technologies are sometimes perceived as a threat by some representatives of the legal profession. A pragmatic approach is needed: AI must be demystified without idealising it.
Here is how to structure your actions around three key issues: ethics and responsibility, task automation, and the protection of your legal data.
Quick glossary
IA Act
The European regulation on artificial intelligence, which came into force in 2024, establishes transparency, security and compliance requirements based on the risk level of AI systems. It strictly regulates systems used in sensitive areas such as justice and human resources.
GDPR – General Data Protection Regulation
This is the European regulation governing the protection of personal data. It requires transparency, consent and security in all data processing, including that carried out using artificial intelligence.
Privacy by Design
This is the principle that personal data protection must be integrated from the outset when designing a tool, service or data processing system. This involves minimising the data collected, securing systems from the outset and ensuring compliance with the GDPR by default.
Soft law
These are rules that guide behaviour (ethical charters, professional recommendations, codes of conduct) but have no binding legal force. This «soft» law complements hard law by specifying good practices.
Legal AI: what impact on ethics and responsibility?
The use of generative artificial intelligence by lawyers implies a redefinition of their role.
Clarifying the chain of responsibility
When AI generates legal advice or analyses your contracts, who is liable in the event of an error? This question becomes crucial in your daily practice.
The Senate report highlights the risk: «Generative artificial intelligence is based on a probabilistic model. It masters language to produce content, but does not understand it. Its reliability is therefore not guaranteed.»
You must therefore establish a clear chain of responsibility between:
- the AI designer (transparency about limitations)
- you, legal professional (verification of results)
- your customer (information on the use of AI tools)
Testimonial
Tiffany Dumas, solicitor specialising in personal data protection, partner at In Extenso Avocats PACA
«In my practice, I have learned to systematically establish a clear chain of responsibility with my clients when I use AI for GDPR analyses. I explain to them that AI saves me time in detecting problematic clauses, but that I am the one who legally validates each recommendation. This transparency builds trust and defines responsibilities.»
Becoming an AI supervisor: your new role
AI does not replace you; it redefines your role. You become an ethical guardian, with new skills to develop:
- critical evaluation generated results (training in algorithmic bias)
- contextualisation automated recommendations (sector-specific adaptation)
- bias detection algorithmic (development of a critical analysis grid)
While the emergence of generative AI may have raised fears of job losses or downsizing among legal professionals (particularly solicitors), the Senate report provides some nuance. Indeed, as generative AI is prone to errors, the expertise of legal professionals will remain indispensable.
When used judiciously in an ethical and secure environment, AI can help make the law more accessible, efficient and equitable.
For example:
A law firm has implemented a double validation protocol. Each AI-generated contract analysis is critically reviewed by a senior solicitor, then finally validated by a partner or the legal director, who verifies the legal relevance and contextualises the recommendations according to the client's sector of activity.
[Also read]
What is the real impact of artificial intelligence on professions? What new roles and skills are emerging from this revolution?
Find out more in the ORSYS white paper. The new AI professions - The impact of AI on professions.
Legal AI and task automation: efficiency gains and skills preservation
Measurable efficiency gains
Generative AI also enables you to conduct legal research or draft standardised documents more quickly. It efficiently automates many of your daily tasks.
- Legal research : significant reductions in search time, according to industry studies
- Specific tools : Doctrine.fr with AI, LexisNexis+, Dalloz AI, Claude/ChatGPT with systematic verification methodology
- Contract analysis : significant improvement in the detection of risky clauses based on feedback
- Specific tools Kira Systems, Luminance, Contract Intelligence (Wolters Kluwer)
- Document generation standardised
- Specific tools HotDocs, ContractExpress, custom AI templates
- Regulatory monitoring automated
- Specific tools : Doctrine Veille, Légifrance automated alerts, RSS + AI summaries
These applications demonstrate the tangible impact on your productivity. This allows you to devote more time to high value-added activities: strategic consulting, complex negotiations, risk management.
Forward-looking vision: AI at the service of ESG assessment
Testimonial
Valérie Tiersen, Founder and Chief Executive Officer, Green Score Capital
«AI is revolutionising ESG risk assessment by making previously invisible risks visible, thanks to detailed analysis of unstructured data, particularly geospatial data. It enables a shift from a declarative approach to a predictive approach, which is much more useful for risk management.
But what about the reality of the market? ESG AI in finance is still in its infancy. Most use cases remain focused on compliance, with little integration into risk management processes. The true potential remains largely untapped. What I see in the field is that it facilitates report writing, but with inputs from declarative data. There is still a long way to go and many opportunities to be seized!»
This perspective perfectly illustrates how AI is transforming legal analysis beyond traditional applications, creating new bridges between law, finance and sustainable development.
5-step methodology for implementing legal AI
To securely integrate AI into your practice, follow this proven methodology.
Step 1: Preliminary analysis
- Map your sensitive data flows (Who : Data Protection Officer + Senior Legal Officer)
- Identify low-risk tasks that can be automated (How to : audit of existing processes)
- Assess the impact on data protection (Deliverables : GDPR risk matrix)
Step 2: Technology selection
- Prioritise «Privacy by Design» solutions (Who : CIO + legal advisor)
- Check suppliers' GDPR compliance (How to : due diligence questionnaire)
- Test several tools on non-critical cases (Deliverables : benchmarking report)
Step 3: Secure configuration
- Set default privacy settings (Tools : advanced security settings)
- Minimise the data transmitted to AI systems (How to : prior anonymisation)
- Configure multi-factor authentication (Who : DSI)
Step 4: Validation and control
- Test the confidentiality guarantees (How to : penetration testing)
- Conduct an external audit if necessary (Who : external auditor specialising in GDPR)
- Document all security settings (Deliverables : complete technical documentation)
Step 5: Ongoing governance
- Monitor regulatory compliance (Tools : compliance dashboard)
- Train your teams regularly (How to : quarterly sessions)
- Update your procedures in line with developments (Customer communication : monthly legal newsletter)
For example:
A medium-sized firm deployed this methodology to implement a contract analysis solution. The result: no confidentiality incidents in over a year of use and significant time savings in the analysis of commercial contracts.
Preserving your core competencies
Beware of the risk of «intellectual laziness». Uncritical use of AI can actually weaken your analytical skills.
Testimonial
Jean-Christophe Pasco, postdoctoral researcher at the University of Poitiers
«Artificial intelligence represents a real breakthrough in the production and creation of legal knowledge. It challenges the traditional role of the legal researcher. Until now, legal researchers have constructed analytical frameworks that enable them to compare, distinguish and adapt legal systems through scholarly work drawing on multiple sources. Pursuing an ideal of justice that consists of «treating similar cases in the same way», legal researchers develop and systematise sophisticated legal, jurisprudential or doctrinal analyses in order to provide the public with conclusions that enrich legal doctrine.
Nowadays, AI can be used at every stage: collecting and processing legal sources, case law and legal doctrine, thematic summaries, analysing and comparing texts; and generative AI excels at generating textual content.
However, the requirements of the legal and scientific worlds remain: legal certainty, analytical and scientific rigour, ethical compliance and protection of confidentiality. These are also areas where research choices and assumptions belong solely to their authors (acceptance or rejection of previous theories, construction and selection of relevant and convincing arguments).
Thus, without calling into question the benefits of AI in the production of knowledge, these conditions limit the very possibility of systematic use and exclusive reliance on AI-generated outputs.»
However, the Senate report concedes that it is more likely that there will be a reduction in staffing requirements for support tasks. It will therefore be necessary to upskill these professionals, in particular by asking them to monitor the results obtained through the use of generative AI.
[Solution] Continuing education
It is essential to continue and accelerate the adaptation of initial and continuing legal training to the challenges and use of generative artificial intelligence. Training organisations such as ORSYS are incorporating the following into their professional training programmes:
- legal digital skills
- AI ethics applied to law
- sector-specific best practice guides
Are you determined to integrate artificial intelligence into your daily legal practice? Come and acquire the knowledge you need to understand how generative AI works and master the tools tailored to your specific needs. You can also try your hand at creating legal documents with Copilot and other automation tools. Want to find out more? Take a look at the training programme. Artificial intelligence (AI) at the service of legal professions.
Protecting your data: legal AI, weakness or shield?
Regulatory update
The regulatory developments of summer 2025 marked a decisive turning point.
AI Act deadlines
- 10th of July 2025 : publication of the code of practice for general purpose AI (GPAI)
- 2 August 2025 : entry into force of new transparency, audit and quality requirements for GPAI models
- Direct impact on the tools you use every day (ChatGPT, Claude, etc.)
Regulatory developments
- 12 September 2025 : entry into force of the Data Act, creating a right of access to data from connected objects
- 12 January 2027 : new obligations for manufacturers to ensure data portability
These developments create a stricter but also more predictable framework for the professional use of legal AI.
Managing confidentiality risks
Your legal data is particularly sensitive: personal information, trade secrets, litigation strategies. The use of AI therefore raises crucial questions about protection.
The main risks you need to manage:
- storage of confidential data by AI models
- information leak in cloud systems
- breach of professional secrecy obligations
Testimonial
Tiffany Dumas
«The three essential GDPR precautions before using a legal AI tool are: checking that the tool does not store the data entered, ensuring that the servers are located in the EU, and always anonymising documents before analysis. Since the AI Act, my perception has changed: we finally have a clear legal framework, which makes our recommendations to clients more secure.»
A regulatory framework that is becoming clearer
First, you must comply with an existing legal framework:
- GDPR
- the European regulation on AI (AI Act), which came into force in August 2024
The Senate report also recommends the development of specific professional rules. A complementary approach could include soft law.
This approach would offer you:
- flexibility in the face of technological developments
- professional consensus on best practices
- accountability actors
- practical guidance on ethical issues
AI as a protection tool
Paradoxically, AI can also enhance the protection of your data. Certain applications allow you to:
- detect automatically confidential information in your documents (solutions such as Microsoft Purview, Varonis)
- anonymise court decisions (specialised tools such as Doctrine Anonymisation)
- automate your GDPR compliance processes (platforms such as OneTrust, TrustArc)
For example:
A legal department uses an AI tool to automatically scan its contracts and identify personal data clauses that need to be updated following the introduction of the GDPR. The result: large volumes of contracts can be processed in a matter of days, rather than several weeks manually.
Library of ready-to-use legal prompts
Here are some practical examples that you can use immediately in your practice.
For contractual analysis:
«Analyse the legal risks of this contract, focusing on liability clauses, termination conditions and GDPR aspects. Identify points requiring negotiation and propose alternatives.»
For GDPR compliance:
«Draft a GDPR-compliant confidentiality clause for a service agreement that includes the processing of personal data. Incorporate the principles of data minimisation and retention period.»
For legal monitoring:
«Summarises recent regulatory developments on AI in the financial sector in Europe, identifying the concrete impacts for credit institutions and compliance obligations.»
For the drafting of deeds:
«Generate a force majeure clause adapted to the post-COVID context, incorporating health risks and mitigation obligations for the contracting parties.»
These prompts provide a working basis that should be adapted to your specific context and always validated legally.
Ultimately, artificial intelligence transforms your legal practice by offering considerable opportunities for efficiency. But to get the most out of it, you need to take a balanced approach. First, by positioning AI as a complementary tool to your expertise. But also by maintaining critical oversight of algorithmic recommendations. You also need to develop dual legal and technological skills. Finally, you need to implement rigorous data protection protocols. Training plays a crucial role in this transition. It allows you to acquire the skills necessary to use these technologies effectively while preserving your critical judgement. The future belongs to legal professionals who can master these tools while preserving the essence of their profession: advice, critical analysis and human support.
