For the past twenty years, legal departments of companies of all sizes and in all sectors have been looking for technical solutions to optimize contract management. The market has therefore seen the emergence of a specialized software category called CLM (Contract Lifecycle Management). These tools, intended to cover all stages of the contractual life cycle, from initial creation to archiving, through negotiation and validation-, initially promised increased efficiency and a significant reduction in contractual risks. However, despite these promises, it is clear that traditional CLM tools have rarely fully met the expectations of their users...

Today, needs are changing and evolving, businesses need to review their technological approach. The intrinsic limitations of conventional CLM solutions, highlighted by years of sometimes painstaking use, make it essential to significantly evolve the tools. For modern legal departments facing increased constraints of speed, precision and adaptability, it is necessary to explore new technological paths capable of going beyond existing limits!

The three major limitations of traditional CLM tools

To understand the value of generative AI applied to the legal field, it is essential to first analyze the recurring shortcomings of traditional CLM solutions. Three main limitations regularly emerge from user feedback and constitute major operational obstacles.

Complexity and slow implementation

The first major pitfall of traditional CLM solutions concerns their initial implementation. These tools often require several months of complex settings, involving the participation of technical teams and specialized consultants. This delay is particularly problematic for companies subject to frequent regulatory changes or strong operational pressure. In concrete terms, each modification or new regulation requires costly and time-consuming technical adjustments, often carried out via external service providers.

Lack of flexibility in the face of changes in legal practices

The second limitation is the rigidity of traditional CLMs, which were initially designed around linear and repetitive processes. However, the legal profession is constantly evolving, with more and more varied use cases and constantly changing legal norms. The lack of flexibility prevents these software from quickly supporting internal changes in companies. For example, a simple internal review of standard confidentiality clauses (NDAs) may require a complete reconfiguration of existing workflows in the software.

Difficulties in managing documentary and contractual heterogeneity

Finally, traditional CLM tools often fail when faced with the diversity of contract types and formats handled by modern legal departments. Each contract, even of an apparently similar nature, may contain atypical clauses or specific conditions that are complex to be managed by software with rigid structures. This diversity and the absence of advanced automation often result in persistent manual processing, greatly reducing the interest and ROI of a solution that is supposed to make life easier for legal teams.

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Generative AI: an advanced technological response to current legal issues

Faced with the limitations of traditional CLMs, generative artificial intelligence appears to be a particularly suitable solution. Unlike traditional static approaches, generative AI offers continuous learning dynamics and superior adaptability that perfectly match the new requirements of lawyers.

Instant adaptability thanks to machine learning

Generative AI is constantly based on documentation and practices specific to each company. Thus, it is able to adapt quickly to internal, but also external changes (regulations, case law, emerging contractual trends). Unlike traditional solutions, it is no longer a question of manually reconfiguring fixed workflows: AI automatically detects, learns, and integrates new requirements into its contractual analyses.

Intrinsic flexibility that facilitates the integration of complex cases

Thanks to advances in Natural Language Processing (NLP), generative AI reads and interprets contractual clauses in context. Where traditional CLMs struggle with documentary heterogeneity, AI easily understands and processes the contractual subtleties specific to each case. Thus, unusual or rare clauses can be immediately identified and analyzed, without requiring systematic human intervention, thus saving lawyers a considerable amount of time to focus on complex issues with high added value.

Proactive generation of clauses and strategic recommendations

In addition to the analysis of existing contracts, generative AI brings a major innovation: the proactive ability to automatically generate personalized standard clauses. Thus, based on the drafting habits of a legal team, the system proposes model clauses adapted to the internal and sectoral specificities of the company. These proposals, verified by lawyers, make it possible to speed up the negotiation of contracts while ensuring strong compliance with internal legal strategies.

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Feedback and concrete use cases of generative AI in contract management

The concrete experiences of companies that have switched from traditional CLMs to generative AI show very positive and encouraging results.

A concrete example: the automated management of NDAs

Take the case of technological or industrial companies that regularly use NDAs. Traditionally, each new version had to be revised individually. Thanks to generative AI, the validation of NDAs is now done in a few moments, through the automatic application of internal legal playbooks. This automation considerably frees in-house lawyers from repetitive tasks with low added value.

Use cases in the banking and financial sector

In highly regulated sectors, such as banking or insurance, generative AI allows for continuous and automated contract verification. The system automatically identifies regulatory risks and proposes immediate compliance clauses, offering essential responsiveness in this changing and demanding regulatory environment.

Legal AI, a new essential pillar for modern legal departments

In the end, traditional CLM solutions have certainly brought initial improvements, but are now running up against their intrinsic limits, in the face of rapid changes and the new responsiveness requirements of modern legal departments. Generative artificial intelligence, through its flexibility, autonomy and continuous adaptability, responds precisely to the current challenges of corporate lawyers. At a time when businesses need to be able to anticipate legal risks and respond quickly to regulatory changes, generative AI is no longer an option but an imperative.

However, adopting generative AI requires a profound rethinking of how legal teams interact with technology. This naturally brings us to the next essential topic to explore: How to effectively prepare legal teams to fully and calmly integrate generative AI into their daily practices?