For these reasons, it is not sufficient to simply provide a new platform because it’s a “brand name” or because you saw a great demo. Often, a great piece of technology is paid for but is not optimally right sized for the law firm or corporate’s specific environment. Even worse, adoption is never fully realized, and the investment becomes a sunk cost. To avoid these pitfalls, consider a step-by-step automation journey, starting from scratch and moving towards full generative AI adoption.

The first step in automating a legal process is the detailed mapping of all workflows. This includes interviewing stakeholders from the requisite practice areas and internal/external clients, as well as observing and tracking how the activity has been historically performed. Once all relevant information and documentation have been gathered, it becomes possible to design and create optimal processes that leverage a blend of human expertise and GenAI automation.

The second step is to implement the newly created processes through specific operational mechanisms. Best practices include the creation of legal centers of excellence (COEs) or transactional service centers (TSCs) with dedicated personnel to execute the vision and roadmap. This requires applying the right level of change management, which typically involves creating KPIs, training all involved stakeholders, and properly communicating the initiative. The importance of communication cannot be understated – the way information is disseminated can make or break a legal transformation journey.

The third step is to repeatedly execute the implemented processes, tracking their performance through the new KPIs, and continuously improving every detail. In the initial phases (months 1-3, 4-6), there will undoubtedly be hiccups, and the target quality goal may not be immediately achieved. However, continual tweaking, program management, and quality control will lead to optimal and maximal impact.

Once the third step shows results (mostly human-driven at this point), the fourth step involves evaluating the technology that best suits the specific use case for the improved process. With many AI tools available, ensuring the chosen platform fits the change management program is imperative. By infusing, adopting, and merging GenAI technology into the targeted workflow, you can further improve it by reducing human interaction for standard business-as-usual tasks. This allows attorneys and legal ops professionals to focus on higher-value strategic work and standardizes quality within the law firm or corporate legal department.

The fifth step is to continue down the AI journey, completely automating tasks that are repeatable and do not require much nuance. This involves improving the adopted technology and reducing human interface on these tasks to a negligible amount, where quality oversight, sanity checks, and prompt engineering iterations are all that remain. Applying algorithms, supplemental generative AI, and other related technologies can further improve the legal tech stack and synergies, such as integrating a contracts redlining and interrogation assistant into a document management platform for gold-standard organization.

Applying this automation journey to a concrete case, we can envision contract drafting activities (historically a completely manual task requested by email and without any KPIs defined to track it) becoming a trackable activity. This would involve automated template drafting, self-service capabilities, and metrics to track speed and quality from pre-execution to post-execution.

The crux of this step-by-step automation guide is more than just automating manual tasks – it will be a game-changer for improving processes and adopting emerging technologies for corporate legal and law firms. While there may be initial resistance, stakeholders will eventually learn to appreciate the value driven by these processes, including time savings and improvements to their day-to-day workstreams. Finally, with a proof of concept for a complete automation journey with one discrete workflow/process, it will be possible to apply it to another legal task/workflow, creating a virtuous cycle of automation. This will free up time for more strategic and fulfilling work, which can ultimately help to reduce attrition within legal.