Many legal professionals are eager to learn about artificial intelligence (AI), though few legal departments are using it at this time. While technologists debate a precise definition of AI, most agree that with the significant advancements made in recent years, AI will (1) automate many time-consuming activities, (2) transform the practice of law in our lifetime, and (3) continue to make more advancements in the near future. Meanwhile, AI also raises a host of thorny ethical questions, including (but not limited to):
- Must I learn to create machine learning algorithms to meet the duty of competence?
- Does the duty of supervision mean that I must manually redo all the work that AI performs to ensure it works as it should?
- Does the duty of confidentiality preclude the use of AI — making every other question moot anyway?
Even with these questions, AI helps lawyers meet ethical obligations far more than it stands in the way. Here, we’ll briefly review the legal ethics that typically apply with the use of AI. Next, we’ll see how AI works within Contract Lifecycle Management (CLM) software, which is similar to how it works with other legal technologies. In the end, you’ll discover a way to continually understand AI to help you meet your ethical obligations.
What legal ethics apply with the use of AI?
Several ethical duties may apply for technology use. Here is a quick look at three of them.
Duty of competence
Currently, 38 states have adopted the duty of technology competence based on the ABA Model Rules of Professional Conduct. Competent lawyers are expected to keep abreast of the benefits and risks associated with relevant technology. You don’t need to elucidate the inner workings of AI algorithms. But you do have to understand:
- What technologies are available to improve the legal services you deliver,
- The capabilities and limitations of AI tools,
- How the data that AI tools use is obtained and input,
- How AI produces results, and
- The risks and benefits of the legal answers AI provides.
Duty of supervision
The same duty of supervision that applies when lawyers delegate work to paralegals and junior attorneys also extends to AI tools. You can rely on advisors with established technological competence, but you must monitor the application of AI and ensure the resulting work product is accurate and complete.
Duty of confidentiality
The potential to commingle multiple clients’ data when using AI freezes many lawyers in their tracks. Some AI tools require that client data be “shared” with third parties.
Lawyers must ensure that their clients’ information is safeguarded, including ensuring third parties use appropriate security measures. Rest assured, the confidentiality duty is here to stay no matter what technology we use.
What does AI look like in contract lifecycle management software?
AI in legal practice usually refers to machine learning and natural language processing techniques. CLM platforms often train on extensive bodies of commercial contracts to optimize AI models for data extraction, language detection, and classification purposes.
Those models then work within AI-based tools that help lawyers (1) gain a more thorough understanding of contracts much faster, and (2) convert predictable manual tasks into time-saving automated workflows. There are endless possibilities for how AI can be used in CLM. Here are several ways AI-based tools enhance CLM performance.
AI-powered contract initiation: Guidance and consistency
End users can create new contracts based on no-code templates powered by AI. Users respond to questions to automate contract assembly. The most appropriate templates are selected based on the individual’s input and the template established for the type of contract created.
CLM systems can pull data from third-party systems as needed to populate contracts with the most up-to-date information. As AI guides users through the process, it can explain why terms and clauses exist in templates, offer standard fallback positions, and list terms and conditions that are unacceptable to improve understanding and ensure consistency.
AI-powered legacy contract migration: Instant action
AI helps to automate legacy contract migration and new customer onboarding by extracting data such as key milestones and contract classifications from legacy contracts and contracts created outside a CLM platform.
This makes contracts instantly actionable to ensure they are routed to the appropriate people, deadlines are properly tracked, and notifications are automatically delivered to the right people based on predefined policies.
AI-powered negotiation: Detection and protection
AI helps identify specific language and legal concepts in contracts, such as indemnification obligations and choice of law provisions, to bring important issues to the surface. It also detects unusual and risky language and spots omissions and additions.
With the ability to structure collaboration for greater efficiency, legal teams can typically establish roles such as reviewer, chief negotiator, and viewer. Assigning each team member the appropriate role and access level protects confidentiality and speeds up negotiations.
AI-assisted contract workflows: Speed and predictability
Automating manual workflows standardizes and accelerates activities, such as contract request processing and review and approval routing. Categorizing contracts tells the software which workflows to apply.
For example, AI will know to route all contracts categorized as software licensing agreements to specific individuals in a specific order for review and approval. Issues that lie outside CLM’s preset capabilities are quickly escalated for lawyer review.
Automating workflows adds much-needed predictability and scalability to contract processes. And it bakes accuracy and accountability into daily activities.
AI-assisted contract intelligence: Learning and scaling
AI tools pull key variables from contracts to enable the continual measurement of contract-related business data — down to the clause level. Over time, legal departments create libraries that contain the best-performing blocks of contract language from which to build new contracts and templates.
Conditional templates allow end-users to automatically generate new contracts using decision-tree guidance to ensure they include the appropriate language and clauses. AI tools help to automate a host of manual activities like these, from the start of the contract lifecycle to the end.
Smile! Your technology partner can help.
In short, AI helps lawyers perform the work they’ve been doing manually — including reviewing, routing, and negotiating contracts, tracking and analyzing KPIs, and developing standard templates — but it helps them perform much faster and more accurately while also generating more impactful insights. These capabilities are key to providing competent legal services.
As AI-based tools advance further, lawyers must continue to understand how they work. But turn those frustrated frowns upside down! Your legal technology partner can help. Ask your partner to explain how AI works in its software today, how they plan to invest in AI going forward, and how the product you use today will change over time.
The right technology partner should be able to provide the education and information you need to meet all your ethical obligations and help you prepare for the more automated future. And that’s a great reason to smile!
