AI revolution!?
AI is taking the world by storm and transforming how we do business in every niche. The legal sector is no exception. AI for lawyers is a legal artificial intelligence that takes over routine and data-intensive tasks and lightens the daily lawyers' workload. AI in law firms has become a valuable asset, helping lawyers prepare for cases, process and evaluate information, gather various case-sensitive insights, and take on more clients with first-response AI attorney assistants available 24/7 to the general public. These are just a few examples of why AI and law are a word combo that is here to stay.
Since popular legal platforms like Westlaw have been using AI for a while now, almost all law firms have used some form of artificial intelligence at some point. However, the adoption of Generative AI in the legal sector is relatively new.
The main advantage of artificial intelligence in the legal industry is its ability to save time. Tasks that once took hours or even days, like research, drafting, reviewing documents, and entering data, can now be done in seconds. With the help of AI, routine tasks can be automated, and lawyers can focus more on higher-level, strategic work that directly benefits their clients.
To fully grasp the benefits AI in legal sector can bring to the table, let's step back a little and dive into what AI is all about.
What is artificial intelligence?
Artificial Intelligence (AI) is a subset of computer science that aims to create machines capable of performing activities which were previously possible only through human intervention. Some of these activities include learning, problem-solving, perception, and understanding languages. The first implementation of AI in the area of law was carried out using a rules-based approach. As the name suggests, in such an approach, the machine performs a certain task or makes decisions based on predefined rules. In the legal context, rules-based AI systems can help in arranging documents, categorizing files and even locating laws and precedents. Rules-based AI is particularly suited for tasks which can be performed based on clear instructions.
Machine Learning (ML) is an advanced form of AI, one which goes beyond mere rule-based AI models. This refers to programming the AI such that it learns from any data fed to it, recognizes patterns in such data, and then makes decisions based on it, with as little human intervention as possible. The combination of machine learning and law could examine the results of old case rulings, legal precedents, and other data for predictive purposes, legal research, or even estimating the result of a particular case.
Natural Language Processing (NLP) is a crucial feature of AI with regard to the legal industry. NLP enables AI systems to interpret and generate human language in a meaningful manner. In the legal field, the application of NLP involves analyzing legal texts, managing contracts, and creating legal briefs.
Large Language Models (LLM) is another milestone achieved by the current AI technologies. LLM stands for Large Language Model and refers to models, similar to GPT, which make use of machine learning techniques and NLP features to be able to comprehend and create natural human language. Regarding the tasks associated with the legal sphere, LLM may help draft legal texts, conduct legal research, and provide preliminary legal advice. The main advantage of LLMs lies in the ability to comprehend context and generate appropriate text based on it. With further use of LLMs, they become more accurate and meaningful.
If you'd like to know more about LLMs, you can read our article that explores areas of excellence and limitations of large language models.
What can AI in LAW practice help with?
Legal research
The primary applications of AI in legal research include predictive analysis, document review, and document analysis. Through fast analysis of a lot of documents, AI is able to uncover patterns and extract essential information. The benefits of legal AI software for the legal profession are as follows:
- Ability to analyze lots of data in just a few minutes, recognizing patterns from past similar cases, reducing errors, improving decision making concerning a particular case, anticipating risks, and avoiding future obstacles.
- Assistance in contract review in identifying unusual clauses, inconsistencies in language, and risks. With the help of AI, one can go through the entire text of a contract and point out areas where more attention should be paid.
Compliance and risk management
Identifying and preventing fraud, assisting with due diligence and compliance monitoring, as well as assessing and managing risks are all doable tasks for AI in the legal field. More specifically AI in legal industry can:
- Detect and prevent fraud and spot suspicious financial activities, such as money laundering or fraudulent transactions, while analyzing large data sets.
- Assist with due diligence and compliance monitoring, identify potential issues, and flag them for further review, saving time and helping to identify risks before they escalate.
- Assess and manage risks by analyzing past legal cases, spotting patterns in cases, and assessing the likelihood of risks.
Client services
As for client services, AI chatbots and virtual assistants give clients personalized recommendations and even predictive analytics with regard to the billing and pricing process. AI for law firms can also aid in client retention through:
- Interactions with clients through AI-driven chatbots and virtual assistants that can respond to common queries made by clients and provide them with information about their legal matters and even give some legal advice. Such chatbots can be installed on messaging applications and websites to offer clients around-the-clock assistance.
- Personalized recommendations based on the analysis of client’s information. Using information regarding a particular client, AI will be able to give this person customized recommendations with respect to various legal aspects, from possible risks to the outcome of particular proceedings.
- Predicting billing and pricing data in order to determine how much legal services will cost.
Case management and workflow optimization
When it comes to work processes, AI can help with case prioritization, legal project management, and workflow automation. AI is making lawyers' daily workload lighter by:
- Helping legal professionals prioritize their workload by analyzing factors like case complexity, deadlines, and client priorities.
- Assisting in managing legal projects by tracking tasks, deadlines, and resources so law firms can monitor progress to keep projects on schedule and within budget.
- Taking on such tasks as data entry, document generation, and scheduling. AI can extract information from legal documents, fill databases, create standard legal documents, and schedule appointments saving time and allowing legal professionals to focus on more complex work.
Predictive maintenance in legal technologies
Predictive maintenance is yet another area in which software using AI outshines its peers. Whether in the prediction and scheduling of maintenance activities for legal databases, hardware, software updates, and user assistance, you can always count on AI to do the trick for you.
Reduce the risk of losing your data or having downtime by making use of AI in your predictive maintenance:
- Constantly keep tabs on your legal database status and performance, predicting possible maintenance or upgrade needs ahead of time.
- Automate the process of software updating and patching, taking into account scheduled releases to apply updates at optimal times and avoid disruptions.
- Predict potential critical security vulnerabilities that should be attended to immediately.
- Track hardware performance parameters such as temperature and usage, predicting when it might be necessary to perform some maintenance or replacement activities.
Legal marketing and client acquisition
The role of AI in marketing is in automated targeted advertising, content creation, customer care, lead generation, and analyzing market trends. With regard to marketing, AI tools used by lawyers will assist with:
- Data analysis of the client profile and internet activity to generate advertisements that target the right clients.
- Content creation on the field of law including articles and blog entries as well as optimization of content to appear on search engines.
- Customer engagement, answering any questions and gathering personal data to be contacted in the future and generating leads for law offices.
- Marketing trend analysis in terms of publications, social media platforms, and client feedback.
EXAMPLES of artificial intelligence in law
Kira Systems uses AI to analyze and extract relevant information from legal documents, improving the efficiency of due diligence processes. Kira Systems team used Natural Language Processing, and Machine Learning to save time, reduce human error, and enhance the accuracy of document review.
Lex Machina offers legal analytics that predict litigation outcomes by analyzing past case law and judge rulings. Machine Learning and Predictive Modeling was employed to help lawyers devise better case strategies and manage client expectations by understanding trends and precedents.
LawGeex is a legal tech company that automated contract review and approval with the help of AI. LawGeex's platform analyzes legal documents, compares them to the company’s predefined legal policies, and highlights any deviations or issues that require attention. Now legal teams can review contracts faster and handle higher volumes of work while reducing the risk of missing important legal details.
DoNotPay was originally designed as a chatbot to help users contest parking tickets, and now has evolved into a broader legal service platform. The platform assists users in a wide spectre of legal matters, including filing small claims, managing subscriptions, and even helping with immigration processes. The chatbot interacts with users to gather necessary information and generate the appropriate legal documents or provide guidance on their legal issues.
ELTEMATE – A Hogan Lovells technology company, adopted AI-powered e-discovery tools to manage large-scale litigation cases. By using AI for technology-assisted review (TAR) and predictive coding, the firm can automatically sift through vast amounts of electronically stored information (ESI), such as emails, documents, and other data. The AI tools help identify relevant information more efficiently and accurately than manual review, significantly reducing the time and cost associated with e-discovery in complex legal cases.
Clio is a widely-used legal practice management software that employs AI for case prioritization and management. The platform uses AI to automate tasks like case scheduling, document management, and client communication. Clio’s AI features help law firms prioritize cases by analyzing deadlines, complexity, and client needs, ensuring that the most urgent cases receive attention first.
Seal Software is an AI-powered contract analysis and fraud detection platform that helps legal teams identify risks and potential fraud within contracts and other legal documents. NLP and ML is used by the software to analyze contracts, flag clauses or terms that may indicate fraudulent intent or non-compliance with regulations.
Derwent Innovation is an AI-driven platform that provides comprehensive patent research and analysis tools. The platform analyzes global patent data, identifies trends, assess the patentability of inventions and provides analysis of patent documents, helping with strategic IP decisions.
JuryScope is a legal consulting firm that uses AI to assist law firms with jury selection. The company combines AI tools with psychological analysis to evaluate potential jurors. By analyzing social media activity, online presence, and demographic data, JuryScope helps legal teams identify biases or predispositions that may affect the outcome of a trial.
DeepL, an AI-based translation service, used by legal professionals for translating contracts, court documents, and other legal texts. DeepL uses its neural network technology to provide highly accurate translations while maintaining the original legal terminology and tone.
Ravel Law (acquired by LexisNexis and now a part of their Lexis+AI products) used AI for sentiment analysis to assist lawyers in understanding judicial opinions and trends. By analyzing the language used in court opinions, Ravel Law's platform provided insights into judges' sentiments, helping legal professionals predict how a judge might rule on a particular case.
Verbit is an AI-driven transcription service that uses speech recognition and NLP technologies to provide real-time transcription services. Law firms use Verbit to transcribe depositions, court hearings, client interviews, and other legal proceedings. Verbit’s ability to learn from legal-specific language and terminology ensures that transcriptions are not only accurate but also contextually relevant.
Clio Grow is a legal-specific CRM and client intake management system that uses AI to streamline client relationship management for law firms. It helps law firms manage the entire client lifecycle, from lead generation and intake to ongoing client communication and relationship building. This AI for attorneys can analyze incoming inquiries, automatically categorize and prioritize leads, and even suggest personalized follow-up actions based on client interactions. Clio Grow’s AI features can also analyze communication patterns to identify clients who may require more attention or follow-up, helping the firm maintain strong client relationships and improve retention rates.
Risks to be aware of when using AI
Ethical concerns
- Bias and fairness
AI models, specifically ML, may unintentionally replicate any bias present in the datasets, resulting in biased legal outcomes or recommendations.
- Transparency
A significant number of AI models are described as black boxes, meaning that there is no clarity about how specific outcomes were reached.
- Dependency
It should be considered that overreliance on AI could possibly result in compromising the professional decision-making of lawyers.
- Client Confidentiality
It is essential to make sure that any AI application is in accordance with professional guidelines regarding client confidentiality.
Data privacy issues
- Data breach risks and sensitive data
AI use increases the amount of highly sensitive data stored electronically by Law firms, which can heighten the risk of data breaches. Strong security measures are needed to keep this data secure and prevent unauthorized access.
- Compliance with data protection laws
Law firms must ensure that AI systems comply with laws like GDPR or other local regulations to avoid legal and reputational risks.
Education and training
- Knowledge about AI
It is essential for lawyers and staff members to be educated on the pros and cons of AI to utilize its benefits effectively.
- Training
In order to benefit from AI, proper training in the usage of AI technologies is required.
- Keeping it updated
Due to the constant evolution of AI, ongoing education regarding changes in AI technologies and their legality becomes a necessity.
Liability and accountability
- AI and decision-making
Assigning responsibility for decisions based on AI is not always an easy task. Proper regulation of the use of AI in practice is necessary to ensure liability for any potential risks.
- Who is accountable for errors?
In the case of making an error in using the program, one should consider who is to blame – the software designer, the law firm, or the attorney.
Client trust and perceptions
- Creating trust
The client may have to become less closed regarding using AI in practice. Transparency when working with technology and communicating its benefits could help create trust.
- Expectations management
At the same time, it is important to set realistic expectations for clients to prevent their dissatisfaction.
Even though there are certain difficulties associated with the incorporation of AI in practice, this way forward is still worth trying. After all, legal practice and artificial intelligence are two disciplines that fit together quite well. AI does all the hard work, while attorneys can concentrate on what is more difficult to accomplish in legal practice.
