AI in Law Firms to Deliver New Models of Legal Services
Sean Doherty takes a look at NexLP's Story Engine product and the future of artificial intelligence in law.
April 23, 2018 at 10:00 AM
5 minute read
Today law firms are challenged to maintain profitability in a buyer's market for legal services. The 2017 and 2018 reports on the state of the legal market by The Center for the Study of the Legal Profession at the Georgetown University Law Center and Thomson Reuters observed a flattening demand for law firm services. The reports also document a loss of market share to alternative legal service providers, such as Axiom and UnitedLex, which have developed new models for delivering legal services. Also, corporate legal departments are accomplishing an increasingly amount of legal work in-house.
Beyond the competition from alternative legal service providers and client legal departments, the “2018 Citi Hildebrandt Client Advisory” identified that the Big Four accounting firms (Deloitte, EY, KPMG, PwC) have built up their legal departments with integrated service offerings to compete with law firms. “ The 2017 Global 100,” by the American Lawyer, observed that the Big 4 use multi-point client relations, and build solution sets for business issues. And ALM Intelligence's “The Big 4 Are at the Door” reports that the accounting firms are better positioned to meet the needs of future legal departments than traditional law firms. And the Big Four's legal services are no longer exclusive of the US. Last year, PwC launched ILC Legal in the District, marking a continuing push into the law firm market by the Big Four.
Since the Great Recession (2007-09), firms have primarily met revenue challenges by increasing billing rates and strategizing to maintain profit margins and cut costs. Firms merge with other firms to obtain economies of scale and adopt new technology to manage the business of law more efficiently to provide more cost-effective services to clients. And like their corporate counterparts, firms cut costs, such as downsizing staff and reducing real estate footprints. But with increasing competition for law firm services, it's not clear that firms can continue to raise rates and cut costs. Firms need to take another strategy from the corporate playbook.
Companies in many industries are building more efficient business models and revenue streams using data and artificial intelligence (AI) tools, such as machine learning and natural language processing (NLP). The healthcare industry employs data and AI techniques to develop new healthcare service models, improve treatments, and reduce prescription costs. The retail and entertainment industries use data to predict customer needs and identify customer problems to minimize incidents and complaints.
If law firms are to compete in the legal marketplace, they need to embrace the way the world around them is using data to create new value with AI. To their credit, firms have invested in AI from the likes of likes of Lex Machina, Luminance AI, Neota Logic, and NexLP to make practice areas and workflows more cost-efficient and engage data-driven litigation strategies. Firms use predictive coding for document and due diligence review and embrace text analysis and contract analytics software to manage contract language. They also invest in predictive analytics to review how courts and judges may decide motions and cases based on decision-making patterns. But firms have not used AI on their data to create new business and new value for existing clients.
|Now Is the Future of AI in Law Firms
NexLP is developing products and services that will lead to widespread adoption of AI in law firms. Firms have data from open and closed client e-discovery and investigation matters that have been previously reviewed and coded. Using AI tools from NexLP, firms can turn that work product into meaningful insight for clients and create new business opportunities and recurring revenue streams.
The Chicago-based company's Story Engine product uses AI to find relevant information and key documents in e-discovery and investigations. The product enables firms to quickly identify and understand significant players and topics in client data, such as money, dates, people, locations, and organizations, to gain a tactical advantage to prepare and strategize for court proceedings quickly and get on top of regulatory investigations with data profiles and summarized facts.
With AI tools, such as deep learning, NLP, content classification, and emotional and behavioral intelligence, NexLP's platform uses a model library approach to client data. Story Engine collects and analyzes lawyers' work product in finding and labeling relevant and privileged information in e-discovery matters and analyzes the client data that may span years, even decades. The platform builds models of inappropriate behavior and illegal activity that can alert firms and their clients of risks in compliance, fraud investigations, insider trading, anti-money laundering, price fixing, insider threats, whistleblowers, data leakage, discrimination, even sexual harassment. NexLP calls this “predictive coding without the coding.”
NexLP's AI Models synthesize e-discovery data into mathematical models to deliver to clients. The AI Models can be used on all new cases to quickly understand facts, hot documents, and people, allowing clients to swiftly understand data under investigation or litigation and provide them with actionable insight to develop case strategy or negotiate a settlement. Story Engine is deployed as a managed software-as-a-service (SaaS) or installed on premises, or through NexLP's many channel partners.
For law firms, maintaining profitability in the legal marketplace will not come from retrenching and cutting costs, but from retooling with AI to bring new approaches in delivering legal services.
Sean Doherty is a sole practitioner and freelance writer based in Brooklyn, New York.
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