Top 8 Legal AI Use Cases & Leading Vendors in 2024

Legal AI Market Growth Projection

Artificial intelligence (AI) technology is rapidly transforming the legal industry. From automating routine tasks to uncovering insights from volumes of data, AI is boosting efficiency, reducing costs, and allowing attorneys to concentrate on high-value legal work.

According to one estimate from MarketsandMarkets, the legal AI software market is projected to quadruple in size over the next five years, skyrocketing from $0.3 billion in 2019 to $1.2 billion by 2024.

In this comprehensive guide, we‘ll explore the top use cases for AI in legal functions and highlight some of the leading vendors in each category that legal teams should have on their radar.

Surging Interest and Adoption of Legal AI

Interest in exploring legal applications for artificial intelligence has risen steadily in recent years. According to Google Trends, searches for the term "legal AI" have spiked over 140% since 2016:

Legal AI Google Trends

Driving this growth is legal professions hunger for new technologies that can drive greater efficiency and cost savings. According to Thomson Reuters, 52% of legal professionals say improving operational efficiency is a top business priority. AI is increasingly seen as a solution.

The expansion of the legal AI software market mirrors this growing appetite. As cited above, MarketsandMarkets predicts stellar growth for the sector – from $0.3 billion in 2019 to $1.2 billion by 2024, representing a 31% compound annual growth rate.

Legal AI Market Growth Projection

Key factors fueling the adoption of legal AI include:

  • Demand for efficiency – Legal teams need to improve productivity and do more with limited resources. AI automation allows attorneys to offload repetitive tasks and focus their skills on high-value work.

  • Access to data – Law firms and legal departments have a wealth of documents, contracts, and case records that can be mined for insights using AI.

  • New capabilities – AI techniques like natural language processing and machine learning can unlock new ways to analyze legal documents and predict case outcomes that were previously not possible.

  • Client expectations – Corporate legal departments especially face pressure from business executives to control costs and operate more efficiently.

  • Competitive advantage – Law firms that fail to adopt legal AI may lose out to competitors utilizing AI‘s advantages.

With these trends showing no signs of slowing down, legal AI appears primed for even more substantial growth in coming years as these technologies transition from cutting edge to mission-critical.

The Top Use Cases Driving Legal AI Adoption

Let‘s explore some of the most popular current uses for legal AI that are delivering proven value:

Contract Review and Management

Reviewing contracts may be one of lawyers‘ least favorite tasks. Yet it consumes a massive chunk of their time. According to research by Gartner, in-house legal departments spend upwards of 50% of their time manually reviewing and drafting contracts.

AI-powered contract review tools promise to slash the hours spent on this rote work by automatically scanning documents and flagging key terms, risks, and issues for lawyers to examine. This allows legal professionals to focus their review on only the most critical contract sections requiring human analysis.

Leading AI contract review solutions include:

  • Clearlaw – Clearlaw states its software can accelerate contract review by 3X over manual methods. Its algorithms draw insights from a database of over 1.2 million contracts.

  • eBrevia – eBrevia‘s AI platform is purpose-built for contract review and claims to cut review time by over 50%. The system extracts key data points and clauses.

  • ThoughtRiver – ThoughtRiver‘s software leverages machine learning to detect risks in contracts and suggest mitigation steps for lawyers to incorporate.

Meanwhile, contract management platforms like Seal Software utilize AI to analyze agreements after signing. This provides vital intelligence to optimize the contract lifecycle, including:

  • Ongoing compliance monitoring
  • Deadline and renewal tracking
  • Identification of revenue upsell opportunities
  • Mining data to inform contract negotiations

According to a Seal Software survey, 4 in 10 companies admit they don‘t know the terms of their own contracts. AI-powered analysis provides much-needed visibility.

Litigation Prediction

Forecasting potential litigation outcomes allows attorneys to better assess case risks and opportunities. But traditionally, attorneys had to rely solely on instinct and experience. AI litigation prediction tools leverage vast databases of past verdicts and decisions to accurately predict case results.

Vendors like Lex Machina claim over 90% accuracy for their AI-powered litigation forecasting models. Key players providing predictive insights include:

  • Lex Machina – Lex Machina‘s Legal Analytics platform uses AI to predict case outcomes and opposing counsel behavior based on millions of legal cases and documents.

  • Premonition – Premonition mines data on millions of U.S. court cases to provide litigation analytics and case projections.

  • CaseCrunch – CaseCrunch‘s AI toolset delivers case outcome forecasts, optimal settlement ranges, and more tailored litigation insights.

These analytics help legal teams determine which cases to pursue aggressively versus settling, enabling data-backed litigation strategy.

Legal Research

Conducting research to uncover relevant legislation, precedents, filings, and legal opinions is a core yet time-consuming aspect of legal work. AI-powered legal research aims to accelerate this process by reviewing millions of documents and precisely surfacing the most relevant results.

As highlighted in Forbes, over 4,500 U.S. law firms now use Casetext CARA, an AI legal research assistant that leverages natural language processing to deeply analyze legislation and case law.

Top AI-enhanced legal research platforms:

  • CARA – Casetext‘s CARA solution returns the most relevant case law with analysis tailored to specific legal issues.

  • ROSS – Created by IBM Watson, ROSS is an AI legal research tool that quickly answers natural language questions with relevant citations and passages.

  • Ravel Law – Ravel‘s legal research platform uses AI techniques like dynamic visualization to uncover connections in legal data.

By autosummarizing key details rather than requiring full document review, these tools boost associate productivity.

Document Automation

Automating the creation of common legal documents like contracts and briefs is a longstanding yet still emerging legal AI application. Efficiencies through automation are significant – some estimate time savings up to 70% compared to manual drafting.

With solutions like HotDocs and Rocket Lawyer, lawyers can build custom templates that auto-populate with relevant data to quickly generate compliant, customized documents. Key features include:

  • Integrations to pull client data from CRM systems and folders
  • Expert libraries of clause language and templates by document type
  • Automated workflows to route generated docs for signatures
  • Syncing generated documents across devices

Leading legal document automation platforms:

  • HotDocs – Used by over 180,000 legal professionals for document assembly.

  • Rocket Lawyer – Rocket Lawyer‘s AI helps personalize and automatically generate contracts, LLC formations, and other legal documents.

  • Kira Systems – Kira clients report creating documents in 60 seconds versus an hour manually using its AI tools.

This automation enables attorneys to scale document creation while minimizing monotonous work.

Legal Billing

Billable hours have long been the currency for law firms. But manually tracking, recording, and parsing legal bills is tediously time consuming. AI-powered legal billing platforms like Pilosio and Fireman & Company promise to eliminate these inefficiencies by:

  • Automatically convertinginvoices into structured data

  • Auditing billing details for errors, duplications, and excess charges

  • Providing real-time legal spend analytics

  • Automating compliance with billing guidelines

Key solutions to watch:

  • Pilosio – Pilosio‘s AI inspects legal invoices to ensure accuracy, compliance, and optimal rates.

  • Fireman & Company– Fireman uses natural language processing to extract billing data from invoices and provides spend analysis by matter, law firm, practice area, and more.

  • Brightflag– Brightflag customers reduced legal spending by an average of 10% per year using its AI-enhanced legal bill review offerings.

These legal billing AI tools give finance and legal teams greater visibility into spend while maximizing value.

Contract Analytics

Enterprise legal departments oversee mountains of contracts across business units and geographies. Just tallying obligations and commitments across these agreements can be a nightmare. AI-powered contract analytics solutions enable legal teams to continuously monitor this universe of contracts to extract key data, risks, and insights.

Popular contract analytics platforms include:

  • Evisort – Evisort uses AI to instantly parse contract terms, obligations, and metadata into automatically generated summaries.

  • LinkSquares – LinkSquares customers have achieved up to 90% faster contract review efficiency using its AI-powered contract analytics.

  • Icertis – The Icertis Contract Intelligence platform structures contract data for analysis and reporting.

According to IACCM research, almost half of organizations admit they do not know the return value of their contracts. By converting unstructured contract data into quantifiable intelligence, contract analytics solutions empower strategic decision-making.

Key Challenges Holding Back Legal AI Adoption

Despite explosive growth, barriers still exist to the mainstream adoption of artificial intelligence in legal functions. Key challenges include:

Legal Industry Skepticism

The legal sector is notoriously risk-averse when it comes to new technologies. Lawyers tend to err on the side of caution, especially when it concerns potential liability or ethics conflicts. This cultural hesitancy has slowed AI adoption relative to other industries. Firms want reassurance of AI‘s safety and validity from peers and industry associations before fully committing.

Perceptions of Job Replacement

Like automation in other sectors, legal AI stirs understandable fears about technology rendering jobs redundant. The reality is AI aims to augment professionals, not replace them entirely. But uncertainty persists around how workforces may need to be reconfigured. Proper change management and transition support is crucial to minimize disruption.

Data Privacy Needs

The legal profession handles extremely sensitive client information covered by privacy laws and privilege. Fears exist about client data security as this information gets piped into cloud-based AI tools. Vendors must provide ironclad security and gain trust.

Limited Integration

Many legal AI applications today focus on a single capability. But lawyers use an array of systems and need insights flowing seamlessly between them. Integration between tools is still maturing. Legal teams want a unified analytics experience versus having to access disparate interfaces and datasets.

Constantly Evolving Regulations

Laws, regulations, and legal standards change frequently. This requires regular updating of AI tools to incorporate new legislation, amendments, and repeals. For predictive analytics, research, and other applications, maintaining 100% up-to-date datasets is an ongoing challenge.

What‘s Next for Legal AI?

Legal AI adoption remains in the early chapters, with tremendous headroom left for continued innovation and growth. These key developments appear over the horizon:

Integrated AI Legal Platforms

Many current solutions focus singularly on tasks like contracts or billing. But the future lies in unified platforms combining document review, analytics, research, predictions, and other AI capabilities into complete legal productivity suites.

More Accurate Predictions

As algorithms improve and training datasets expand, the speed and accuracy of legal forecasting will increase exponentially. Lawyers will be able to assess litigation risks and opportunities with greater confidence.

Natural Language Research

Already in progress, conversational interfaces will enable attorneys to query legal records and receive intelligent answers using natural speech versus keywords.

Augmented Drafting

AI writing tools will work interactively with lawyers to generate customized legal documents tailored to specific client matters and scenarios. This automation will drastically reduce document preparation time.

"Smart" Evidence Discover

Utilizing computer vision and textual analysis, AI e-discovery will help lawyers rapidly pinpoint the most relevant evidence and relationships from mountains of documents.

Firms that embrace legal AI will gain a distinct competitive advantage in the coming years. Those that fail to adopt will likely struggle to keep pace with demands for faster, better, and cheaper legal services. AI is quickly transitioning from cutting-edge to mission-critical.

Conclusion

Legal AI is here to stay. As the technology matures, it will transform how legal professionals research, forecast, draft, review, bill, and make data-driven strategic decisions.

Rather than replace attorneys, AI will augment their skills and allow more time for meaningful, high-judgment work while eliminating rote tasks. Forward-looking law firms and legal departments that implement legal AI now will propel their teams into the future ready to meet the demands of clients and business leaders alike for efficiency, value, and innovation.