AI technology for legal business functions has a significant potential to help lawyers focus on higher value-adding tasks. As a result, the legal AI software market is expected to quadruple in the next five years. Although there are some challenges to overcome, like biased forecasts and keeping track of changing regulations, there are numerous manual tasks in legal departments to automate. AI can be successfully applied to those use cases for time savings and cost reductions.

How is the interest in legal AI?

Source: Google Trends

We observe increasing popularity in legal AI, according to Google Trends. While the level of interest was around 15% before 2016, we see that it has risen to 60% in the last two years. We witness a similar trend in the legal AI market. A 2019 Markets&Markets research shows that the legal AI software market will grow from $0.3 billion in 2019 to $1.2 billion by 2024 at a Compound Annual Growth Rate (CAGR) of 31% during the forecast period. Considering the market growth of AI solutions for legal processes, we expect this increase to continue for a few more years.

What are the typical legal AI use cases? 

Document automation

Legal document automation can provide significant time savings (around 70%) and prevent errors. With AI, companies can generate different types of legal documents for their clients instantly and proofread them to avoid any mistakes. These documents can include business contracts, non-disclosure agreements, wills, and trusts. You can learn more about legal document automation in our related article. For more about document automation in general, here is our in-depth guide.

Here is a shortlist of AI-powered legal document automation vendors:

  • Knackly
  • Legal Up
  • PerfectNDA

Contract Review

Creating business contracts is a time-consuming process where both side’s lawyers need to manually review, edit, and exchange drafts numerous times. Gartner shares that in-house legal departments spend half of their time reviewing contracts. As it is uncertain when both sides agree on a particular contract, this process might cause delays in other related tasks.

AI can accelerate contract review processes by leveraging natural language processing (NLP) technologies, analyze them, and define the problematic parts. As manual contract review processes are prone to errors, AI can fix spelling mistakes and optimize content to provide shorter but more effective contracts.

Here is a shortlist of AI-powered contract review vendors:

  • Clearlaw
  • LegalRobot
  • ThoughRiver

Litigation Prediction

AI can evaluate the riskiness of cases and predict court outcomes. As this assessment can help companies plan their litigation strategies, AI can determine the riskiness of cases and predict court outcomes. This assessment can provide fast-track settlement negotiations and minimize the number of cases that need actually go to trial. BlueJ Legal shares they can predict case outcomes with 90% accuracy.

Here is a shortlist of AI-powered litigation prediction vendors:

  • BlueJ Legal
  • Legalist

Legal Analytics

Large companies will have lots of outstanding contracts, with different counter-parties, across numerous divisions. Thus, it is challenging to be aware of all the details and commitments of the company. By using AI to analyze existing agreements, legal firms and departments can achieve valuable insights that would provide different teams to improve their processes:

  • Sales: Companies can track when contracts are up for renewal and capitalize on revenue with upsell opportunities.
  • Procurement: Companies can be aware of the details of existing agreements and renegotiate with clients when necessary.
  • Compliance: Companies can easily monitor if they follow regulatory procedures.
  • Finance: Companies are always ready for cases like mergers and acquisitions (M&A) and due diligence.

Here is a shortlist of AI-powered contract analytics vendors:

  • Evisort
  • Lexion
  • Paperflip

Legal Research

Legal research is a manual process where mostly junior firm associates and young lawyers spend them to conduct research for different cases and understand them accurately. AI can:

  • scan through laws and regulations
  • provide different legal opinions for cases
  • inform legal departments with similar cases

This use case started to be more popular between legal companies, as Forbes shares that over 4,500 US law firms subscribe to Casetext for AI-driven legal research purposes today.

Here is a shortlist of AI-powered legal research vendors:

  • Casetext
  • Ross Intelligence

Intellectual Property

Companies that have multiple brands to promote online need to monitor 30+ digital platforms to protect their trademarks. AI can handle tasks related to businesses’ intellectual property like invention disclosures, docketing, filing applications, valuing your IP portfolio, and budgeting. According to IBM, using AI can half the total time spent by lawyers for analyzing trademark search results.

Here is a shortlist of AI-powered intellectual property vendors:

  • Anaqua Studio
  • SmartShell
  • Trademark Now

Electronic Discovery 

In legal departments, electronic discovery can account for as much as 70% of the cost of any legal action or lawsuit. AI can support businesses in electronic discovery processes to prevent them from unexpected issues. For that, AI can process high volumes of data, create relationships with different information assets, and provide legal departments with insights to protect themselves. This will enable faster electronic discovery processes and reduce legal review costs.

Here is a shortlist of AI-powered electronic discovery vendors:

  • Catalyst
  • Everlaw
  • OpenText

Electronic Billing

Managing legal expenditure is one of the automatable tasks that the majority of companies handle manually through spreadsheets. With AI, companies can reduce paper costs, decrease human-made errors, and achieve more accurate insights about their legal spending.

Here is a shortlist of AI-powered electronic billing vendors:

  • Brightflag
  • Smokeball

What are the main challenges of legal AI?

We can provide two critical challenges of AI for legal business functions:

AI can give biased predictions

AI might give biased results while forecasting court outcomes. While computing forecasts, AI bots can take irrelevant characteristics into account and provide inaccurate predictions to legal departments. This might cause companies to calculate the riskiness of their cases wrong and encounter unexpected situations.

AI might not be able to follow up changing regulations

Regulations change continuously, and AI bots need to stay up to date for legal use cases. An outdated legal AI solution can make inaccurate predictions and lead companies into wrong conclusions. As new regulations are passed every day, and existing ones change, it is a challenge to follow these regulations for legal AI tools.

Now that you have checked out AI applications in the legal business functions, please check out other AI applications in marketingsalescustomer servicehealthcareinsurance, or analytics. You can also read our other articles about AI and legal functions:

If you have more questions, do not hesitate to contact us:

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