Contract AI

What is Contract AI?

Contract AI refers to the application of text-based machine learning and natural language processing to mimic human contract drafting, reviewing, versioning, and monitoring processes. Over time, this technology learns to handle your complex legal language and replicate human decision-making processes in clerical work.

The most valuable uses for contract AI include:

• Scanning and digitizing physical documents
• Templating and clause libraries to streamline the contract creation process
• NLP-powered data analysis to uncover risks, costs, and contract abnormalities
• Identifying contract types, extracting important terms, and classifying metadata
• Automated notifications and legal/managerial approval workflows
• Reminders for expiration and renewal dates
• Contract analysis to pinpoint and resolve incorrect clauses and compliance issues
• Classification and clustering by type, purpose, or risk level
• Integration with other legal technologies for a seamless contract management process

With standard contract management software, you’d have to set up alerts and manually manage approvals. And you would still need to physically search for problems and update specific contract terms.

With contract AI, the system automatically identifies and analyzes key information using NLP. It then presents the information in an easy-to-understand format and suggests actions to take.

Contract AI also makes it possible to generate full legal contracts from scratch. It uses case-specific prompts to draft legally sound contracts with the highest degree of accuracy and completeness.

Synonyms

• AI for contract management
• AI contract generator
• Contract artificial intelligence

Key Concepts in AI for Contract Management

Legal teams and deal desks use contracting software throughout the entire contract lifecycle. As such, its applications are quite broad.

To simplify, let’s look at the key themes in AI for contract management:

Natural Language Processing (NLP)

One of the key components of contract AI is NLP. This technology allows machines to understand and interpret human language, including legal terminology.

It helps with:

• Contract analysis and review
• Identifying relevant clauses and provisions
• Summarizing contracts and extracting key information (contract abstraction)
• Classification and categorization

NLP works by using algorithms to break down sentences into smaller parts and analyze the relationships between words and phrases. It then interprets the context and tone in legal language. This forms the basis of the AI’s ability to understand and manage contracts.

Pattern and Trend Recognition

Machine learning algorithms extract features from processed contract data. Features can include:

• Specific terms
• Clauses
• Dates
• Monetary values
• Parties involved
• Geographic locations

Through supervised learning, the system analyzes patterns over time to identify trends in these areas. For example, it may recognize shifts in regulatory compliance requirements or changes in standard contracting practices in a particular industry. It can also help you understand the relative value of different contract terms through financial analysis and risk assessment.

Predictive Analytics

AI-powered contract analytics unlock a whole new world as far as negotiation and strategic decision-making go. Not only does it allow you to identify outliers and optimize your workflows, but you can also use it to:

• Quantify the Expected Value of a contract (revenue vs. costs)
• Spot trends and relationships within large datasets
• Flag financial risks or liabilities
• Create and manage risk profiles for different contract types

Machine learning algorithms analyze historical contract data, including outcomes like disputes, compliance issues, and successful fulfillments. This forms the basis for predicting future contract outcomes.

From there, it builds predictive models using techniques like supervised learning, where the algorithm is trained on a dataset with known outcomes. The models learn to associate certain contract features with specific outcomes.

As more contract data becomes available, the predictive models continuously update and refine themselves to improve their accuracy and relevance.

Automation in Contract Processes

Historically, businesses used rules-based contract lifecycle management software with programs that were trained to perform specific tasks (and not much else). They’re adaptable to different scenarios, yes. But humans are setting the rules, so they’re inherently rigid and error-prone.

Now, machine learning and generative AI enable trained, real-time contract intelligence built on a Large Language Model (LLM). It can adeptly analyze, assess, and present information it derives from contract data.

The result? A meticulously organized and efficient system devoid of any human errors.

How Contract AI Works

Data Input and Processing

The first step involves ingesting contract data, which can be in various formats (PDFs, Word documents, scanned images, etc.).

This data is then preprocessed to normalize, structure, and make it suitable for analysis. Preprocessing might include OCR (Optical Character Recognition) for scanned documents, text normalization, and data cleansing.

This step also involves cleaning and standardizing the text. Contract AI corrects typos, converts text to a uniform case, removes irrelevant characters, and standardizes date and currency formats.

Algorithmic Processing

There are a few ways algorithms analyze text data from your business and legal contracts:

• Semantic analysis — Breaking text down into constituent parts, deriving meaning from those parts individually and in context
• Synonym resolution — Identifying different words that refer to the same thing (such as “contract” vs. “agreement”)
• Concept extraction — Identifying words and phrases that represent specific ideas or topics

Algorithms also leverage pre-trained models to identify patterns in your contract data, such as a particular clause or term. This allows for more efficient and accurate processing of contracts.

Pattern Recognition and Predictive Modeling

Once the data is processed, machine learning algorithms use it to identify patterns and trends in your contract data. This can help with tasks like risk assessment, predicting outcomes of future contracts, and analyzing compliance across multiple contracts.

Automation and Decision-Making

Your AI-powered contract software will suggest the next course of action or run a set of rules to determine the best approach for handling a contract. It can also automate routine tasks like reviewing and redlining contracts, flagging potential risks, and updating contract templates.

Thanks to NLP, your contract review software will also structure complex contract data into more understandable formats, like reports or visual dashboards, making it easier for legal teams and non-technical stakeholders to make informed decisions.

Applications of Contract AI

Depending on the specific needs of your company, using AI-driven software to automate contract management can take on numerous forms. Contract lifecycle management comprises all the functions of the contracting process, from initial drafting through execution, renewal, or cancellation. AI supports and enhances the work involved throughout every stage in several ways.

Here’s a look at how you’ll use a contract AI solution throughout the contract lifecycle:

First Draft Authoring and Template Creation

AI-generated contracts are a lot different from the ones you assemble from a clause library and simple template. While those are tools you’ll still use in your contracting workflow, AI generates text from scratch. When you’re just using templates and prewritten clauses, you’re still manually building contracts.

AI contract software learns from your previous negotiations, agreements, and legal precedents. As you use it, it gets smarter and smarter, which enables it to generate unique legal agreements from clauses, templates, or from scratch using prompts in minutes (with little to no human intervention).

Legal and Managerial Review

Of course, a template or AI-generated contract isn’t the final document. There will always be a need for human oversight when you’re writing contract terms, clauses, and conditions.

Legal teams and managers can use AI to navigate the more challenging parts of contract creation with templates, such as defining roles and responsibilities, service level agreements (SLAs), and key performance indicators (KPIs).

AI assistance extends to the approval stage, where the software can automatically escalate certain issues, clauses, and terms to higher-level team members for the final sign-off.

Negotiations and Initial Redlining

Contract redlining is largely a manual process. Still, AI can help you identify key clauses that need to be redlined and modified. When you’re modifying the contract with another party, your AI software will do most of the heavy lifting for you.

The software uses natural language processing to analyze changes made by both parties, compare them against negotiated templates or previously executed contracts, and potentially suggest alternatives or flag potential risks.

AI is also tremendously useful for contract version control. Instead of tracking individual changes via word processing software, AI automates the process and keeps an accurate log of the contract’s evolution, including all versions and contract modifications (throughout its entire lifecycle).

Recognizing Risks and Discrepancies

The system identifies patterns within the contract data using algorithms like clustering, classification, and regression. These patterns could relate to common clauses, frequently negotiated terms, risk factors, or compliance issues. This helps in categorizing contracts and understanding commonalities and deviations in contract structures.

Performance and Compliance Tracking and

AI-based metrics track all activities related to implementing legal policies and enforcing contract compliance guidelines in ways your legal/compliance team couldn’t do alone.

It can automatically detect any potential policy violations across multiple contracts or sections and flag these risks for review. The results are consistent and auditable reports that keep all stakeholders informed.

If you’re operating in a highly regulated field like healthcare, finance, or banking, specialized contracting technology also learns the regulations for your particular industry. You can use it to keep your business in good legal standing.

Simplifying Complex Contract Language

Many of the people involved in the contracting process won’t have technical or legal backgrounds, but they still need to understand the language and implications of a contract. Contracts aren’t normally written in a way that’s easy for the average layperson to understand, though. Even for those who do understand its contents, a contract is normally much too long.

With AI, you can summarize and simplify an otherwise intricate, complex contract in a few easy-to-understand sentences that don’t require a law degree to comprehend using NLP.

Renewal Management

With artificial intelligence, you don’t have to worry about remembering every contract renewal. Your software can automatically flag when a contract is set to expire and initiate the renewal process. It’ll also notify your customer success or sales team, so they’re aware of the upcoming renewal date and can take appropriate action.

AI can also help you track key dates for compliance obligations and other critical milestones, like the end of a service term or payment due dates.

Benefits of Contract AI

Improved Accuracy and Risk Mitigation

AI reduces (and, in some cases, eliminates) the likelihood of human error in contract creation, review, and execution. Since it reads through your entire contract to identify words and phrases based on context, there’s no chance it’ll accidentally gloss over something like a human would.

Thanks to machine learning capabilities, contract AI can also help you make high-level decisions about which deals and partnerships to take on, which terms are most feasible for your business from a financial risk and profitability standpoint, and which clauses are most likely to result in disputes.

Time and Cost Savings

AI-powered contracting software streamlines sales and negotiation workflows, so your team is always working on the most relevant contracts while eliminating much of the clerical work. This reduces quote-to-cash time and the costs associated with contract negotiations, redlines, and approvals.

Enhanced Compliance and Legal Consistency

Further down the line, AI contracting tools’ ROI becomes even clearer. Noncompliance and poor contract management cost businesses around 9% of their total revenue (on average).

Let’s say your company does $10 million ARR. A 9% noncompliance risk means $900,000 in annual leakage. Every percentage point you shave off that equates to $100,000 in revenue loss.

By reducing noncompliance errors with AI solutions, you’re not just optimizing your finances and employee output. You’re also becoming more profitable by protecting your business from these expensive issues.

5 Types of AI-Based Contract Software

1. Contract Review and Analysis Tools

Contract review tools use AI to extract key data from contracts and compare it against your company’s policies, legal standards, and best practices. They can create abstracts of a contract, identify risks, pinpoint opportunities, and prompt decision-making.

2. Contract Automation Platforms

Contract automation software uses generative AI, templates, and resource libraries to create standard drafts of business contracts. The goal is to replace manual drafting with automation that’s faster, more accurate, and less prone to errors and biases.

3. Contract Lifecycle Management (CLM) Software

CLM manages the entire lifecycle of a contract, from creation to renewal/termination. It stores every version in a navigable, cloud-based contract repository with permissions-based access control. Based on keywords, clauses, and data points in agreements, it generates relevant data for automatic updates and alerts.

4. Intelligent Document Processing (IDP) Solutions

IDP focuses on extracting and processing relevant information from contracts and other documents. They use OCR, NLP, ML, RPA, and other AI technologies to review the agreement and extract information based on keywords, language patterns, formatting, dates, names, and other types of text-based contract data.

5. Predictive Contract Analytics Software

Predictive analytics tools use historical performance and market data to forecast outcomes of modifications, additions, or omissions of contract terms or the outlook of an entire agreement. They use AI to recognize patterns and make assumptions based on similar past events, with a degree of confidence for each forecast.

Challenges and Considerations in AI Contract Management

Data Privacy and Security

Business contracting software deals with sensitive business information, customer data, and legal terms that need to be kept confidential.

That said, AI makes data protection easier in several ways. Data masking, for example, removes or hides personal identifiers like names, addresses, and phone numbers, so a third party can’t use it to identify a person in the dataset.

2FA (two-factor authentication) and MFA (multi-factor authentication) add another layer of security, so only authorized users can access the software.

Bias and Risk of Discrimination

Since machine learning algorithms learn from human data, they can inherit biases that exist in society, even if unintentional. AI-powered contracting tools need to account for these issues and continuously monitor and update the algorithm to ensure fairness.

Ethical Use of AI in Contract Management

Ethics are probably the most widely discussed issue in AI. Aside from biases and data security, how a business uses its customer data, how transparent it is about data processing, and the potential impact on employees all need to be carefully considered when implementing a contract AI solution.

Integration with Existing Systems

Process automation is a huge part of why you’d invest in contract AI in the first place. But contract management tools don’t do all the work on their own. The reason they’re able to automate data entry and contract creation workflows is that they integrate with:

• CPQ software
• CRM systems
• Enterprise resource planning (ERP)
• Digital asset management (DAM)
• E-signature platforms

Before investing in any form of contract automation, take a look at your current tech stack, its integration capabilities, and the tools that work best together.

Future Trends in Contract AI

Advancements in NLP and Machine Learning

One of the most exciting advancements is the development of customized generative AI models. Unlike large, general-purpose models like GPT-4, custom models cater to specific industries and user needs, including sectors with highly specialized terminology like law, finance, and healthcare.

For contract management, this means AI tools can be more precisely developed to understand and process complex legal language.

Transfer learning — a technique where AI models apply knowledge gained in one domain to another — has also seen significant advancements. Businesses can use models trained in related fields (like general legal or business document analysis) and fine-tune them for specific types of contracts.

This accelerates the training process and reduces the need for large labeled datasets specific to each contract type.

Integration with Blockchain for Smart Contracts

This integration of AI and blockchain technologies will enable more sophisticated and autonomous contract management systems. The combination of blockchain’s secure, tamper-proof record-keeping and dynamic contract execution base, plus AI’s predictive and analytical prowess, will greatly enhance both the reliability and functionality of AI-generated contracts.

Increased Adoption and Industry-Specific Solutions

As AI technology becomes more advanced and its benefits become obvious, more businesses (and their employees) will adopt contract automation tools. We can also expect to see more industry-specific solutions tailored to the unique needs of various sectors such as healthcare, government, and finance.

Now, roughly one in three businesses and 45% of the US population say they’re using gen AI for at least one function. With a significant number of businesses planning to invest more in it in the coming years, it’ll eventually permeate every corner of business, including (for an increasing number of companies) contract management.

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