The progress made in AI and machine learning has ushered businesses into a new era of automation. Thanks to Generative AI and ChatGPT, the adoption has been fast, and contract workflow management has followed suit.
Contract management involves drafting, negotiating, reviewing, and executing contracts. Traditional contracting practices are slow and filled with bottlenecks. These bottlenecks result from factors such as manual tasks, a high volume of contracts, complex legal language, limited visibility into the contract lifecycle, and the need to keep up with updates in regulatory requirements. These cause delays, inefficiencies, and increased costs in contract management.
AI can contribute to each of the contract lifecycle stages and address the bottlenecks to streamline the entire contract workflow management, improving efficiency and reducing the time taken to complete tasks.
Despite the progress in AI, legal teams have hesitated to adopt it in contract management due to concerns about control, language precision, and trust in machine algorithms (read
Embracing ChatGPT in contract workflows with caution). Other concerns include reliability, data privacy, human judgment, compliance, and implementation challenges. However, we’ve come to a point where ignoring AI is no longer feasible.
By the end of this post, you’ll be able to identify different ways to use AI in your contract workflows and what to be cautious about.
How is AI changing contracts?
AI is changing how contracts are managed, bringing big improvements to different parts of the process, such as data extraction,
automation, language analysis, and insights. 1. Data extraction
Contract data extraction is manual and time-consuming, prone to errors and inconsistencies. Contract managers spend countless hours reviewing and manually inputting data into databases or spreadsheets.
Using natural language processing (NLP) algorithms, AI can analyze contract documents and extract relevant data points, such as contract dates, payment terms, parties’ names, contract values, and specific clauses.
The automated extraction process is faster and more accurate than manual data entry, reducing the risk of errors and inconsistencies. Contracts are a rich source of information, and AI can extract valuable insights from the extracted data. This enables better decision-making, risk analysis, and contract performance tracking.
Managing numerous contracts requires significant time and effort, leading to delays and potential errors. Automation efficiently handles a large volume of contracts and redundant processes. With AI, contract creation, review, and approval can be automated, reducing the time and resources required for these processes.
AI-powered systems can also automate follow-ups and reminders for contract milestones. This ensures important deadlines are not missed.
Contract storage is another area where automation can be applied. The traditional process involves physical filing systems or scattered digital repositories, which makes it challenging to locate specific agreements. AI-powered automation centralizes storage and provides intelligent search capabilities, enabling users to quickly find and access the contracts they need.
3. Language analysis
Contracts are laden with complex legal language, making it challenging for both legal and non-legal professionals to comprehend the terms and clauses accurately. AI tools now have the capability to analyze contract language and simplify it, ensuring better understanding and clarity.
During the review process, AI tools can identify potential issues, inconsistencies, or missing clauses, enhancing the quality and accuracy of contracts. AI-powered systems can also summarize lengthy contracts, extracting key insights and highlighting essential information.
4. Insights and analytics
Contract analysis requires extensive manual review, making it time-consuming and prone to human errors or oversights. Using ML algorithms, AI can detect potential risks within contracts. It can identify clauses that are non-compliant with regulatory requirements or unfavorable to the organization’s interests. By flagging these risks, AI empowers organizations to mitigate potential liabilities.
AI can analyze a large volume of contracts to identify patterns and trends. This enables organizations to uncover valuable insights regarding contract performance, supplier relationships, or customer behavior. For example, AI can identify common negotiation points or clauses frequently leading to disputes, helping organizations improve their contract drafting and negotiation strategies.
How is AI used in contract workflow management?
Contract intelligence uses AI to analyze and extract key information from contracts. It interprets contract language, identifies clauses, obligations, and risks, provides insights to support decision-making, and simplifies contract management processes.
But, why do we need AI in contract workflow management? The answer is simple - we encounter common challenges such as:
Changing laws and regulations Time-consuming nature of the process Complex legal language and terminology Effective identification and mitigation of risks Inconsistencies, misunderstandings, and errors Collaboration and management of multiple versions
AI and automation are all about making things better! They help us by reducing errors, improving quality, and speeding things up. Sometimes, they can even achieve outcomes beyond what humans can do.
Let’s take a look at how AI can change contracts
Automate manual tasks such as contract drafting, reviewing, and data entry. This reduces errors and enhances efficiency. Analyze contracts, extract key information, and identify patterns using natural language processing and machine learning. Improve visibility into the contract lifecycle by centralizing and organizing contract data, facilitating proactive management. Assist in compliance management by monitoring and analyzing regulatory updates to ensure adherence to standards. Enhance accuracy and consistency throughout the contract management lifecycle, minimizing risks and penalties. AI in contract drafting
Contract drafting is creating the initial version of a contract, including outlining the parties’ terms, conditions, rights, and obligations. AI can automate and simplify contract creation by analyzing existing contracts, extracting relevant clauses, and generating customized contract templates.
Here are some ways businesses can use AI in contract drafting:
Automate contract template generation based on existing contracts. Interpret complex legal language using NLP. Suggest standard and alternative clauses for customization. Identify potential risks and discrepancies in contracts. Optimize contract language for clarity and coherence. Automate review and proofreading for error detection. Monitor clauses for compliance with legal and regulatory requirements.
EY Law Survey in 2021 found that 57% of business leaders experience inefficiencies in the manual contracting process, directly impacting their revenue. With AI in the picture today, businesses can process data and create contracts in a simplified and expedited manner.
AI in contract drafting provides several advantages, including
streamlined handling of a higher volume of contracts within shorter timeframes, minimized creation and consultation costs, enhanced consistency and accuracy, reduced review time. AI in contract analysis and review
Contract analysis is the process of carefully examining and understanding the contents of a contract. It involves extracting important information, identifying key terms and clauses, and evaluating the contractor’s compliance with legal requirements. It helps businesses understand their contractual obligations, identify potential issues or opportunities, and ensure the contract aligns with their goals and legal requirements.
AI contract analysis uses language analysis, customizable rules, and machine learning to update, edit, and revise contracts. Some practical uses of AI in contract analysis are:
Summarize complex legal language through NLP. Score and assess anomalies for effective risk management. Extract data such as expiration dates, stakeholders’ names, jargon, etc. Ensure compliance and adherence to legal and regulatory requirements. Automate metadata analysis for improved organization and categorization. Provide a comparative analysis of contracts to highlight similarities and differences. Gartner says that by 2024, the manual effort required in contract review will be halved by adopting AI-powered contract analysis solutions. With AI, businesses can gain a competitive edge by saving time, reducing costs, and ensuring better contract governance and risk mitigation. AI in contract management
Contract management refers to managing contracts throughout their lifecycle, from start to finish. It involves drafting contracts, negotiating terms, tracking important dates, monitoring performance, ensuring compliance, and resolving disputes. It also means keeping all the contracts organized, ensuring everyone knows what to do, and proactively managing
contract renewals, amendments, and terminations.
AI in contract management helps legal teams track and review thousands of contracts quickly. Some of the applications of AI and automation in this step include:
Create a single, organized location for storing and accessing all contracts. Ensure adherence to contract terms and conditions by all parties involved. Streamline the process of contract amendments and contract renewals. Facilitate better communication and collaboration among stakeholders. Enable effective tracking and monitoring of contractual obligations. Simplify and speed up contract approval and signing procedures. Advantages of using AI in contract management
Imagine having a personal assistant that never tires, is always at your disposal, and can instantly analyze vast amounts of data—that’s AI. With its ability to simplify complex information, AI has become a valuable asset in automating contract management.
Top benefits include
1. Increased efficiency and productivity through automation
AI simplifies and standardizes contract management, giving organizations more flexibility and adaptability. By automating processes like data extraction and contract requests, AI speeds up procurement and shortens contract lifecycles, boosting productivity. It also helps identify risky clauses and alerts the team for review, improving process efficiency.
2. Reduction of manual errors and improved accuracy
Contracts contain important details such as dates, deadlines, terms, payment terms, termination clauses, and more. And going wrong with this information can lead to ambiguous clauses and non-compliance with legal requirements. AI in contract management can help minimize these errors by automating review processes, ensuring standardized language, extracting data intelligently, and checking for compliance, improving the accuracy and quality of contracts.
3. Enhanced risk management and compliance
AI enhances risk management and compliance by identifying and analyzing contract compliance terms. It enables proactive monitoring of changes in terms and conditions, helping organizations manage risks better. AI software also ensures the security of sensitive data. With AI, organizations can streamline compliance processes and achieve greater confidence in risk management.
4. Time and cost savings in contract management
Mistakes in contracts can have significant financial consequences for legal organizations. For instance, a poorly worded contract can lead to misunderstandings or disputes, resulting in costly litigation expenses. Non-compliance with regulatory requirements can lead to penalties or fines, impacting the company’s profitability. With AI, these risks can be mitigated. AI automation also saves time in tasks like data extraction, analysis, and drafting, further enhancing efficiency and minimizing the potential for mistakes.
Disadvantages of AI in contract management
While AI has made remarkable advancements, it still faces limitations in areas such as contextual comprehension, ethical decision-making, and handling unpredictability. There is a continued need for human involvement and oversight. Let’s look at the top disadvantages of AI in contract management.
1. Absence of specific regulations to govern AI tools
There needs to be more specific regulations to govern the use of AI tools in contract management. Without clear regulations in place, it becomes difficult to ensure consistency, fairness, and transparency in the use of AI tools, impacting the overall integrity of contracts. The absence of regulations also raises questions about accountability, as there are no established guidelines to monitor and govern the behavior and outcomes of AI tools used in contract management.
2. Requirement for highly skilled professionals
AI tools require the involvement of highly skilled professionals who are responsible for not only understanding the capabilities and limitations of AI tools but also ensuring their successful integration into existing processes. Smaller firms or organizations with limited resources may face challenges in accessing the necessary technical skills, making the adoption of AI tools less feasible or practical for them.
3. Challenges with bias and misinformation in AI systems
The training data used to teach AI algorithms can be biased, leading to biased outcomes. Misinterpretation of contract text and complex legal terms can also result in incorrect analysis. Algorithmic bias and inaccuracies in data extraction can further contribute to misinformation. Additionally, AI systems may struggle with understanding industry-specific context. To address these risks, human oversight is crucial to review and validate AI outputs, ensuring accuracy and fairness.
4. Ethical considerations in AI-based contract management
As AI assumes greater decision-making responsibilities, particularly in contract drafting and analysis, ethical concerns gain prominence. Recent technological advancements have raised apprehensions about the potential for AI systems to cause more harm than good to society. Ethical considerations include determining the authorship of AI-generated contracts and addressing the ongoing threat of cyber-attacks. Another ethical consideration is the concern of job displacement as AI technologies automate certain tasks. It is crucial to find a balance between leveraging AI for efficiency and productivity gains while ensuring that it complements human capabilities and creates new opportunities.