The Impact Of Artificial Intelligence On Commercial Contracts
Author: LawSphereX
Category: Technology, Cyber & Privacy
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THE IMPACT OF ARTIFICIAL INTELLIGENCE ON
COMMERCIAL CONTRACTS
Aarthi D Asrani, LL.M (Corporate and Financial Law), O.P Jindal Global University.
ABSTRACT
Integration of Artificial Intelligence in commercial contracts represents a paradigm shift in drafting, reviewing, and enforcing legal agreements. Conventionally, managing contracts has involved time-consuming scrutiny and interpretation by humans, but AI technologies, particularly those that leverage NLP and ML, are also increasingly transforming processes for higher accuracy, efficiency, and cost-effectiveness than ever before. This paper discusses the varied use of AI in current contract management and analyzes its impact on the legal sector. AI-powered drafting of contracts employs past data and contract templates to automate the generation of legal documents. Such software could produce boilerplate clauses, and even apply them according to customizing specific requirements, saving lawyers' time spent in repetitive work.
This may increase efficiency, but one needs to consider the risk of bias that comes along with the data the AI model is trained on. In addition, the application range of AI tools remains mainly at standard contracts, with complex and bespoke ones still requiring substantial human guidance. The partial automation thus makes it worthwhile to question how much AI can substitute human judgment in drafting agreements that normally depend on in-depth legal nuances. Advances in AI have also revamped the contract review and due diligence process, which were extremely time intensive. NLP-based tools can scan voluminous contracts, flag unusual clauses, identify potential risks, and ensure compliance with legal standards. This capability enables businesses to accelerate due diligence processes, especially in large-scale transactions, mergers, and acquisitions.
Automated review of large volumes of documents by AI reduces the risk of human error and facilitates consistency across contracts. However, the dependability of AI for contract review throws up issues like interpretability and transparency. Legal professionals are held accountable for ensuring that AI systems function within the lines of ethics and law while establishing appropriate mechanisms to correct errors and omissions on the part of the tool.
The use of AI is also forth in enforcing contracts through the determination and management of breaches or non-compliance. Smart contracts, driven by blockchain and AI, feature self-executing contracts where the terms and conditions can be automatically enforced when certain predefined conditions are met. This innovation may smooth out enforcement by getting rid of intermediaries and reducing disputes. However, the rigid nature of smart contracts raises legal challenges, especially when, according to the situation, modifications are required in a contract or even human intervention takes place. The inflexibility of AI in handling such instances raises concerns about its suitability for all types of commercial agreements. Generally, widespread AI adoption in contract management raises very significant implications for legal accountability.
With AI taking a bigger role in the entire contract lifecycle, responsibility for mistakes or breaches becomes an increasingly pressing question. This is because such legal systems or frameworks are relatively more strained in having determinable liability when they involve AI in drafting, reviewing, and enforcing contracts. The paper will relate to regulatory approaches and ethical factors that pinpoint a need for collaboration, blending human expertise and the application of AI systems. In conclusion, the influence of AI on commercial contracts will bring the benefits of higher accuracy, along with more efficiency, yet will be surrounded by challenges regarding legal accountability, data bias, and the overall restraint of automation in more complex legal cases.
This paper argues for a balanced approach that advances AI while the supervised role of human beings remains central to the contract management process. Keywords: Artificial Intelligence (AI), Commercial Contracts, Contract Drafting, Contract Review, Legal Accountability, Smart Contracts, Natural Language Processing
(NLP),
Machine Learning
(ML),
Contract Enforcement, and Automation in the Legal Industry.
INTRODUCTION
Artificial Intelligence is, of course, one of the revolutionary technologies of our times-the face of which has changed various industries, and the legal profession is no exception to this phenomenon. Traditionally, what was required was labor-intensive intense human oversight: drafting, reviewing, and then enforcing commercial contracts. But all this will change through the swift integration of NLP and ML-based AI technologies into legal workflows: the contract management process will be revolutionized. From automating the creation of contracts to reviewing legal documents and facilitating enforcement through smart contracts, AI is reshaping the future of commercial agreements. This paper examines the role of AI in contract management and explores its implications for accuracy, efficiency, and legal accountability. Within legal applications, interest in AI has recently picked up pace.
These are developments at the heels of advanced technology and the ever-increasing quest for more streamlined legal workings. The use of AI could significantly reduce the time and cost associated with contract related affairs. It can automate repetitive work such as contract drafts and due diligence reviews for the lawyers to be able to dedicate their resources to more strategic and elaborate matters of contract negotiations and dispute resolution. However, as clear as it is in terms of efficiency and accuracy, the application of AI-driven tools is not without challenges. Some of the issues relate to data bias, interpretability, and the inflexibility of AI systems in dealing with complex legal situations. AI in contract drafting: Some of the major applications where AI can be seen to have made good promises include contract drafting.
Traditional contract drafting is always a painstaking exercise; the drafting of clauses, terms, and conditions depends on legal precedents and the needs of the specific parties involved. Contract drafting AI tools use large datasets of historical contracts and legal documents to generate standardized agreements with minimum human intervention. It is possible to have these systems pull and modify relevant clauses, even flag potential issues based on existing standards. This reduces the time required to draft a contract and minimizes the risk of human error, which is extremely costly in the legal merits of any dispute. Still, these benefits notwithstanding, AI currently can only draft a standard or routine agreement. Such agreements include service contracts or non-disclosure agreements. When the
agreements become more complex and require significant tailoring and an understanding of the parties' intentions in depth, they lie beyond what most AI systems can currently do. Another concern is that of bias in AI-driven drafting tools, especially with biased or incomplete datasets used to train such models. Increasingly making these systems fair, transparent, and accountable remains a challenge. AI in contract review and due diligence: The review of contracts is another area where AI has been transformative. Legal professionals have, for so long, dug through contracts to identify potential risks, inconsistencies, and compliance issues. Tools powered by AI and especially NLP are now capable of automating large portions of this process. These tools can quickly scan documents, flag problematic clauses, and ensure compliance with legal regulations.
Accelerating the review process by AI provides a means for faster transactions, more so in mergers and acquisitions, where volumes of contracts need to be reviewed within tight time constraints. This is perhaps one of the core advantages by which AI works on contracts: it ensures consistency of documents. Standard terms and conditions can be enforced through all the contracts for a company with an AI tool, minimizing the possibility of discrepancies that could lead to legal disputes. However, as with drafting, reliance on AI for contract review presents challenges. AI systems, while highly efficient at identifying surface-level issues, may not fully understand the intricate nuances of legal language and intent. Legal professionals must, therefore, remain involved in the process to ensure that AI’s output aligns with the overarching legal strategy and intent of the parties involved.
AI in contract enforcement: AI is also increasingly playing a role in enforcing contracts, even through the incorporation of smart contracts. These are self-executing contracts with terms written directly into code that enable automatic enforcement once certain predefined conditions have been met. Smart contracts, usually operating within blockchain environments, have the potential to eliminate the need for intermediaries in enforcing contracts thus reducing the time and cost associated with dispute resolution. For example, under conditions of arrival, a smart contract might automatically trigger rent payments. As such, it may pay the rent when a due date occurs in the commercial lease agreement.
However, smart contracts also have their disadvantages. The very toughness of such a contract disqualifies them from being involved in contracts that require flexibility or adaptability in uncertain cases. As opposed to traditional contracts, which could be renegotiated and altered as conditions change; smart contracts operate based on their code that may elicit unintendedness hence becomes questionable whether AI can be allowed in more complex or dynamic commercial relationships as it involves human judgment in certain cases.
ANALYSIS:
The integration of Artificial Intelligence (AI) into commercial contract management is revolutionizing the legal industry by enhancing efficiency, accuracy, and cost-effectiveness. However, this transformation is accompanied by several challenges and implications, particularly concerning legal accountability, data bias, and the limitations of AI systems in handling complex legal tasks. This analysis considers the potential benefits and challenges of AI in drafting, reviewing, and enforcing contracts and addresses the broader implications of these technologies for the legal profession and commercial practices. AI in contract drafting: Efficiency and limitations: One of the most striking developments in the legal services sector relating to contract drafting is AI drafting.
Traditional drafting of contracts is laborious and requires considerable time and repetition, while still paying heed to minute details. AI tools with NLP capabilities can generate contracts quickly, developing standard clauses from large datasets of existing contracts. 1 These tools both streamline the time it takes for contractual production and negate the opportunity for human error, which is pricey if not caught. Examples include language inconsistency and contradictory clauses. With AI these can be caught and corrected by the system, improving the overall quality and reliability of the contract. However, the use of AI in contract drafting also has its limitations.
While AI can shine in the drawing of standard templates such as an NDA or a simple service agreement, more complex and customized contracts that require very deep comprehension of what the parties intend and some peculiarity in the legal context call for human intervention. Most complex, nuanced legal 1 Alon Jacovi, Ana Marasović, Tim Miller and Others, “Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI”, https://dl. acm. org/doi/abs/10. 1145/3442188. 3445923 accessed 13 May 2024.
languages with circumstances requiring extensive negotiations or those with dynamic business relationships are suited more for humans than AI expertise, which relies solely on predefined sets of rules and historical data. There is the risk of biased AI-generated contracts. The training of AI systems has been done in historical datasets, which reflect the biases contained in those datasets. As such, in the case where the predominant contracts were included mainly in that dataset, the AI tool might produce biased contracts towards those norms, and miss precious legal considerations applied to other contexts in contrast. The allocation of fair and just treatment is particularly relevant when applying AI-driven contract drafting, especially in a situation where one party may be adversely disproportionately affected compared to the other. AI in Contract Review: Speed and Consistency vs.
Nuance: The area of contract review is another traditionally labor-intensive task, where AI has significantly enhanced the process. Through its analysis, AI-powered tools for contract review can absorb huge quantities of legal documents easily and deliver your desired outcome in the same way. It is only these systems that are the game-changers in high-volume contract production industries like real estate, finance, and mergers and acquisitions. AI simplifies and lightens the burden of legal professionals in this process of detection of unusual clauses, potential risks, or compliance issues, hence increasing the likelihood of contract uniformity. Among the most important functions of AI in contract analysis is the ability to scan hundreds of contracts speedily.
Performing due diligence is often carried out on a massive scale when large transactions take place like mergers or acquisitions; often thousands of contracts have to be reviewed within very short periods by law teams. The AI system can speed up this process by pointing out key issues to enable lawyers to focus on what is most crucial in a transaction. This not only saves much time but also cuts down the risk of human oversight that may creep in when, say, legal professionals are under pressure. With these benefits, however, AI's role in the review of contracts still has limitations. AI is great at identifying a pattern, and finding surface-level concerns, but is not usually able to interpret the nuances in language often expressed in legal documents.
Legal agreements are frequently rife with intricate clauses that require deep knowledge of a business relationship, and the parties involved. Since the AI system is based on predefined rules and algorithms, the subtleties cannot
be captured adequately. In consequence, human oversight remains necessary, since the output generated by AI needs to meet the general legal strategy and business goals. The interpretability of the AI system also poses another challenge. While AI tools might flag some problematic clauses, they do not automatically explain why that clause is problematic, so legal professionals must interpret the findings themselves, which is where a lack of transparency brings in accountability since if a critical issue is overlooked or a clause is misinterpreted by an AI tool, then whoever used that tool becomes accountable for the outcome. Therefore, legal professionals must be able to rely on the output of the AI while having room to override the system if necessary. AI in Contract Enforcement: The Rise of Smart Contracts: AI is also advancing in contract enforcement, particularly with smart contracts.
Smart contracts are programs of instructions that contain various terms written directly into code with the ultimate objective of having contractual obligations automatically executed upon predefined conditions. 2 The general implementation of this type of contract is through blockchain platforms and could potentially revolutionize contract enforcement by eliminating the middleman while drastically lowering the associated cost and duration of dispute resolution. For example, in a commercial tenancy, a smart contract could automatically trigger payment of rent on due dates, without the need for human intervention; and in supply chain agreements, smart contracts could ensure automatic payments once goods are delivered and accounted for.
Smart contracts minimized disputes and greatly enhanced the efficiency of enforcement of the contract because they made it impossible to disagree on the terms of the agreement. However, the rigidity of smart contracts poses daunting legal challenges. While traditional contracts allow renegotiation or a change considering changes in circumstances, smart contracts are strictly executed following their code. This inflexibility may often result in unforeseen consequences, especially in complex commercial relationships where unforeseen events may require adjustments to the contract. For instance, if a supplier is held up owing to some natural calamity, a regular contract could allow for renegotiations or more time for
2 Simon Chesterman, “Artificial Intelligence And The Limits Of Legal Personality”,
https://www.cambridge.org/core/journals/international-and-comparative-law-quarterly/article/artificialintelligenceand-the-limits-of-legal-personality/1859C6E12F75046309C60C150AB31A29 accessed 02 June 2024.
delivery. The smart contract, however, would strictly abide by the original agreement and such could lead to legal tangles. Smart contracts raise potential questions about legal liability. By their self-executing nature, the question of fault arises when and if things do indeed go wrong. A mistake in the code that determines the smart contract or a lack of foresight in the consideration of a critical component of the agreement creates an issue of responsibility. In this way, current frameworks of law are not well-suited to the design of responsibility in an environment where AI enforces a contract. Legal Accountability and Ethical Considerations: In this modern age, with the widespread use of AI in creating, reviewing, and enforcing contracts, questions of legal responsibility have come to the fore. Who is liable if an AI makes a mistake in drafting a contract or reviewing a contract?
In traditional responsibility, liability is premised on accountability. That is, legal professionals are responsible for what they write. This is not the case under the new responsibility paradigm involving AI. There is also the problem of data bias, again which can be very problematic because with biased or incomplete datasets, an AI system can produce biased contracts that will potentially disadvantage one party over the other. This becomes particularly problematic where there are inherent power imbalances in industries or jurisdictions. The use of AI technologies must be kept in mind as fair and transparent with a mechanism to deal with potential biases.
CONCLUSION:
AI has dramatically changed the legal industry while it has been infused into the management of commercial contracts. It bears a benefit in terms of efficiency, accuracy, and cost-benefit. Two of the most common AI-based tools used include NLP and machine learning. The truth is that these tools have come quite handy in automating much of what was previously the job of legal practitioners: drafting, reviewing, and enforcing contracts. These advances reduce time and the labor of humans in contract management, especially with common contracts and massive deals that require accuracy and consistency. However, while AI helps make all the differences it makes in managing contracts, it raises exclusive challenges in handling complex legal jargon, nuanced negotiations, and deeper aspects of legal responsibility and biases in data.
One of the salient advantages that AI will bring to contract management is the speed at which
AI can automate the process of drafting. Tools for this technology can quite rapidly extract template standard contracts from vast databases of historical contracts and legal templates to generate NDAs or service contracts, thus taking less time and with fewer error possibilities to prepare those documents. Furthermore, AI can also promote uniformity in various agreements through the inclusion of essential clauses and the proper formulation thereof. However, the utilization of AI is restricted when it deals with drawing complex, tailor-made contracts. Contracts that require a great understanding of what parties want or complex negotiations are mainly beyond what the AI system could currently solve, considering that it uses rules and past data to respond.
Of course, here, too, general human knowledge will always be relevant in such matters, especially in the interpretation of ambiguous legal jargon or otherwise modifying terms of a contract according to fluctuating business relationships. AI applies its transformative role in contract review, especially for high volumes- M&A as it deals with very large numbers of contracts that must be analyzed against compliance, risks, or inconsistencies in their background. This can be done quickly by AI-based review tools scanning documents, identifying problematic clauses, and flagging out the areas of concern for the legal team. This capability massively accelerates the process of due diligence, avoiding bottlenecks and speeding up transactions. However, this is exactly where AI's weaknesses in understanding ambiguous or context-specific language become critical.
While AI can identify risk, it may be less capable of identifying a more profound legal implication that would require an understanding from a holistic perspective of the business relationship or transaction. Therefore, human oversight becomes necessary to determine whether AI insights are getting the organization closer to its strategic goals and toward intended legal intent. It is through contract enforcement that AI is applied, because of self-executing pieces of code written as an agreement and automatically triggering actions following preset conditions. Such contracts, usually deployed on blockchain platforms, make enforcement easier by reducing the interposition of unnecessary third parties and by speeding up the payment or deliveries, for example. Smart contracts, however, also cause legal hardening.
Since smart contracts are rigid and function strictly according to their code, the atypical conditions such as the sudden change in requirements cannot be accommodated or renegotiated as the case is with traditional contracts. Such rigidity has characterized it as less well suited for complex or constantly changing
commercial relationships. There are also wider implications in terms of questions around accountability and ethics: Who is liable if the AI system drafting or reviewing a contract makes a mistake? The existing legal framework only is inadequate to assign responsibility when AI is invoked in the contract lifecycle. Moreover, bias in AI models due to the training of biased datasets increases ethical considerations, especially in industries where contracts affect power relations or equity. Thus, making AI systems fair, transparent, and accountable becomes a necessary way to prevent such risks. In conclusion, while AI generally presents the most efficiency and accuracy in contracts relating to management, its limitations in dealing with complex legal scenarios and the ethical challenges it introduces point to a balance.
The human choice for legal expertise should therefore be enhanced rather than substituted by AI. The near future will thus see routine tasks assigned to AI and human professionals oversee, interpret, and apply these tools responsibly so that legal processes, in this highly AI-enriched landscape, are fair, flexible, and just due to the very role of human judgment.
REFERENCES:
Alon Jacovi, Ana Marasović, Tim Miller and Others, “Formalizing Trust in Artificial Intelligence: Prerequisites, Causes, and Goals of Human Trust in
AI”,
https://dl.acm.org/doi/abs/10.1145/3442188.3445923. Simon Chesterman, “Artificial Intelligence And The Limits Of Legal Personality”, https://www.cambridge.org/core/journals/international-and-comparative-lawquarterly/article/artificialintelligence-and-the-limits-of-legalpersonality/1859C6E12F75046309C60C150AB31A29.