Generative AI in customer success: Integration, use cases, challenges, ROI, and future outlook

Effective contract management is critical for businesses, as it lays the groundwork for consistent compliance, operational efficiency, and successful negotiations. Contracts govern almost every business transaction, but managing them is no simple task, especially for large organizations with complex agreements across multiple departments. Streamlining contract management can not only reduce operational friction but can also make a notable impact on a company’s financial performance. In fact, research by World Commerce & Contracting indicates that strong Contract Development and Management (CDM) practices could save a company an average of 9% of its annual revenue—an amount that can significantly boost its bottom line.

A recent report from the Thomson Reuters Institute highlights the increasing interest in Generative AI within the legal field, indicating that a substantial majority of legal professionals (81%) see the potential for this technology to enhance their work. This trend is especially pronounced in law firms and corporate legal departments, showcasing a widespread acknowledgment of GenAI’s ability to create considerable value and elevate client services.

One of the primary domains where Generative AI can have a significant impact is contract management. This technology can streamline processes such as drafting, reviewing, and analyzing contracts while also extracting critical insights and assessing potential risks. The implications of this capability could fundamentally transform the management of contracts.

This article explores how generative AI is reshaping contract management practices, including its role in contract drafting, review, negotiation, and analysis. It examines the benefits, challenges, and practical applications of GenAI in this field, offering a comprehensive look at how businesses can leverage generative AI to enhance contract performance and drive better business outcomes. This article delves into the evolving landscape of GenAI in contract management and the unique advantages generative AI platforms like ZBrain offer to organizations seeking to implement these transformative technologies.

• Understanding generative AI
• The current landscape of GenAI in contract management
• How does generative AI work in contract management?
• Approaches to integrating generative AI into contract management systems
• Why is ZBrain the ideal platform for contract management?
• Key use cases of generative AI for contract management systems
• Evaluating the ROI of generative AI in contract management
• Challenges and considerations in implementing generative AI for contract management
• Future outlook of generative AI in contract management
• Optimizing contract management with ZBrain: a full-stack GenAI orchestration platform
• Benefits of ZBrain for contract management

Understanding generative AI

Generative AI is a branch of artificial intelligence focused on creating new content across various formats such as text, images, audio, video, and even code. Unlike traditional AI, which is primarily designed to analyze data and make predictions, generative AI identifies patterns and relationships within large datasets to produce original outputs.

Generative AI has brought remarkable efficiency to various forms of content creation, automating tasks that once required significant time and effort. In business communications, GenAI can generate personalized and coherent emails, reports, and other text-based materials, allowing professionals to focus on core tasks instead of spending hours on drafting. In legal contexts, GenAI-powered tools are particularly useful for contract generation and review, analyzing legal language patterns to produce consistent and accurate drafts while reducing human errors.

Beyond written content, generative AI is transforming visual and multimedia content creation as well. AI models can generate photorealistic images, stylized visuals, and even videos from text prompts or pre-existing data, catering to the marketing, advertising, education, and entertainment industries. Tools like OpenAI’s DALL-E 2 have made it possible to create engaging visuals from simple text descriptions, enabling businesses to quickly produce tailored ads or product visuals that resonate with their audiences. In education, these AI-generated visuals serve as effective aids, enhancing the learning experience for students.

Generative AI has also advanced into creative fields like music composition and software development. AI-generated music, adaptable to various genres, is used in media production, entertainment, and even personal projects, with tools such as OpenAI’s Jukebox creating original songs across a spectrum of musical styles. For software development, generative AI can assist programmers by generating code snippets or entire functions based on specific requirements. AI can also analyze codebases to identify bugs, suggest fixes, and optimize code for improved performance, significantly accelerating development processes.

In breaking language barriers, generative AI facilitates real-time and accurate translations, supporting seamless communication across cultures. Advanced GenAI models, like Google Translate and DeepL, have become increasingly reliable, aiding businesses, governments, and academics with accurate translations that retain critical nuances, especially in technical or academic settings.

Generative AI also excels at summarizing lengthy documents, helping professionals quickly grasp essential insights. By condensing long reports, research papers, or legal documents, AI allows users to access the most critical information without sifting through extensive text. For instance, Google’s Gemini efficiently processes large amounts of text to create actionable summaries. This capability is highly valuable across sectors, from summarizing key clauses in legal documents to condensing complex research papers in healthcare, thereby streamlining decision-making processes across various industries.

How does generative AI work?

Generative AI works by leveraging advanced machine learning models, particularly deep learning and neural networks, to analyze large datasets and recognize complex patterns within the data. The process begins with training these models on vast amounts of data, whether it be images, text, or audio. Through this training, the AI learns to identify relationships and structures within the content, allowing it to generate new outputs that resemble the data it was trained on. For instance, a model trained on images learns to understand visual elements like shapes, textures, and colors, enabling it to create new, realistic images. Similarly, language models are trained on large text corpora, allowing them to understand grammar, sentence structure, and context and subsequently generate coherent text.

Generative AI doesn’t follow predefined rules but continuously learns from feedback, refining its outputs with each iteration. This process allows the AI to become increasingly accurate and creative over time. By adjusting its internal parameters based on user input or corrections, it can improve its content generation capabilities, producing more nuanced and sophisticated results. Whether generating new images, music, code, or text, generative AI synthesizes data patterns and adapts, making it highly effective in creative and content-driven tasks.

The current landscape of GenAI in contract management

The landscape of GenAI in contract management is rapidly evolving, characterized by a surge in adoption and increasing complexity. For years, AI-driven tools have been employed to automate tasks such as data extraction and clause identification. However, recent advancements in natural language processing (NLP) and machine learning (ML) are ushering in a new era of more comprehensive solutions. GenAI is now capable of analyzing contracts for risks and compliance issues, identifying potential problems, and facilitating improved negotiations.

Emerging platforms are designed to automatically redline contracts, generate legal documents, and even forecast future disputes. This transformation is largely driven by a growing demand for efficiency and accuracy in contract management as businesses increasingly acknowledge AI’s potential to minimize errors, optimize workflows, and enhance overall outcomes.

According to Gartner, by 2027, 50% of organizations will adopt AI, particularly GenAI solutions, for contract risk analysis and editing to aid in supplier negotiations. This statistic highlights the significant influence GenAI is having on contract management, especially in procurement processes. As businesses begin to leverage GenAI solutions—ranging from automating mundane tasks to providing valuable insights and enhancing decision-making—the contract management landscape is poised for further transformation.

How does generative AI work in contract management?

Generative AI in contract management utilizes natural language processing (NLP) to interpret and understand the often complex language found in legal documents. The process unfolds through several key steps:

1. Document analysis: GenAI models, trained on extensive datasets of contracts, use NLP to parse and comprehend legal documents. These algorithms can detect specific legal terminology, clauses, and even subtleties within the contract language, enabling them to understand the document’s overall structure and intent.
2. Key term identification: After analyzing the document, GenAI identifies essential elements such as key terms, clauses, dates, names, and other crucial details. This allows the system to extract critical information and highlight sections that need additional review or adjustments.
3. Task automation: Once the AI identifies key terms, it can automate various tasks, including:

• • Flagging potential legal risks: GenAI can detect clauses or terms that may present risks, offering recommendations for resolution.
  • Suggesting contract revisions: Based on analysis, it provides suggestions for improving contract clarity or compliance.
  • Redlining: GenAI can automatically mark up contracts, suggesting edits for more effective communication.
  • Sending reminders and alerts: It can set notifications for key dates, deadlines, and other important milestones, ensuring timely action.
  • Stakeholder notifications: Specific stakeholders can be alerted based on contract terms or changes.

4. Continuous learning and improvement: Over time, the GenAI system refines its capabilities through feedback and new data. This continuous learning improves the AI’s performance, ensuring more accurate and insightful contract analysis and management over time.

Generative AI acts as a powerful assistant for legal teams, efficiently handling time-consuming tasks such as analyzing and extracting data from contracts. Automating these processes and offering valuable insights enables legal professionals to focus on higher-level strategic activities, ultimately improving the overall efficiency and accuracy of contract management.

Approaches to integrating generative AI into contract management systems

There are several approaches organizations can take to incorporate generative AI into their contract management systems, each offering different levels of customization, flexibility, and technical requirements:

1. Custom AI stacks

This approach involves developing a tailored AI solution specific to an organization’s needs and infrastructure. Custom AI stacks provide high flexibility, allowing for deep customization to address unique contract management requirements and seamlessly integrate with legacy systems. While this approach can deliver a bespoke solution, it requires substantial technical expertise, resources, and ongoing maintenance, making it more suitable for large enterprises with dedicated data science teams and extensive IT support.

2. AI point solutions

AI point solutions are standalone tools designed to address specific aspects of contract management, such as data extraction, clause analysis, or redlining. These solutions offer targeted functionality and can be easily incorporated into existing workflows without significant disruption. Point solutions are generally more cost-effective and require less technical knowledge than custom AI stacks, making them an attractive option for businesses with limited IT resources or those needing to automate specific parts of the contract management process.

3. Fully-integrated platforms (e.g., ZBrain)

Fully integrated platforms offer a comprehensive solution for incorporating generative AI across the entire contract management process. Platforms like ZBrain combine advanced natural language processing (NLP), machine learning (ML), and generative AI models to automate and optimize tasks throughout the contract lifecycle. These platforms provide a holistic, user-friendly approach that benefits both legal and business teams. Key features often include:

• Advanced knowledge base: Efficiently storing, managing, and retrieving contract data, including legal clauses, documents, and historical agreements, for easy reference and use.
• Low-code development: Allowing users to build custom applications through a low-code interface, reducing the need for extensive programming skills.
• AI agents: Automating tasks like data extraction, contract review, and even web scraping. AI agents serve as virtual assistants, handling routine tasks while freeing up legal teams to focus on strategic decision-making and higher-value work.

Fully integrated platforms streamline the entire contract management process and eliminate the need for deep technical expertise, offering an accessible solution that addresses all contract management needs in one place.

4. Choosing the right approach

The best approach to integrating generative AI into contract management depends on the organization’s specific needs, available resources, and goals. Large enterprises with significant technical capacity may benefit from custom AI stacks that provide tailored solutions. Organizations looking for a simpler, more focused approach to automate individual tasks may prefer AI point solutions. For companies seeking a comprehensive, user-friendly solution across the contract lifecycle, fully integrated platforms like ZBrain offer a robust and accessible option, allowing for broad AI integration without requiring extensive technical knowledge.

Why is ZBrain the ideal platform for contract management?

ZBrain stands out as an ideal platform for contract management due to its comprehensive suite of features specifically designed to address the complexities of legal documentation. Its advanced knowledge base ensures secure storage and quick access to a wide range of contract data, including legal clauses, documents, and historical agreements. This allows for accurate analysis of contracts, helping users identify key clauses, spot potential risks, and address compliance issues effectively.

One of ZBrain’s major strengths lies in its low code interface. This tool allows users to create custom applications without needing programming skills, automating tasks such as contract drafting, redlining, negotiation, and execution. ZBrain also integrates multiple large language models (LLMs), enabling the platform to support contract creation in various languages, simplify complex legal documents into summaries, and even anticipate potential disputes before they arise.

Additionally, ZBrain’s AI agents serve as virtual assistants, automating repetitive processes like data extraction and contract review. This automation frees up legal teams to focus on more strategic initiatives, enhancing productivity and decision-making. By combining powerful AI-driven capabilities with an intuitive, user-friendly design, ZBrain simplifies the entire contract management process, reducing errors, improving efficiency, and delivering tangible business benefits across the contract lifecycle.

Key use cases of generative AI for contract management systems

Generative AI is transforming contract management by automating complex tasks such as drafting, reviewing, and risk assessment, helping legal teams streamline their workflows. Below is an overview of key use cases for generative AI in contract management and how ZBrain enhances these processes.

ZBrain’s advanced GenAI capabilities empower businesses to streamline their contract management processes, improving accuracy and compliance. With its wide range of applications, ZBrain ensures more efficient contract workflows, making it a powerful solution for modern contract management needs.

Evaluating the ROI of generative AI in contract management

Generative AI offers significant potential to transform contract management, but its value must be substantiated with clear evidence of its impact. Accurately assessing the return on investment (ROI) for generative AI is essential for demonstrating its effectiveness and validating its integration into contract management processes.

How to assess ROI for generative AI in contract management

To determine the ROI of generative AI in contract management, start by identifying the key cost savings and revenue enhancements it produces. First, quantify the time and resources currently allocated to manual contract tasks, including drafting, reviewing, analyzing, and negotiating. Next, estimate the savings in time and costs achieved through automation using generative AI. For instance, consider reductions in labor hours, the minimization of manual errors, and faster turnaround times facilitated by AI-driven automation tools. Additionally, assess any revenue growth or cost savings derived from enhanced contract terms, reduced risk, and improved compliance driven by AI insights. By contrasting these financial benefits with the initial investment in generative AI technologies, a clear ROI can be established for your organization.

Illustrations of ROI from ZBrain implementations

• Reduced operational costs
  • Use case: Automating the review and analysis of contracts.
  • ROI metrics: Lower labor costs, reduced time on manual reviews, and fewer errors.
  • Example: ZBrain can automate the analysis of numerous contracts, significantly cutting down the time and resources needed by legal teams, leading to considerable cost savings and allowing teams to concentrate on higher-value tasks.
• Enhanced customer satisfaction
  • Use case: Speeding up contract processing and improving clarity.
  • ROI metrics: Shorter deal closure times, enhanced customer experience, and increased customer retention.
  • Example: By swiftly generating contract drafts, ZBrain enables businesses to close deals more rapidly and create a smoother customer experience, which can result in improved customer satisfaction and loyalty.
• Accelerated decision-making
  • Use case: Producing insightful reports for contract analysis and risk evaluation.
  • ROI metrics: Reduced time for decision-making, better outcomes in contract negotiations, and improved risk management.
  • Example: ZBrain provides legal teams with real-time analytics, empowering them to make informed decisions regarding contract negotiations, compliance, and risk mitigation, leading to improved outcomes and increased profitability.

Looking beyond the numbers

While quantifying ROI through tangible metrics is vital, it is equally important to consider the qualitative advantages that generative AI brings. These include:

• Increased efficiency: Allowing legal teams to focus on more strategic initiatives.
• Enhanced accuracy: Minimizing errors and improving overall contract quality.
• Improved compliance: Reducing legal risks and ensuring adherence to relevant regulations.
• Competitive edge: Gaining a significant advantage through the capabilities of AI.

By blending the measurable advantages of cost savings and increased revenue with the intangible benefits of enhanced efficiency and informed decision-making, generative AI can significantly contribute to the success and growth of your business.

Challenges and considerations in implementing generative AI for contract management

Although generative AI offers substantial opportunities for enhancing contract management, its implementation involves several challenges and important considerations:

• Data quality and security: The performance of generative AI models relies heavily on the quality of the data used for training. Inaccurate or incomplete data can lead to biased or erroneous outputs, undermining the effectiveness of the AI system.
• Bias and fairness: AI models can inadvertently incorporate biases from their training datasets, potentially leading to unjust or discriminatory results in contract management processes.
• Explainability and transparency: Generative AI models are often perceived as “black boxes,” making it difficult to trace how they arrive at specific conclusions. This lack of transparency can reduce user trust and hinder widespread adoption.
• Human oversight and validation: It is essential to view generative AI as a complement to human judgment rather than a replacement. Human oversight is critical to ensure that AI-generated outputs align with organizational values and objectives.
• Integration and scalability: Incorporating generative AI into existing contract management frameworks can be intricate and may necessitate specialized technical skills. Additionally, scaling these AI solutions to handle large volumes of contracts poses its own set of challenges.
• Legal and ethical considerations: The legal and ethical ramifications of utilizing GenAI in contract management are continually evolving. Concerns regarding data privacy, intellectual property rights, and potential liability must be carefully examined and addressed.

By thoughtfully addressing these challenges and implementing effective solutions, organizations can leverage the transformative capabilities of generative AI to achieve more efficient, accurate, and reliable contract management.

Future outlook of generative AI in contract management

The swift advancement of generative AI is set to transform contract management, expanding the possibilities and redefining how organizations handle legal agreements. Here’s a look at what the future may hold:

• Improved language comprehension and generation: Generative AI models are rapidly enhancing their ability to comprehend and generate intricate legal language, often surpassing human understanding. This evolution will lead to contracts drafted with exceptional accuracy, capturing the nuances of legal terminology and integrating specific clauses with remarkable precision.
• Hyper-personalized contracts: The future promises contracts that are hyper-personalized to meet individual needs and contexts, eliminating generic agreements. Generative AI will adjust contract terms dynamically based on specific situations, utilizing extensive datasets and historical interactions to create truly tailored agreements.
• AI-driven contract negotiation: In the future, AI-powered negotiation assistants could analyze contracts in real-time, pinpoint leverage points, and suggest optimal counter-offers. This innovation will transform negotiations from subjective art forms into data-driven sciences, ensuring organizations secure the most favorable terms.
• AI-powered Contract Lifecycle Management (CLM): The entire contract lifecycle—from drafting and reviewing to execution, renewal, and termination—will be streamlined by AI-enhanced CLM platforms. This advancement will result in faster turnaround times, fewer errors, and increased efficiency at every stage.
• Integration with other business systems: Generative AI will facilitate seamless integration with various business systems, including CRMs, ERP, and accounting software. This interconnectedness will provide a comprehensive view of contract data, empowering organizations to make informed decisions and optimize cross-departmental operations.
• The growth of LegalTech solutions: The evolution of generative AI will drive the development of innovative LegalTech solutions, making legal services more accessible, efficient, and cost-effective.

The future of generative AI in contract management promises to be transformative, presenting organizations with opportunities to achieve significant efficiency improvements, mitigate risks, and enhance overall business performance. As AI technology progresses, we can expect even more powerful and sophisticated tools that will further alter how contracts are created, managed, and negotiated.

Optimizing contract management with ZBrain: a full-stack GenAI orchestration platform

ZBrain is a state-of-the-art, full-stack generative AI platform that is redefining how businesses handle contract management. By automating intricate processes, delivering insightful analytics, and seamlessly integrating with existing systems, ZBrain enables legal teams to operate more intelligently, swiftly, and effectively. Here’s how ZBrain enhances contract management:

Key features of ZBrain enhancing efficiency and accuracy

• Seamless integration: ZBrain connects effortlessly with tools such as Slack, Microsoft Teams, APIs, and other platforms, streamlining workflows, improving team collaboration, and facilitating smooth communication across departments.
• Low-code interface: With ZBrain’s user-friendly, low-code interface, legal teams can create sophisticated AI applications for contract management without needing extensive programming skills. This feature empowers them to develop tailored solutions that align perfectly with their unique requirements.
• Continuous improvement: ZBrain’s AI models undergo regular refinement through user feedback, ensuring sustained accuracy and effectiveness. This ongoing learning mechanism leads to enhanced insights, increased automation efficiency, and better-informed decision-making.
• Multi-source data integration: ZBrain integrates data from various sources, including databases, cloud services, and APIs. This capability provides legal teams with a comprehensive view of contract data, promoting deeper understanding and more informed decisions.
• Advanced knowledge base: ZBrain features a robust knowledge base that efficiently stores and retrieves structured data, empowering legal teams to develop powerful solutions grounded in extensive information about contracts, legal precedents, and industry standards.

Benefits of ZBrain for contract management

• Customized solutions: ZBrain enables legal teams to develop applications specifically designed to address their unique contract management challenges, facilitating effective resolutions to complex issues.
• Automation of complex processes: ZBrain automates intricate workflows—from drafting and negotiating contracts to execution—reducing manual workloads and allowing legal teams to concentrate on high-value tasks.
• Enhanced decision-making: ZBrain equips legal teams with access to powerful analytics tools, allowing for rapid analysis of large datasets and facilitating more informed decision-making.
• Improved compliance: ZBrain assists organizations in ensuring contract compliance with legal regulations and industry standards by identifying potential risks and inconsistencies.
• Increased efficiency and cost savings: By automating repetitive tasks and optimizing workflows, ZBrain boosts efficiency, resulting in faster turnaround times, lower costs, and enhanced productivity.
• Scalability: ZBrain supports legal teams in developing solutions that evolve alongside their needs, ensuring scalability without compromising on quality or efficiency.

ZBrain empowers legal teams to manage contracts with heightened accuracy, efficiency, and control, ultimately contributing to better business outcomes. As the legal industry increasingly embraces AI, ZBrain emerges as an invaluable resource for organizations looking to transform their contract management processes and gain a competitive advantage.

Endnote

As generative AI continues to transform the legal sector, organizations are presented with a unique opportunity to enhance their contract management practices. This innovative technology enables companies to harness AI’s capabilities for significant advancements. Generative AI can automate key aspects of contract drafting, review, negotiation, and management with exceptional efficiency and precision.

Beyond mere task automation, generative AI delivers actionable insights and data-driven support for decision-making, allowing legal teams to focus on strategic initiatives and improve overall business performance. By leveraging these advanced capabilities, businesses can fully realize the potential of generative AI in contract management, leading to reduced operational costs, enhanced customer satisfaction, expedited decision-making, and ultimately securing a competitive edge in today’s rapidly evolving marketplace.

Moreover, as the demand for streamlined operations and compliance grows, adopting generative AI solutions positions organizations to navigate the complexities of modern contract management with ease. The adaptability of these technologies ensures they can evolve alongside changing business needs and regulatory requirements.

Are you ready to elevate your contract management processes through the power of generative AI? Explore how ZBrain can streamline your workflows, minimize risks, and foster improved business outcomes.