Contract Management in the AI Era: Challenges and Solutions
- Last Updated: Dec 26, 2025
- 15 min read
- Sirion
In the AI era, contract management is undergoing a paradigm shift. The adoption of technologies like Large Language Models (LLMs) is empowering enterprises to streamline processes, reduce inefficiencies, and unlock new levels of accuracy and scalability. However, harnessing the full potential of AI in contract management requires addressing critical challenges, including ensuring reliability, safeguarding sensitive data, and balancing cost-efficiency with performance. This article explores how AI-powered solutions like Sirion are driving innovation and transforming contract management for enterprises across industries.
The Evolution of AI and GenAI in Contract Management
AI and GenAI are reshaping contract management across six transformative stages, each unlocking new levels of efficiency, automation, and strategic value.
Unorganized Phase – Laying the Groundwork:
Contract processes are scattered, leading to inefficiencies and risks. AI tools like OCR digitize and organize contracts, providing a foundation for structured workflows.
Foundational Phase – Building Structure:
Organizations implement centralized repositories and basic workflows. AI supports metadata extraction and document categorization, streamlining contract management efforts.
Streamlined Phase – Driving Consistency:
Standardized templates and compliance frameworks emerge. AI-powered tools automate redlining, compliance monitoring, and risk identification, enhancing operational efficiency.
Strategic Phase – Leveraging Insights:
With integrated CLM systems, contracts become strategic assets. Advanced AI analytics offer predictive insights and automate risk management, enabling informed decisions.
Optimized Phase – Unlocking Full Potential:
AI automates complex tasks like contract drafting and negotiation. Machine learning refines risk models and drives continuous improvement, positioning contracts as a source of competitive advantage.
Intelligent Phase – GenAI at the Helm:
GenAI transforms contract management with intuitive tools like conversational interfaces, advanced redlining, and detailed summarization. Teams experience personalized, data-driven insights and seamless collaboration.
As organizations progress, AI and GenAI evolve from simple enablers to transformative forces, turning contract management into a proactive, value-generating business function.
Growth of GenAI in Enterprise Contract Management
Generative AI (GenAI) is reshaping contract lifecycle management across enterprises by boosting efficiency, accuracy, and decision-making. From automating contract workflows to extracting actionable insights, GenAI is revolutionizing contract processes, empowering departments like Legal, Procurement, Sales, and Finance to collaborate effectively, streamline operations, and achieve faster results.
Legal: Simplifying Complex Workflows
- Standardized Playbooks for Contract Drafting
GenAI facilitates the creation of contract playbooks with predefined clauses, fallback options, and templates, ensuring consistent, efficient drafting. - Automated Risk Reviews
AI flags risks, highlights deviations, and compares terms against playbook standards, reducing manual review time and increasing precision. - Intelligent Redlining and Negotiations
GenAI recommends language adjustments and identifies compromise opportunities, supporting risk-aligned negotiations. - Quick Insights and Due Diligence
Interactive queries help legal teams identify risks, ensure compliance, and streamline decision-making with actionable insights.
Procurement: Streamlining Contract and Supplier Management
- Self-Service Contract Generation
Create compliant contracts using pre-approved templates via conversational prompts, reducing reliance on manual efforts. - AI-Powered Contract Negotiation
Simplify reviews with AI-suggested contract clauses and deviation tracking, accelerating approvals. - Integrated Workflows
Seamlessly connect procurement systems to ensure smooth data flow and eliminate silos. - Compliance and Obligation Tracking
Monitor service levels and contract obligations using natural language queries for real-time updates. - Supplier Analytics
Gain valuable insights into supplier performance and procurement strategies with AI-powered contract dashboards.
Sales: Accelerating Deals and Strengthening Customer Relations
- Automated Contract Approvals
Generate sales contracts using pre-approved templates and streamline workflows to minimize delays. - Real-Time Obligation Tracking
Track key contract terms and deliverables, ensuring commitments are met proactively. - Data-Driven Growth Strategies
Analyze historical transactions to uncover growth opportunities and enhance account management.
Finance: Aligning Contracts with Financial Objectives
- Centralized Contract Access
Store and retrieve contracts instantly through a searchable repository using natural language queries. - Strategic Financial Alignment
Use contract dashboards to link cash-impacting terms with financial planning for more informed decisions. - Automated Risk Controls
Identify risks and enforce compliance through automated contract analysis. - Invoice Validation and Spend Optimization
Ensure service levels, validate invoices, and control spending with real-time vendor performance insights. - Renewal Management
Prevent unnecessary costs with timely renewal alerts and accurate cash flow forecasts through ERP integration.
By leveraging GenAI, enterprises can optimize contract management across departments, driving faster results, enhancing compliance, and unlocking greater business value.
Challenges of Using Generative AI in Contract Management
Generative AI holds immense promise but also introduces significant challenges, particularly in the realm of Contract Lifecycle Management (CLM). Legal teams, being naturally risk-averse, approach these tools cautiously due to the critical nature of contract handling, where errors can result in compliance failures, disputes, or financial losses. The nuanced and complex language of contracts and the lack of AI transparency exacerbate these concerns.
Key Issues to Address When Adopting Generative AI in CLM
Opaque Decision-Making Lacks Accountability
Generative AI often operates as a “black box,” offering insights or outputs without providing a clear rationale. This lack of explainability undermines trust, especially in critical areas like regulatory compliance and legal dispute resolution. Without a transparent decision trail, the defensibility of AI-generated results becomes questionable, leading to user skepticism.
Overreliance on a Single AI Model Reduces Flexibility
With many new AI models emerging, each with unique strengths, depending on one model limits your options. Relying on a single-model CLM system could restrict adaptability and lock you into a vendor’s ecosystem, making it harder to pivot as technology advances.
Generic LLMs Are Ill-Equipped for Contract-Specific Needs
Most commercially available LLMs lack the specialized training required to handle the intricacies of legal language, contract structures, pricing strategies, and negotiation nuances. Without deep pretraining tailored for contracts, these models are prone to generating inaccurate or misleading outputs—commonly referred to as “hallucinations.”
LLMs Alone Are Insufficient — Small Data Models Add Precision
While LLMs can provide broad contextual understanding, certain contract management tasks—like identifying specific clauses, pricing terms, or compliance requirements—are better handled by small, task-specific models. These models, trained on contract-centric data, deliver more precise and reliable outputs for critical use cases. Relying solely on LLMs can reduce accuracy in contract workflows where precision is paramount.
AI Training and Maintenance Come with High Costs
Building and maintaining an AI model is expensive. Training even a basic model can cost over $1 million, and you’ll also need experts to keep it running smoothly. This can significantly increase operational costs, making AI adoption a substantial financial commitment.
Data Security Risks with Third-Party LLMs
CLM solutions leveraging external LLM providers may expose proprietary data to risks. When data flows between a CLM vendor’s platform and the LLM provider’s servers, there’s limited visibility or control over how the data is stored or used. Customers face the potential risk of sensitive information inadvertently being used to train models for other organizations.
Addressing these challenges is essential for businesses aiming to integrate generative AI into CLM workflows effectively and securely. Only by overcoming these hurdles can organizations fully realize the transformative potential of AI in contract management.
Related Read: The Evolution Of Contract Management: From Box To Bot
Adapting LLMs for Contract Management
Large Language Models (LLMs) can revolutionize contract management when built on three critical foundations: reliability, security, and cost-effectiveness. Sirion’s advanced AI solutions exemplify these attributes, providing a seamless framework for tailored contracting solutions.
Building a Reliable Framework
Reliability in contract management AI hinges on consistency, accuracy, and adaptability:
- Diverse Model Integration
Sirion integrates both LLMs and Small Data AI (SD AI) models to handle diverse contract tasks. LLMs are great for summaries and clause remediation, while SD AI models ensure precise data extraction and classification. This flexibility allows Sirion to deliver targeted, reliable results for different use cases. - Domain-Specific Intelligence
Standard LLMs lack contract-specific expertise. Sirion bridges this gap by pretraining models on curated contract data from relevant industries, enabling immediate, accurate responses tailored to contractual needs. - Customizable AI Workflows
With Sirion’s intuitive training studio, organizations can easily adapt models to their unique requirements. Users can:- Incorporate proprietary data.
- Add specialized functionalities.
- Update or retrain models to stay aligned with evolving business demands.
Safeguarding Contract Data
Effective use of LLMs in contracting demands robust data protection and transparency:
- Securing Sensitive Information
Sirion ensures all customer data remains in private cloud environments, using advanced techniques to anonymize sensitive details, localize processing, and maintain strict tenant isolation for enhanced security. - Transparent Outputs
Every AI-generated result in Sirion is fully traceable, allowing users to validate outputs against original data sources. This transparency eliminates the risks of relying on unverifiable, “black-box” AI models.
Optimizing Costs Without Compromising Performance
Managing costs is critical when implementing LLMs for contract management. Sirion focuses on efficiency by:
- Using right-sized models designed for contract-related language comprehension and data processing.
- Ensuring cost-effective customization, deployment, and maintenance without sacrificing functionality or precision.
Sirion: The Smarter Choice for Contracting AI
Sirion’s AI CLM solutions are tailored to meet the demands of modern contract management. By integrating a multi-model architecture that leverages both Large Language Models (LLMs) and Small Data AI models, advanced security measures, and cost-efficient scalability, Sirion empowers enterprises to streamline contract processes with precision, flexibility, and cutting-edge technology.
The Road Ahead
As organizations navigate the complexities of contract management in the AI era, it is clear that success lies in adopting solutions that deliver reliability, security, and cost-effectiveness. Sirion’s tailored approach to AI-powered contracting provides enterprises with the tools to enhance decision-making, improve operational efficiency, and stay ahead in a rapidly evolving landscape. By embracing advanced technologies like LLMs, businesses can future-proof their contract management strategies and unlock unparalleled value.
