Legal teams worldwide spend dozens of hours each week poring over contracts – examining clauses, spotting risks, and ensuring compliance. This adds up to staggering amounts of time: LegalOn’s 2025 survey of 286 legal professionals reveals that over half of organizations spend more than two hours reviewing a single contract. For a team reviewing 500 contracts annually at an average of three hours per review, this translates to 1,500 hours—or roughly 188 working days—dedicated solely on contract reviews

This time investment comes at a critical cost, impacting both efficiency and strategic priorities. When skilled legal professionals spend most of their day on routine contract review, they have less bandwidth for strategic work, complex negotiations, and the kind of nuanced legal analysis that truly drives business value. Yet simply accelerating these reviews isn't an option - contracts require careful attention, and mistakes can have serious consequences.

Beyond Basic Automation – The Emergence of AI Agents

While early AI tools helped analyze documents or assist with research, today's challenges require something more sophisticated. AI agents are on the cusp of a fundamental shift from passive tools to proactive assistants. Unlike traditional automation tools that focus on isolated tasks, AI agents are designed to coordinate multiple steps within a workflow, maintain context across tasks, and adapt to new inputs over time. These systems operate within defined boundaries, proactively handling routine processes while integrating with broader workflows. 

What is an AI Agent?

AI agents are autonomous systems that operate within defined boundaries, performing tasks and recommending actions based on context and data inputs. Unlike traditional software, which follows rigid rules, AI Agents act as proactive assistants, maintaining context across workflows and suggesting or initiating next steps based on programmed priorities. 

Industry leaders and researchers have offered varying perspectives on the definition and capabilities of AI agents:

• Anthropic's white paper, Building Effective Agents, describes AI agents using an orchestrator-workers framework. In this model, a central AI dynamically breaks down tasks, delegates them to specialized worker AIs, and synthesizes results, demonstrating the potential of structured autonomy.
• OpenAI's recent introduction of “Operator” showcases an AI agent capable of independently completing web-based tasks, such as filling out forms and ordering groceries, illustrating the power of real-world automation.
• Bret Taylor, co-founder of Sierra, has emphasized AI agents' role in transforming business operations. He highlights their ability to automate processes and enhance customer experiences, positioning them as essential tools for the modern workforce.

In legal applications, AI agents do more than flag keywords or analyze clauses. They assess the context of contractual terms, identify patterns across vast document sets, and flag items that may require human review. Over time, their performance improves as through training and feedback from legal professionals, distinguishing them from basic automation tools. 

Key Capabilities and Limitations

The power of AI agents lies in their autonomy and adaptability. They can process natural language with deep contextual understanding, handle complex decision-making scenarios by evaluating multiple factors simultaneously, and adapt their responses based on new information and user feedback. Most importantly, they maintain a sense of their position within a workflow and identify relevant information at each stage based on predefined parameters. Satya Nadella, CEO of Microsoft, envisions a future where AI agents become the primary interface between humans and computers, understanding user needs and proactively assisting with tasks and decision-making.

However, experts also caution about the limitations and risks associated with AI agents. Yoshua Bengio, a pioneer in AI research, warns that agentic AI systems, which operate independently of human input, could pose significant dangers if not properly regulated. He emphasizes the need for national regulations to ensure AI safety and prevent the hasty deployment of such models.

In the legal domain, the integration of AI agents into contract review and negotiation processes introduces both opportunities and challenges. While AI agents can enhance efficiency by automating routine tasks, they require careful human oversight to ensure accuracy and compliance with legal standards. The National Law Review highlights that automating legally binding documents without human supervision can expose businesses and consumers to significant risks.

The Human-AI Partnership

The most successful implementations of AI agents in legal practice embrace these limitations rather than trying to overcome them. By designing systems with human oversight as a core feature rather than a limitation, legal teams can create workflows that combine the best of both worlds: the AI agent's ability to process vast amounts of information and maintain consistent attention to detail, and the human lawyer's expertise in complex reasoning and nuanced judgment.

This "human-in-the-loop" approach isn't just a safeguard - it's a fundamental design principle that acknowledges the complementary strengths of human and artificial intelligence. The AI agent handles the routine and repetitive aspects of contract review, while legal professionals focus on strategic decisions and complex legal analysis. As the system is refined through feedback and additional training, this partnership becomes increasingly effective, but always with the human professional as the ultimate decision-maker.

AI Agents in Legal Practice

The legal profession has emerged as a prime sector for AI agent implementation. What makes legal practice uniquely suited for AI agents is its combination of high-volume routine tasks and the need for sophisticated pattern recognition across complex documents. As law departments and firms face growing pressure to improve efficiency while maintaining high standards of accuracy, AI agents have the potential to transform how legal work gets done - not by replacing lawyers, but by serving as intelligent partners in the review and analysis process.

Core Applications for AI Agents in Legal Workflows

Contract Review and Management 

In contract review, we believe that AI agents can serve as intelligent assistants that streamline and accelerate the entire document lifecycle. They would automatically route contracts to appropriate specialist reviewers based on type and complexity, while conducting preliminary analysis and markup to flag potential issues. In the future, these agents can help monitor deadlines and commitments through automated obligation tracking and support  version control by identifying amendments and modifications throughout the contract lifecycle.

eDiscovery 

AI agents could potentially transform the eDiscovery process by efficiently processing vast collections of emails, messages, and documents at scale. Through smart filtering capabilities, they would identify privileged content and sensitive information and track  document relationships and chronological sequences. These agents may also organize evidence systematically, creating logical groupings and detailed summaries that streamline the litigation team's workflow.

Legal Research 

In legal research, AI agents could conduct comprehensive multi-source analysis, simultaneously searching across case law, statutes, and regulations to identify relevant precedents. They would recognize patterns in judicial decisions and regulatory interpretations, validate citations for accuracy, and match precedents based on both factual and legal similarities. 

Document Analysis 

AI agents would bring efficiency to document analysis through automated categorization of legal materials based on type, importance, and relevance. They could extract key information from complex documents, identify critical clauses and terms while flagging unusual provisions or missing elements. Through cross-reference checking, these agents would ensure consistency across related documents, maintaining the integrity of legal documentation.

Risk Assessment 

In risk assessment, AI agents could leverage predictive analytics to evaluate potential litigation outcomes based on historical data patterns. They would continuously monitor regulatory changes and their potential impact on legal operations, while quantifying potential legal exposure across different scenarios through sophisticated risk scoring. Their early warning systems can identify potential issues before they escalate, allowing legal teams to take proactive measures.

Client Communication

AI agents have the ability to streamline client communication by managing initial screening processes and directing inquiries to appropriate resources. They would maintain consistent client engagement through automated status updates on ongoing matters and handle routine questions about legal processes. 

Supervisory Framework: Ensuring Responsible AI Integration

To fully realize the potential of AI agents in legal practice, implementation must be guided by a robust supervisory framework. Developed in alignment with best practices, such as those outlined in Stanford Law research, this framework ensures that AI agents operate responsibly, effectively, and within clearly defined boundaries:

• Continuous Monitoring: Mechanisms to ensure ongoing quality control and adherence to legal standards.
• Clear Handoffs: Defined decision points for transitioning tasks between AI agents and human professionals.
• Transparency: Explicit documentation distinguishing AI-generated content from human-reviewed outputs.
• Validation: Regular evaluations of AI outputs to confirm accuracy and consistency with legal norms.

This framework emphasizes the importance of human oversight and collaboration, positioning AI agents as supportive tools that complement—rather than replace—human expertise.

AI Agents for Contract Tasks

Contract review and management represents one of the most impactful applications of AI agents in legal practice, offering significant benefits across the contract lifecycle. The key innovation lies in how these agents can serve as supervisory systems, coordinating between automated processes and human expertise while maintaining clear accountability at every stage.

Pre-Signature Contract Review

For pre-signature activities, an AI agent would serve as an initial line of analysis, flagging issues that require human expertise while handling routine aspects of review. This would enable legal professionals to focus their attention on strategic decisions and complex negotiations rather than spending hours on preliminary review. 

Initial Processing and Routing

• Intelligent Contract Ingestion: The agent would automatically identify contract types (like NDAs) and route them to appropriate specialist reviewers, while simultaneously initiating preliminary analysis
  
  • Document Classification: Uses pattern recognition to detect document type, purpose, and priority level
  • Smart Routing: Assigns contracts to specific reviewers based on rules about expertise, workload, and urgency
  • Metadata Extraction: Automatically pulls key information for contract management systems

Analysis and Risk Assessment

• Clause Analysis: Agent identifies standard and non-standard clauses, with automated first-pass review that can immediately flag common issues
• Risk Identification: Flags potential issues and unusual terms, creating a preliminary markup that human reviewers can validate
• Template Matching: Compares against approved templates and standards, allowing counterparty agents to automatically detect major deviations from original templates
• Language Optimization: Suggests clearer or more favorable language, with the ability to compose explanatory notes for suggested changes

Communication and Coordination

• Communication Automation: Drafts preliminary emails to counterparties or internal stakeholders summarizing review findings and suggested changes
• Status Tracking: Maintains real-time visibility into review progress
• Stakeholder Updates: Generates automated notifications for key milestones and decisions
• Collaboration Support: Facilitates concurrent review and feedback from multiple stakeholders

Post-Signature Contract Management

In post-signature management, the agent would transition into a monitoring role, tracking obligations and changes while ensuring nothing falls through the cracks. 

Obligation Management

• Lifecycle Tracking: The agent would monitor deadlines, commitments, and renewal dates while ensuring adherence to contract terms through automated compliance checks
  
  • Automated Alerts: Provides early warnings for upcoming deadlines and potential compliance issues
• Performance Monitoring: Tracks adherence to service levels, delivery schedules, and other measurable obligations

Document Control and Compliance

• Change Management: Tracks amendments, versions, and modifications across the contract portfolio while maintaining comprehensive audit trails
  
  • Version Control: Maintains clear records of all contract changes and approvals
• Compliance Verification: Ensures all modifications follow approved procedures
• Document Repository: Organizes and indexes all contract-related documents for easy retrieval

Process Automation

• Workflow Automation: Manages review and approval processes, routing tasks to appropriate stakeholders, and coordinating cross-functional activities
• Performance Oversight: Monitors contract performance metrics, identifies potential breaches, analyzes obligation fulfillment, and maintains organized contract repositories with automated alerts for key events
• Integration Management: Coordinates with other business systems to track financial, operational, and compliance impacts

Deep Dive: Contract Review 

As legal departments face mounting pressure to review contracts faster while maintaining accuracy, AI agents can become a critical bridge between traditional manual review and fully automated solutions. By working alongside dedicated contract review software, these AI agents can help transform what was once a purely human process into an augmented workflow that maximizes both efficiency and expertise. The integration is particularly valuable as contract volumes grow and legal teams seek ways to scale their capabilities without increasing headcount.

AI agents can complement traditional contract review processes by:

Providing initial screening and issue spotting 

AI agents can serve as the first line of review, rapidly analyzing contracts to identify potential risks, non-standard terms, and compliance issues. They can leverage purpose-built legal models trained specifically on contract language to catch nuances that general AI might miss. This initial screening allows legal teams to focus their attention on the most critical aspects requiring human judgment.

Automating routine review tasks 

AI agents can handle time-consuming manual tasks like comparing contract versions, checking against playbooks, and flagging deviations from standard templates. This automation can reduce review time from hours to minutes, particularly beneficial for high-volume contract types like NDAs, service agreements, and purchase orders.

Supporting human reviewers with AI-powered insights 

Beyond basic automation, AI agents could provide contextual insights by drawing from vast databases of legal knowledge and precedents. They would offer specific recommendations for clause modifications, suggest alternative language, and provide practice notes based on industry standards. This augments human expertise rather than replacing it, helping lawyers make more informed decisions faster.

Maintaining consistency across review processes 

AI agents could help standardize review practices by consistently applying organizational playbooks and policies across all contracts. They would ensure that every contract review follows the same rigorous standards, whether handled by senior attorneys or junior staff. This systematic approach reduces errors and variations in contract handling.

The synergy between AI agents and contract review creates a comprehensive solution that combines automated efficiency with human expertise. While AI agents handle the heavy lifting of initial review and routine tasks, human legal professionals retain control over strategic decisions and complex negotiations, creating a more efficient and effective contract review process. Learn more about how AI contract review software is speeding up contract review.

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