Legal operations teams have spent the last decade getting faster at reacting. Intake forms route contracts in minutes. Approval workflows enforce SLAs. Document repositories make retrieval painless. But speed in isolation does not solve the structural problem: legal ops still operates in a silo, disconnected from the procurement, compliance, security and finance decisions that shape every vendor relationship. Agentic AI changes this, but only if legal teams stop treating it as a smarter layer on top of the same disconnected workflows.
By Lihi Lutan, Co-Founder and CEO, Opstream
Co-Founder and CEO of Opstream, previously COO of StokeTalent (acq. Fiverr) and VP Operations at Taboola where she helped scale the company from $8M to $1B in revenue.
Why are legal ops teams still stuck in reactive mode?
The numbers paint a clear picture. According to the Thomson Reuters Legal Department Operations Index, 70% of legal departments report higher matter volumes while 66% face flat or declining budgets.1 Legal teams are doing more work with fewer resources, and their technology stack reinforces the problem rather than solving it.
Contracts live in a CLM. Compliance documents live in a GRC platform. Vendor risk assessments live in a spreadsheet or a standalone portal. Each tool automates its own slice of legal work, but none of them connect to what happens before and after legal’s involvement. A renewal contract lands on a reviewer’s desk with no context about the vendor’s compliance history, the associated purchase order, the budget impact or the security flags raised during the original onboarding process.
This is not a technology problem. It is an architecture problem. Legal ops tools were designed to optimize legal workflows in isolation. They were never designed to give legal teams visibility across the full vendor lifecycle.
- Renewal contracts arrive weeks before expiration with no prior version comparison
- Vendor questionnaire responses sit in folders no one checks outside audit season
- Software purchases get approved by procurement and finance before legal learns they involve regulated data
- Compliance certifications expire without anyone noticing until an auditor asks
Workflow automation made each of these tasks faster. It did not make any of them proactive.
The real bottleneck is visibility, not speed
Most conversations about AI in legal operations focus on the wrong constraint. The assumption is that legal teams need faster document review, smarter contract summaries or more efficient intake routing. Those capabilities matter. But they treat symptoms while ignoring the root cause.
The root cause is data fragmentation. Legal teams make decisions with partial information because their tools cannot see beyond the legal function. When a contract reviewer opens a renewal agreement, they should see the vendor’s full history: prior contract terms, compliance status, total spend, active security assessments and any flags raised during onboarding. Instead, they see a standalone document and a thread of internal comments.
A workflow automation tool can route a contract to the right reviewer in minutes. But if that reviewer has no visibility into the vendor’s compliance history, the purchase order, or the security flags from three months ago, speed alone solves the wrong problem.
This is why adding AI to a siloed legal tool produces underwhelming results. The AI can only operate on the data it can access. If that data is limited to contracts and legal intake forms, the AI’s output is equally limited. It can summarize what it sees. It cannot connect what it sees to the broader vendor relationship.
What does agentic AI actually mean for legal operations?
The term “agentic AI” has entered enterprise vocabulary quickly. Gartner projects that 40% of enterprise applications will integrate task-specific AI agents by 2026, up from less than 5% previously.2 But in legal technology, the term is being applied loosely, often to capabilities that do not meet the bar.
Adding a chatbot to a legal workflow tool is not agentic. Summarizing a contract with a large language model is not agentic. These are useful features. They still depend on someone initiating the action, knowing what to ask and having the context to act on the answer.
True agentic orchestration works differently. The system monitors the full vendor lifecycle continuously. When a renewal contract arrives, it compares the new version against the previously approved terms and categorizes every material change: commercial, legal, compliance, IP, liability and termination. It checks whether the vendor’s SOC 2 report has expired. It surfaces the original purchase request so the reviewer sees the full history. It does all of this before anyone opens their inbox.
According to Gartner, agentic AI systems in procurement are “designed to operate autonomously, making decisions and executing tasks with minimal human intervention, thereby increasing efficiency and reducing the potential for human error.”3 The same principle applies directly to the legal operations layer that sits alongside procurement.
What changes when legal has full vendor lifecycle context
When legal workflows connect to procurement, compliance, security and finance data within a single platform, three structural shifts follow.
Reviews get smarter, not just faster
Instead of reviewing a renewal contract in isolation, legal sees the complete vendor record: prior contract terms, compliance documentation, spend history, security assessment results and any flags raised during onboarding. AI Document Comparison surfaces every material change between the current and previous version, categorized by clause type. Reviewers focus on what actually changed rather than re-reading 50-page agreements from scratch.
Compliance becomes continuous, not periodic
Agentic workflows monitor vendor compliance documents in the background. When a SOC 2 certification expires, when a regulatory deadline approaches or when a vendor’s risk profile changes, the system triggers alerts and can automatically create follow-up requests. Legal stops playing audit-season catch-up because the platform enforces compliance timelines year-round, without anyone remembering to check a spreadsheet.
Legal becomes a strategic function, not a bottleneck
When legal ops teams can query vendor spend, contract obligations and compliance status through natural language, they stop being the team that slows approvals down and start being the team that prevents costly mistakes. A question like “which vendors have auto-renewal clauses expiring in the next 90 days?” gets answered in seconds, pulled from live data across the entire vendor portfolio.
70%
of legal departments report higher matter volumes1
66%
face flat or declining budgets to handle that volume1
40%
of enterprise apps will integrate AI agents by 20262
Why orchestration beats point solutions
The shift to agentic AI in legal operations demands a specific kind of foundation. Bolting AI onto a contract management tool or a legal intake portal is not enough. The system needs four things working together.
Unified data. Vendor information, contract terms, compliance documents, spend data and approval history must live in a single structured data model. AI cannot surface insights across silos if the underlying data is itself siloed. Gartner’s research on procurement orchestration platforms reinforces this, noting that these platforms must “aggregate procurement and other relevant data from multiple internal and external sources.”4
Configurable workflows. Every organization’s legal review process is different. The platform must let administrators define custom intake forms, approval sequences, conditional logic and escalation rules without engineering work. Rigid templates break the moment a real process deviates from the assumed default.
Cross-functional integration. Legal does not work in isolation. The platform must connect to ERP systems for purchase orders and budgets, to identity providers for organizational structure, to communication tools for notifications and to e-signature platforms for contract execution. If legal’s system does not talk to procurement’s system, the visibility gap persists.
Governance and auditability. AI-driven actions in legal workflows carry real risk. Every action needs a clear audit trail. Role-based access must control who sees what. The system must enforce policy guardrails so AI operates within the boundaries that the legal team defines, not outside them.
Key Takeaways
● Unified data across vendors, contracts, compliance and spend
● Configurable workflows that match how your organization actually works
● Cross-functional integration connecting legal to procurement, finance, security and IT
● Governance and audit trails for every AI-driven action
These are not nice-to-have features. They are the prerequisites that determine whether agentic AI in legal operations delivers real results or just produces summaries that no one trusts enough to act on.
Where legal operations is heading
The best legal ops teams over the next two years will not be the ones with the most automated workflows. They will be the ones with the most connected workflows.
Gartner predicts that by 2028, 40% of procurement teams will have implemented at least one AI agent.5 Legal operations sits at the intersection of procurement, compliance and risk. As those adjacent functions adopt agentic capabilities, legal teams that remain siloed will find themselves further behind, not because their tools are slow, but because their tools cannot participate in the broader orchestration layer.
Agentic orchestration dissolves the boundary between “legal’s system” and “procurement’s system” and “compliance’s system.” It creates a single operating layer where every stakeholder, from the requester to the CFO, works from the same data and the same audit trail.
For legal ops leaders evaluating their AI strategy, the question is not “how do we add AI to our legal workflows?” The real question is “how do we connect legal workflows to the decisions and data that happen around them?”
The teams that answer that question well will stop reacting and start orchestrating.
Frequently Asked Questions
What is the difference between legal AI and legal workflow automation?
Legal workflow automation executes predefined rules: routing intake requests, enforcing approval sequences and triggering notifications based on if-then logic. Legal AI adds intelligence on top of those workflows. It can interpret unstructured documents, classify risk, compare contract versions and surface insights from data. The highest-value implementations combine both: automation handles the structured process execution while AI handles the interpretation and decision-support layers.
How does agentic AI differ from traditional legal automation?
Traditional automation requires a human to initiate every action. Someone submits a request, someone triggers a review, someone runs a report. Agentic AI operates continuously in the background, monitoring conditions and acting when thresholds are met. It can detect an expiring compliance certificate, compare a renewal contract against prior terms and flag deviations from company policy, all without a human starting the process. The critical distinction is autonomy: agentic systems act within defined guardrails rather than waiting for instructions.
What data does a legal ops team need to move from reactive to proactive?
At minimum: contract terms and version history, vendor compliance documentation with expiration dates, spend data by vendor, security assessment results and the full approval history for each vendor relationship. The key is that this data must be unified in a single system, not scattered across a CLM, a GRC tool, an ERP and a series of spreadsheets. When the data is unified, AI can draw connections that are impossible when each dataset lives in a separate silo.
How does vendor lifecycle visibility improve legal contract reviews?
When a legal reviewer opens a renewal contract, they typically see only the document itself and whatever notes colleagues have added. With full vendor lifecycle visibility, that same reviewer sees the previous contract version with changes highlighted, the vendor’s current compliance status, total spend to date, any security flags from the onboarding process and the original purchase justification. This context transforms the review from a document-level exercise into a relationship-level assessment, dramatically reducing the risk of approving terms that conflict with existing obligations.
See how legal ops teams use Opstream to stop reacting
Opstream connects legal workflows to procurement, compliance and finance data in a single platform. One vendor record. One audit trail. Full lifecycle visibility.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation.
Sources
- Thomson Reuters, “Legal Department Operations Index,” 2023. thomsonreuters.com
- Gartner, reported statistic on enterprise AI agent adoption projections, 2025.
- Gartner, “Hype Cycle for Procurement and Sourcing Solutions, 2025,” Kaitlynn Sommers, Micky Keck, et al., June 30, 2025.
- Gartner, “Innovation Insight: Procurement Orchestration Platforms,” 2025.
- Gartner, “Predicts 2025: Procurement Addresses Data Challenges and Embraces Rapid Change,” 2025.
About the Author
Lihi Lutan
Co-Founder and CEO, Opstream
Lihi Lutan is the Co-Founder and CEO of Opstream, changing the way companies buy. Throughout her career, Lihi built and scaled business operations at startups and large corporations. Early in her career, Lihi was with Cyota (acq. RSA Security) as a team leader and project manager before moving to Thomson Reuters and Fundtech to manage global projects. Later, Lihi joined Taboola (NSDQ: TBLA) as employee 15, as VP Professional Services and Operations, leading the department as the company scaled from $8M to $1B in revenue. Transitioning from Taboola to StokeTalent (acq. Fiverr), Lihi served as the company’s COO. Lihi holds an LLB of Law and BSc of Computer Science from Tel Aviv University.
