TL;DR
- Contract management appears in both the top 5 return areas AND top 5 risk areas for agentic AI.
- The opportunity: GenAI can translate legalese, extract obligations, and flag compliance issues at scale.
- The risk: autonomous contract decisions without proper guardrails create legal and financial exposure.
- Success requires separating AI-assisted analysis from AI-autonomous execution.
- Organizations must integrate contract AI with CLM, S2P, and ERP systems to realize full value.
Contract management occupies a unique position in the agentic AI landscape: it’s simultaneously where organizations see the highest potential returns and where they perceive the highest risks.
According to The Hackett Group’s 2026 research, contracts rank in the top 5 areas where procurement expects agentic AI to deliver significant value. But in the same research, contract-related AI errors rank among the top governance concerns.
This isn’t a contradiction — it’s a signal. Contract management is where AI can create the most leverage, which is exactly why the stakes are so high.
The Return Side: Why Contracts Are an AI Goldmine
Contracts are documents that define business relationships, obligations, and risks. They’re also notorious for being:
Dense and difficult to interpret. Legal language exists for precision, not readability. Most business users can’t quickly extract key terms from a 40-page supplier agreement.
Scattered and poorly organized. Organizations often have contracts stored across multiple systems, shared drives, and email archives. Finding all agreements with a specific supplier can take days.
Underutilized after signing. Negotiated terms, rebates, and SLAs frequently go untracked and unenforced because nobody has time to monitor compliance.
Agentic AI addresses all three. GenAI can translate contract language into plain-English summaries. AI-powered extraction can pull key metadata — pricing, obligations, renewal dates — from thousands of documents. And intelligent monitoring can flag when suppliers miss commitments or when opportunities for price adjustments arise.
Contract Management: Opportunity vs. Risk Matrix
| AI Application | Opportunity | Risk Level |
| Contract summarization | High | Low |
| Metadata extraction | High | Low-Medium |
| Compliance monitoring | High | Medium |
| Autonomous clause editing | Medium | High |
| Auto-execution of terms | Medium | High |
Source: Zycus Analysis based on The Hackett Group Research, 2026
The Risk Side: Where Guardrails Are Essential
The same capabilities that make contract AI valuable create exposure when deployed without oversight:
Misinterpretation risk. AI summarization can miss nuances that a trained legal eye would catch. A “standard” indemnification clause might have variations that significantly change liability.
Autonomous modification risk. If AI can suggest contract edits, what happens when it makes changes that seem minor but create unintended obligations?
Compliance cascade risk. AI-flagged compliance issues might trigger automated responses — payment holds, supplier notifications — that damage relationships or create legal exposure.
Navigating the Risk-Return Balance
The solution isn’t avoiding contract AI — it’s deploying it thoughtfully. Zycus — positioned as a Leader in the 2025 IDC MarketScape for AI-Enabled Source-to-Pay — approaches this through AI-driven anomaly detection that flags issues for human review rather than acting autonomously on high-stakes decisions.
- Use AI for analysis, humans for decisions. Let AI surface insights and flag risks. Keep humans in the loop for anything that creates legal commitment.
- Integrate with your CLM and S2P systems. Contract AI is most valuable when connected to the systems that execute on contract terms.
- Build escalation paths before you need them. Define what triggers human review and ensure those escalations reach the right people with the right context.
Contract management is where agentic AI can deliver the most value — but only for organizations that respect both the opportunity and the risk.
FAQs
Q1. Why does contract management rank high in both AI returns and AI risks?
Contracts are complex, high-stakes documents where AI can create significant efficiency gains through summarization and analysis. But the same complexity means AI errors can create legal and financial exposure, making proper guardrails essential.
Q2. Where should organizations start with contract AI?
Begin with lower-risk applications like contract summarization and metadata extraction. Build confidence and refine processes before moving to higher-risk capabilities like compliance monitoring or clause suggestions.
Q3. How can organizations mitigate contract AI risks?
Keep humans in the decision loop for anything creating legal commitment, integrate AI with existing CLM systems for proper context, and build clear escalation paths before deploying autonomous capabilities.
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