Legal teams handle many kinds of contract work, and one of their hardest problems is matching the right technology to the specific problem in front of them. When this post was first written, many smaller legal departments were wary of AI. Since then, generative AI has made the question unavoidable. The useful question now is not whether to use AI, but where it removes real delay.
This guide looks at four challenges that stop contracts reaching signature on time: inconsistent language, manual processes and silos, poor visibility into terms and slow signing. For each, it explains what AI and contract lifecycle management software can do, and what still needs a person.
Why does inconsistent legal language cause delay?
When every contract is drafted differently, every review starts from scratch. Reviewers read each clause to work out what it means, compare it in their heads with what the company usually accepts and argue over wording that should have been settled years ago.
Standard language solves most of this. A clause library of approved positions, with fallbacks for common negotiations, means drafts start from known terms. AI then compares incoming paper with those standards and flags only what differs. Modern tools can also assemble an agreement from the right template based on contract type, counterparty and region, so the first draft is closer to final.
The benefit goes beyond drafting. When AI can read and interpret contract language, legal teams save time on every review, not just the ones they write. See contract clause library.
How do manual processes and silos hold contracts back?
Complexity rises quickly when contracts are managed across offices, regions and languages. Drafts live in personal folders, approvals happen by email and nobody can see the whole picture. Legal works hard to keep track, but the process depends on people remembering where things are.
Contract lifecycle management software brings requests, drafts, approvals and signed agreements into one system. AI extracts key information from each contract so teams can work on the details together, whatever the contract's complexity. Legacy agreements can be brought in the same way, so the silo of old contracts disappears too.
In Contractflow, requests, drafting, review, approval and signature run in one workflow, natively on ServiceNow or standalone.
Why does visibility into contract terms matter?
If you cannot see a term, you cannot control it. Without a way to organize contracts, renewals slip past, expired agreements stay in use and nobody can confirm that the company is getting the value it negotiated.
AI enabled contract software reads the common contract formats, including scanned documents, and extracts parties, dates, values, renewal terms and obligations into a searchable repository. Teams can then ask which agreements expire next quarter, or which include a particular clause, and act in time. See contract renewal management.
What stops contracts being signed on time?
Even an approved contract can stall at signature. Paper signing means meetings, couriers and scanning. Email signing without a process means documents sit in inboxes, the wrong person signs first or a signer is on leave. Each delay pushes back the start of the work, the revenue or the savings.
| Cause of delay | Fix |
|---|---|
| Paper signatures | Electronic signature built into the workflow |
| Wrong signing order | Signing sequence set before sending |
| Signer unavailable | Delegation rules and alternate signers |
| Document forgotten in an inbox | Automatic reminders and escalation |
| Unclear status | Live signature status on the contract record |
| Last minute changes | Version control so the signed copy matches the approved one |
In Contractflow, users can set the signing order before sending documents through DocuSign, track status on the contract record and send reminders. The executed contract returns to the repository, and Aavenir AI extracts its obligations for a contract manager to approve. Learn about electronic signature.
How should you measure progress?
Pick a few measures and track them from your current baseline. Useful ones are time from request to first draft, number of review rounds per contract type, time from final approval to full signature and the share of contracts using standard clauses without changes.
Break the signature measure down by stage, because the fix depends on where time is lost. If contracts wait for internal signers, look at delegation rules. If they wait for counterparties, look at reminders and at whether the version you sent was really final. Review the numbers monthly, and change one thing at a time so you know what worked.
Where does AI help most, and where does it not?
- Most help: comparing drafts with standards, extracting terms from executed and legacy contracts, answering questions across the repository and drafting routine agreements from templates.
- Some help: suggesting negotiation positions based on past outcomes, with a lawyer deciding.
- No substitute: judging risk on a bespoke deal, negotiating with a counterparty or deciding whether to sign.
Regulation of AI in legal work is still developing, and professional duties stay with lawyers. The safest approach is AI that shows its sources, logs every action and has a person approve each result. Read about Avy.
The bottom line
Contracts miss their signature dates because of problems that start long before signing: inconsistent language, silos and poor visibility. Standardize your clauses, bring contracts into one system, let AI do the reading and comparing, and set up electronic signature with a clear order and reminders.