Contract management processes are costing businesses nearly 10% (9.2) of their annual revenue and taking, on average, nearly three and a half (3.4) weeks to manually execute.
As conducting business has grown to be ever more complex and involves an increasing number of contracts, overcoming this challenge should be a high priority for any business, but especially those with in-house legal teams.
These costly delays stem from key inefficiencies across the contract management lifecycle, including stalled sequential stakeholder signatures, manual version control challenges, lack of visibility into contract status, and siloed departmental handoffs. While these are inherently manual problems, even with the aid of contract lifecycle management (CLM) software, exceptions that break the rules-based model CLMs operate on can and do arise.
Innovative new platforms now combine contract lifecycle management with powerful artificial intelligence capabilities to transform this costly bottleneck into a driver of business value through Agentic AI approval workflows.
What Is an Agentic AI Approval Workflow
These enhanced workflows provide rapid value once implemented by using AI Agents to understand context, intent, and goals. AI agents manage, evaluate, and route contracts through internal sign-off phases.
Further to this, AI Agents evaluate proposed terms against contract playbooks, identify missing information, and determine the precise level of human authorization required.
How agentic AI differs from rule-based approval routing
Legacy systems follow predetermined, checklist-style sequences of events and lack broader context, making them prone to unexpected failures or unintended time wasting. For example, a typical rule might be that contracts worth over a hundred thousand dollars are sent automatically to the CFO, but what if a contract worth ninety-nine thousand dollars is high risk? And the hundred thousand is a low priority? Only the low-priority contract would end up in front of the right stakeholder.
Also, a rules-based CLM only looks for what it is told to look for (like specific clauses in specific places) and will miss everything else. AI rapidly reads an entire document as if it is a legal professional, and views it within the wider context of the existing contract ecosystem, company playbooks, and other incoming documents.
This means that it can apply risk profiles cumulatively rather than in isolation and fast-track high-value but low-risk contracts for approval, and vice versa, flagging issues and routing to the appropriate stakeholders with justified logic.
| Capability | Legacy Rule-Based Routing | Agentic AI Approval Workflow |
| Routing Logic | Hardcoded criteria (e.g., deal size, contract type) | Contextual risk analysis & playbook alignment |
| Exception Handling | Stalls workflow; requires manual intervention | Resolves minor deviations or suggests fallback fixes |
| Execution Path | Strictly sequential step-by-step sign-offs | Parallel, dynamic routing based on clause-level risk |
| Auditing & Context | Static task reminders | Generates risk rationales & decision summaries |
Where approvals fit in the contract lifecycle
Deploying Agentic AI during approvals reduces risk by ensuring contracts are thoroughly vetted and redlined before reaching legal counsel.
How Contract Approval Automation Software Works
A previously opaque and slow process becomes a driver of business efficiency and value when it is transparent and automatic. By equipping contract approval automation software with advanced AI capabilities, legal departments can enjoy an improved level of trust, thanks to:
Automated routing and escalation
As contracts enter the approval stage, AI Agents trained on legal data can apply and execute different tasks concurrently and automatically:
Risk scoring: AI will scan a document in its entirety and pull everything for comparison to internally defined risk profiles and other metrics, proactively highlighting points of contention for humans.
Collaborative Notifications: If an agreement requires the input of multiple departments, such as finance and Information Technology, the AI Assistant can pull the appropriate sections and send them to them in parallel, saving time.
Smart escalation: The Agentic AI can understand if a required signatory is out of office and will be able to reroute documents to other approvers if needed, for example.
Real-time status tracking
A clear use case for Agentic AI in contract approval workflows is the solving of the “black hole” effect, whereby stakeholders lose visibility over a contract out for approval. They know it's been sent and are awaiting a signature, but may have lost sight of who it is sitting with, when it needs to be signed by before it expires, and whether it has become stuck somewhere.
The AI will know, and be able to provide updates, commentary and metadata at every step of a contract’s journey. Connectivity with messaging tools such as Microsoft Teams or Slack, and enterprise Customer Relationship Management platforms like Salesforce will give in-house legal teams the transparency they need to overcome this challenge, in a familiar environment.
CLM Software That Automates Contract Creation and Approvals
The goal of a contract approval workflow transcends solving problems in isolation, and is primarily to have a cumulative beneficial impact across every stage of the process that is felt organization-wide.
Once the loop has been optimized by AI Agents, it can be repeated continuously, freeing up human time.
From clause library to signature
These new platforms bake AI into the entire lifecycle of a contract, from pre-approved authors generating pre-approved clause libraries to automatic approvals if the document is 100% pre-approved, removing the need for manual review entirely.
Should requested changes retain a match to pre-approved fallbacks, the contract remains AI-managed with automated approvals. Naturally, the reverse will cause a human-in-the-loop (HITL) review.
Reducing manual handoffs
Research from Business Plus AI found that AI-driven approval processes can reduce turnaround time as much as 85%, representing a realized time cost saving of days compared to hours. In part, this is due to administrative tasks (such as forgotten email attachments!) that an AI Agent would eliminate.
Benefits of Cutting Contract Cycle Time
To recap, cutting contract cycle time protects an organization’s revenue, ensures total legal compliance, and reduces human time costs, adding further value over time once implemented.
Faster deal velocity
There are numerous benefits to be felt from increasing the velocity of signed deals, from better reporting and more onboarded partners and customers (not to mention revenue generated) to the implementation of mission-critical new tools, faster.
Accession Risk Management Group implemented LinkSquares and empowered their team with self-service workflow and AI-driven insights. They were able to slash legal queue times from nearly 197 hours down to 55.5 hours.
In short, the results of any deal come sooner if the deal itself closes sooner. Shorter turnaround times for signing also help prevent deals from getting lost simply by taking too long.
Fewer bottlenecks and missed deadlines
Senior legal counsel may have more pressing priorities than reviewing ever-growing manual approval queues. Conversely, with the help of an AI assistant, they would be able to prioritize by risk level and key dates in a few simple clicks, without needing to dig through a crowded inbox.
Choosing the Right Approval Automation Software
With contract approval being such a key element of operating a modern business, it’s vital that care is given to choosing an appropriate platform for approval workflows. Business and technical leaders will need to be appraised of the challenges, risks, and opportunities of implementing any new tooling.
Key features to evaluate
The following features should be considered absolute must-haves:
- The engine must be aware of context and intent at the clause level instead of relying on exact-match keywords or metadata.
- It must be able to ingest your company playbook and quickly understand your unique scenarios and approval matrices, escalation policies, and risk tolerances.
- It must provide logical rationale when making suggestions or decisions so that humans understand why what was done was done.
- It must protect the privacy of the documents it reads to protect sensitive information, and never train the AI with it.
CLM that Integrates with Existing Platforms
Finally, any new platform must be able to fully integrate with the rest of your technology ecosystem, including contract repositories, CRM platforms, messaging tools, and more.
Further, it should be able to direct updates into those platforms as well as its own dashboard.
Schedule a demo to learn how LinkAI could transform your contract approval workflow.