- March 21, 2024
- 8 min read
- Sirion
Introduction
In the negotiation phase of contracting, two parties – usually a buyer and seller – work together to agree on contract terms. These terms might include service level agreements, delivery schedules, warranties, conditions, and even termination.
Ideally, the terms are favorable to everyone involved, which calls for meticulous coordination on all sides and an effective contract negotiation strategy to pull off.
However, without a technology-led contract management framework, the entire process is at risk and full of inefficiencies. This is where AI comes into play.
This article will explore the gaps within a traditional negotiation process and how AI contract negotiation tools help improve in-house legal teams.
Traditional Contract Negotiation Challenges
Although many basic business practices today are automated, the routine elements of contract negotiation (as with most aspects of contract management) are often manual. However, at the scale of a large enterprise, driving negotiations manually puts unmanageable strain on the capacity of legal teams.
As a result, teams must reimagine traditional contract negotiation and turn to highly scalable, risk-aware processes that mitigate any negative impact on the bottom line.
Let’s look at some of the most common issues associated with traditional approaches to negotiating contracts so that we know what to look out for:
1. Legacy tools and human error
Some businesses still use spreadsheets, emails, and paper copies to manage contract negotiations. The result – clerical errors, missing data, and miscommunication. While human error is natural, a missed clause or a slight deviation in clause language can cause significant and detrimental downstream issues.
2. Prolonged contract review cycles
Relying solely on email to track information spread across multiple departments and workflows creates excessive back-and-forth. Your teams will spend more time clarifying miscommunications than resolving priority issues, prolonging the negotiation cycle. Negotiations are also usually time-sensitive, and a missed deadline can disrupt operations.
3. Lack of centralization
Historically, contracts have been poorly managed. Think duplicate, incomplete, and erroneous copies getting lost in lengthy email chains or filing cabinets – a bad case of version control at its finest, especially for large enterprises.
Not having a centralized repository to house all contract-related documents results in scheduling issues and a lack of transparency. Internal teams can’t preserve an auditable communication trail or expect accuracy when funneling information through multiple platforms.
4. Poorly standardized contract management
Negotiations are logistically challenging. Relying solely on a manager’s contract negotiation skills is not optimal, and no amount of training can prepare teams for complications if there aren’t standards to guide proceedings.
Without standardization, teams are unable to:
- Compare drafts
- Evaluate predefined risk positions
- Understand if a counterparty’s suggested clause aligns with the company’s preferred position
- Prevent unfavorable outcomes wherever possible
- Understand the risks associated with missing clauses.
The Power of AI Contract Negotiation Software
In today’s world, manual contract negotiation processes may not be enough to negotiate satisfactory contracts. Enterprises must embrace AI contract lifecycle management (CLM) software to create stronger agreements that ensure better business outcomes.
This can also help maintain stronger counterparty partnerships – a true win-win!
Benefits of AI Contract Negotiation
Here’s how AI-powered CLM software supports and streamlines the contract negotiation process:
1. Speed up legal review
An AI-powered CLM platform can scan documents at scale and assist in legal review by highlighting changes made to a draft in minutes. This will let human reviewers – who would otherwise spend hours or days comparing versions – focus on more strategic goals.
2. Automate risk discovery
AI can autonomously highlight missing clauses or clause deviations in third-party drafts and offer prescriptive clause suggestions to ensure effective risk control in negotiated agreements.
3. Streamline contract creation
With an AI-led CLM, you can standardize the contract negotiation process to align with your company playbook by setting up pre-approved templates and clauses. AI then reviews the draft contract to ensure its language matches company-preferred positions. A CLM’s AI can also leverage historical contract data to make recommendations to create more solid agreements that offer better business outcomes.
4. Digitize and centralize storage
You can securely and sustainably store your contracts by utilizing a centralized, cloud-based contract repository. The repository also acts as a single source of truth for all contracting data, including related documents, comments, and communication from the negotiation phase.
5. Simplify contract review and workflows
With so many hand-offs between multiple internal stakeholders and the counterparty, it is easy to skip a step by mistake. A CLM platform streamlines and automates this process using configurable workflows. Once a contract is ready for approval, it can quickly move from reviewer to reviewer while offering complete visibility into the status of each stage of the process.
6. Deep analytical insights based on past contracting data
Accurate contract data on past deals is vital to developing strong negotiation tactics, presenting appealing counteroffers, and finding the best alternatives to unfavorable contract terms. AI contract negotiation software provides actionable insights based on past performance trends. Retrospective contract analytics will help you gain an edge during business negotiations and modify clauses in new contracts.
Potential Drawbacks and Considerations
1. Dependence on data
AI relies on data to function effectively. But the quality and accuracy of AI contract negotiations depend on the quality and quantity of the data it’s trained on. If the AI system isn’t fed with complete and relevant contract data, there’s a risk that it will miss crucial nuances or give misinformed recommendations.
2. Initial setup time
AI solutions in complex domains like contract negotiation require a significant initial time commitment. You have to train, test, and optimize models using historical contract data to ensure accuracy and reliability.
3. Ethical and privacy concerns
As with any technology that collects and processes data, you should always consider ethical and privacy policies when considering an AI contract management system. If not managed properly with the proper standards and protections in place, there’s a potential risk of data breaches or misuse.
4. Human oversight
Despite how fast technology and AI seem to be advancing, humans aren’t going anywhere anytime soon. AI needs checked. For example, it can sometimes overlook context or nuances that a human expert would catch. It’s essential to ensure that your team is still closely reviewing contracts generated or processed by AI to maintain the agreement’s integrity.
Best Practices for Implementing AI Contract Negotiation Processes
Now that we have the basics down, how do you put an AI-based contract negotiable process into place? Here are the steps to take and how to sustain it over time:
- Collaboration – Seamless collaboration between legal, procurement, and IT teams is non-negotiable. By ensuring constant communication and alignment with these teams, your AI CLM tool will be technically sound and amp back to your teams’ needs.
- Continuous Training – Just as legal regulations and procurement processes are constantly changing, so is AI! Check your AI models frequently for updates and ensure it’s continuously being trained with new data for accuracy.
- Data Privacy – Always enforce strict data protection protocols and ensure your AI tools comply with regional and global data protection regulations, like GDPR. Regular audits are paramount.
- Pilot Programs – Before implementing AI-driven contract negotiation on a larger scale, running pilot programs is beneficial. These smaller-scale tests allow teams to identify potential hiccups and get a tangible sense of the tool’s benefits and limitations.
The Future of AI in Negotiations
Whether it’s a sales or vendor contract, a unilateral agreement, or an employment contract, contract negotiation is often so complex that traditional, manual processes are simply inadequate.
Businesses require intuitive, next-gen CLM systems to secure and streamline a successful negotiation. Most importantly, enterprises must leverage AI to develop smarter contract strategies and gain an edge in negotiations.
With AI-powered contract negotiation functionalities such as automated risk discovery, scoring, and advanced analytics, your legal and procurement teams will be one step ahead.
Reach out to learn more about how to implement AI in your contract negotiation processes.
Additional Resources
14 Contract Negotiation Strategies and Techniques
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