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Common Contract Mistakes

5 Common Contract Mistakes Legal Teams Make and How AI Can Fix Them

Ashutosh Sharma

Legal contracts are essential for organizations because they create a formal agreement between parties, clarifying their rights, duties, and expectations. 

For legal teams, contracts act as a protective tool. They help prevent misunderstandings and disputes by clearly defining the terms of an agreement. 

This offers security and a clear way to seek resolution if issues arise. 

This blog discusses common contract mistakes legal teams make and examines how AI is changing contract management for these teams.

Mistake 1 – Incomplete or Vague Contract Terms

Legal teams sometimes draft contracts using unclear language or leave out important terms. This can lead to costly mistakes. Though it may seem harmless during the drafting phase, this lack of clarity can result in significant and expensive problems later on.

Let’s look at some numbers:

  • Poor contract management can cause an average loss of 8.6% to 9.2% of a company’s annual revenue, according to World Commerce & Contracting. 
  • The Association of Corporate Counsel also reports that breaches of contract due to unclear language are common legal issues, impacting about 58% of in-house legal departments.

Legal Costs in the US

Cost Category Average Cost Range
Attorney Fees $250 – $1,000+/hour
Court Filing & Admin Fees $100 – $500+ per filing
Discovery Costs (per case) $5,000 – $2,993,567+
Expert Witness Fees $250 – $1,500+/hour
Total Litigation Cost (per dispute) $20,000 – $500,000+

Source: US Courts Website

How AI Solves for Vague Contract Terms

  • Clause Detection & Benchmarking

AI-first legal operations software can contracts and flag unclear phrases that might cause problems later. 

By removing disputes over interpretation, AI saves legal teams millions in costs.

  • Suggesting Alternatives

AI not only points out vague language, but it can also suggest standard wording based on previous contracts, regulations, or best practices. 

This promotes consistency and lessens subjectivity.

  • Learning from Past Disputes

Some advanced AI legal management softwares use over 200 million cases to examine historical contract disputes in the industry.

They pinpoint which unclear terms caused issues in the past and flag them in future contracts.

Mistake 2 –  Using Inefficient Contract Review Processes

Manual legal contract review processes are outdated. Companies that still rely on these processes face various issues, including 

  • Slower Deal Cycles

When a deal gets stuck in legal review, revenue recognition is delayed. This puts the business at risk of losing the deal to a competitor that moves more quickly. 

  • Resource Drain and Low Morale

Repetitive tasks keep lawyers from focusing on the important, complex legal matters they were trained for. This can lead to low morale as frustrated professionals seek more satisfying roles.

Let us talk numbers

  • Many case studies and user reports by Gartner show that AI can cut review times by an impressive 70% to 90%.
  • In addition to the time spent, manual reviews are prone to human error. Fatigue, oversight, and the sheer volume of information can result in missed clauses, inconsistent interpretations, and a failure to identify critical risks. 

Research from LegalTech News also indicates that 60% of contract errors come from human mistakes, often leading to disputes, financial losses, and damage to reputation.

How AI solves for Inefficient Contract Processes

While there is an initial investment in AI technology, the long-term cost savings are substantial. 

By automating routine review tasks, businesses can rely less on costly external counsel and improve the productivity of their in-house legal teams.

The boost in efficiency and accuracy also helps to lower risks, preventing expensive legal disputes in the future. Platforms like Legistify’s Contract Lifecycle Management Software, can cut review time by 30 to 50 percent while minimizing risks related to ambiguity.

Mistake 3 – Manually Extracting Data for Analysis

Manual data extraction and analysis of contracts is a big problem for legal teams. It wastes time, raises costs, and creates significant risks.

Instead of giving strategic legal advice, lawyers get stuck with the boring, repetitive job of searching through documents for key terms, obligations, and dates.

Let us look at the numbers

  • According to World Commerce & Contracting, companies can lose up to 40% of a contract’s value for every hour of ineffective contract management.

This wasted time can delay the launch of a new product by 6.5 days, leading to millions in lost revenue.

  • A report from Thomson Reuters called “State of the Legal Market” reveals that legal teams spend up to 3 hours a day just gathering and analyzing data from contracts for reports and insights.

How AI Solves for Manual Data Extraction and Analysis ?

  • AI changes contract analysis by automating the slow, manual task of data extraction. It converts unstructured legal documents into organized, useful data.

This allows legal teams to focus more on strategic tasks instead of administrative work.

  • AI tools use Natural Language Processing (NLP) and Optical Character Recognition (OCR) to read and understand contracts automatically.

Going through thousands of contracts by hand makes it hard to catch every risk or deviation from a standard approach. AI systems can also learn from a company’s internal policies and a large dataset of contracts to flag high-risk clauses, inconsistent terms, or missing information.

For example, Legistify’s legal tech software is trained on 200 million legal cases to identify potential issues in legal contracts. 

Mistake 4 – Poor Version Control

The old-school method of managing contracts through email, word documents, and shared drives is not only inefficient but also a major source of risk and a significant bottleneck for the business.

In a legal dispute, it is essential to provide a clear, tamper-proof record of every change, comment, and approval. Manual processes, like saving “v1,” “v2,” and “v3 Final,” do not offer this important audit trail.

Let us Talk Numbers

  • According to World Commerce & Contracting (WorldCC) and the Association of Corporate Counsel (ACC), finalizing a contract usually takes between 20 and 30 days. A lot of that time is spent on version control and negotiation. 
  • Forrester has found that using CLM software can cut contract approval time by an average of 82%.

AI-powered contract lifecycle management (CLM) platforms, like Legistify’s , aim to solve these issues by centralizing and automating the entire version control process. 

A CLM system serves as a secure central repository for all contracts. Every draft and finalized version is stored in one place. This reduces the risk of a lawyer working on a local copy that isn’t the most recent version. 

Every change, comment, and review is automatically logged in a complete audit trail. An AI-powered system not only shows you the latest version but also gives you a full history of the contract’s evolution. 

This includes who made a change, when they made it, and what the change was, creating a solid record for legal defense and compliance.

Mistake 5 – Failure to Track Renewal Dates 

Manually tracking contract renewal dates poses a significant financial and operational risk for legal teams. 

Without a centralized, automated system, companies face various costly issues, such as being stuck with unfavorable terms or losing valuable clients or vendors. 

Legal teams often depend on manual methods like spreadsheets and calendar reminders, which are very prone to human error.

Let us Talk Numbers

  • Missed renewal or termination dates can be problematic. If a company does not terminate an unfavorable contract, it could end up stuck in an expensive auto-renewing deal for another year. 
  • On the other hand, if a key client contract is not renewed on time, it may result in a direct loss of revenue. A survey by Dock 365 found that nearly 50% of organizations do not track at least some of their contracts effectively, which leads to missed renewal dates.

How AI Solves for Manual Renewal Tracking  

AI-powered document management softwares aims to directly tackle the risks of manual renewal tracking. AI uses Natural Language Processing (NLP) to read and extract important dates from every contract, including renewal, termination, and notice dates. 

This process, which would take a human hours, gets done in minutes, with a near-perfect accuracy. 

With all data in one place, AI platforms like Legistify can send automated alerts to relevant stakeholders well before a deadline. 

This reduces the risk of human error and gives legal, finance, and procurement teams plenty of time to review, renegotiate, or terminate a contract.

About Author

Ashutosh Sharma

Ashutosh Sharma is a skilled SEO and content specialist based in Gurugram, Haryana. He blends expertise in SEO with a passion for creating clear, engaging content that speaks directly to readers. With experience in keyword research, link building, and on-page optimization, Ashutosh focuses on delivering valuable and trustworthy information, especially for education and technology audiences.

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