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Last updated on 2024年4月20日

What challenges do companies face when implementing AI for contract management?

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Contract management is a crucial process for any business that deals with suppliers, customers, partners, or regulators. It involves creating, negotiating, executing, and monitoring contracts to ensure compliance, performance, and value. However, managing contracts manually can be time-consuming, error-prone, and inefficient. That's why many companies are looking for ways to automate and optimize their contract management with artificial intelligence (AI).

AI is the ability of machines to perform tasks that normally require human intelligence, such as understanding language, recognizing patterns, learning from data, and making decisions. AI can help contract management in various ways, such as:

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Márcio Zampiron

Head Cloud|OCI|AWS|GCP|FinOps|CKA|CKAD|DevSecOps|SysAdmin |SRE|Cloud Architect|SOA Architect|Integration…

1 Extracting key information

AI can use natural language processing (NLP) and optical character recognition (OCR) to read and analyze contracts, extract key information, such as parties, terms, clauses, obligations, and risks, and store them in a structured format. This can reduce the need for manual data entry, improve accuracy, and enable faster and easier access to contract data.

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Márcio Zampiron

Head Cloud|OCI|AWS|GCP|FinOps|CKA|CKAD|DevSecOps|SysAdmin |SRE|Cloud Architect|SOA Architect|Integration Architect|Oracle Middeware Consultant
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One major challenge companies face when implementing AI for contract management is extracting key information from contracts. Contracts often contain complex language and are formatted in various ways, which can be difficult for AI to interpret consistently. This requires sophisticated NLP capabilities to accurately understand, extract, and categorize the relevant data from the legal text. Additionally, the AI system must be trained on a diverse dataset of contracts to handle different styles and clauses effectively. The quality of the data input and the training of the AI models are crucial to ensure the system can reliably extract important details like payment terms, deliverables, and termination clauses without errors.

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2 Generating and reviewing contracts

AI can use natural language generation (NLG) and machine learning (ML) to create and review contracts, based on predefined templates, rules, and best practices. This can speed up the contract drafting and approval process, ensure consistency and compliance, and avoid errors and disputes.

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3 Monitoring and managing contracts

AI can use data analytics and predictive modeling to monitor and manage contracts throughout their lifecycle, such as tracking performance, deadlines, milestones, renewals, and changes. This can enhance visibility and control over contract obligations, identify opportunities and risks, and trigger alerts and actions.

However, implementing AI for contract management is not without challenges. Some of the common challenges that companies face are:

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Saravanan K

Global Supply Chain | Strategic Sourcing | Supplier Management | Manufacturing | Supply Networking | Problem Solving | Negotiation | Contract Management | Procurement | Project Management | Product Development | LSSBB
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AI has the potential to revolutionize contract management by providing companies with enhanced visibility, control, and decision-making capabilities. However, implementing AI presents challenges such as data quality, legal implications, human oversight, and change management.

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4 Data quality and availability

AI relies on large amounts of high-quality and relevant data to learn and improve. However, many companies have incomplete, inconsistent, or outdated contract data, stored in different formats, systems, or locations. This can affect the accuracy and reliability of AI outputs and insights. Therefore, companies need to invest in data cleaning, standardization, and integration, as well as data governance and security.

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Saravanan K

Global Supply Chain | Strategic Sourcing | Supplier Management | Manufacturing | Supply Networking | Problem Solving | Negotiation | Contract Management | Procurement | Project Management | Product Development | LSSBB
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AI's effectiveness in contract management hinges on high-quality data. However, many companies struggle with incomplete, inconsistent, and outdated contract data, scattered across different systems. This can lead to misinterpretations, inaccurate performance tracking, and ineffective risk assessment. Companies need to invest in data cleaning, standardization, and integration to ensure data accuracy and consistency. Data governance and security measures, such as access controls, data encryption, and auditing, are crucial to protect sensitive contract information. Addressing these areas, companies can make a robust system for AI-powered contract management, leading to improved efficiency, risk mitigation, and strategic decision-making.

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5 Legal and ethical issues

AI can raise legal and ethical issues, such as liability, accountability, transparency, privacy, and bias. For example, who is responsible if an AI-generated or reviewed contract contains errors or breaches? How can companies explain and justify the decisions and actions of AI? How can companies protect the confidentiality and rights of the parties involved in contracts? How can companies ensure that AI does not discriminate or harm anyone? Therefore, companies need to establish clear policies, guidelines, and frameworks for the use of AI in contract management, as well as monitor and audit its performance and impact.

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6 Change management and adoption

AI can change the way contract management is done, requiring new skills, roles, and processes. However, many companies face resistance or reluctance from their employees, stakeholders, or partners, who may fear losing their jobs, authority, or trust. Therefore, companies need to communicate the benefits and limitations of AI, provide training and support, and foster a culture of collaboration and innovation.

AI can offer significant advantages for contract management, such as efficiency, accuracy, and value. However, companies need to overcome the challenges of data quality and availability, legal and ethical issues, and change management and adoption, to ensure a successful and sustainable implementation.

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Saravanan K

Global Supply Chain | Strategic Sourcing | Supplier Management | Manufacturing | Supply Networking | Problem Solving | Negotiation | Contract Management | Procurement | Project Management | Product Development | LSSBB
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Companies must effectively communicate the benefits and limitations of AI, providing training and support to equip employees for the new demands. Fostering a culture of collaboration and innovation will help integrate AI seamlessly into the organization's fabric. While AI offers substantial advantages in contract management, organizations must carefully address data quality and availability, legal and ethical considerations, and change management strategies to ensure successful and sustainable implementation. By overcoming these challenges, organizations can harness AI's power to enhance efficiency, improve accuracy, and unlock greater value in their contract management processes.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What challenges do companies face when implementing AI for contract management?

1

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3

4

5

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1 Extracting key information

2 Generating and reviewing contracts

3 Monitoring and managing contracts

4 Data quality and availability

5 Legal and ethical issues

6 Change management and adoption

7 Here’s what else to consider

Supplier Sourcing

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What challenges do companies face when implementing AI for contract management?

1

2

3

4

5

6

7

1 Extracting key information

2 Generating and reviewing contracts

3 Monitoring and managing contracts

4 Data quality and availability

5 Legal and ethical issues

6 Change management and adoption

7 Here’s what else to consider

Supplier Sourcing

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