In today’s fast-paced working world, managing contracts can be a time-consuming and complex task, where things can quickly get messy. From data extraction to contract analysis, contract management requires significant resources and attention to detail. However, with the arrival of AI, contract management has become more efficient, accurate, and even compliant. That’s why we’ll take a look at the 5 best practices of AI in contract management here.
In this article, we’ll cover:
- Best practice #1: Define clear objectives of using AI in contract management
- Best practice #2: Ensure data quality
- Best practice #3: Seek expert advice
- Best practice #4: Keep an eye on how AI is working out
- Best practice #5: Ensure transparency and compliance
But before any of that…
What is AI?
AI stands for ‘artificial intelligence’. It refers to a range of computer programs and softwares that can do tasks that would normally require human intelligence to complete. In essence, AI software is programmed with logical algorithms that give them the ability to “think” and act appropriately.
AI has been around for a while, but it was the launch of ChatGPT in late 2022 that really led to its big breakthrough. We’ve probably all had at least a few goes on ChatGPT by now. So whether you find it fascinating, slightly terrifying or are indifferent toward it, we can all agree that we’re only just scratching the surface of what AI can do, especially in contract management.
So, without further ado…
Best practice #1: Define clear objectives of using AI in contract management
The first of the best practices of AI in contract management is to define clear objectives. These objectives should be specific, measurable, achievable, relevant, and time-bound (SMART). This will ensure that the AI system is designed to meet the specific needs of the contract management process.
For example, the objectives could include reducing the time and effort required to manage contracts, improving accuracy in contract analysis, and enhancing contract visibility to identify trends, risks, and opportunities.
To achieve these objectives, organisations should establish a clear roadmap for AI implementation in contract management. This roadmap should include identifying the key stakeholders, setting project milestones, and developing a data governance framework. By defining clear objectives and establishing a roadmap for AI implementation, organisations can ensure that the AI system is aligned with their business objectives and can deliver measurable results.
Best practices of AI in contract management #2: Ensure data quality
Data quality is critical for the successful implementation of AI in contract management. The data used for training the AI system must be clean, accurate, and reliable. It is important to establish a data governance framework to ensure that data is properly collected, stored, and maintained. This framework should include data quality checks, data cleansing processes, and data security measures.
To ensure data quality, organisations should conduct a thorough data audit to identify any data quality issues. This audit should include a review of the data sources, data formats, and data integrity. Once data quality issues have been identified, organisations should develop a plan to address these issues. This plan should include data cleansing processes, data quality checks, and data security measures.
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Best practice #3: Seek expert advice
Collaboration with experts in AI and contract management can help organisations gain valuable insights into the latest technologies, tools, and best practices. Experts can also provide guidance on how to effectively integrate AI into the contract management process. This collaboration can take many forms, including workshops, seminars, and conferences.
Organisations should also consider partnering with AI vendors who have experience in contract management. These vendors can provide access to pre-built AI models and contract management solutions, as well as technical support and training. By collaborating with experts in AI and contract management, organisations can stay up-to-date with the latest technologies and best practices, and ensure that their AI system is optimised for contract management.
Best practice #4: Keep an eye on how AI is working out
AI systems require continuous monitoring and evaluation to ensure that they are performing effectively. Regular review of the system’s performance metrics can help identify areas for improvement and optimisation. Regular testing and evaluation can help organisations make data-driven decisions about the use of AI in contract management.
To continuously monitor and evaluate the AI system, organisations should establish a feedback loop. This feedback loop should include regular performance reviews, user feedback, and system audits. Organisations should also establish clear metrics for measuring the effectiveness of the AI system. These metrics could include the time and effort required to manage contracts, the accuracy of contract analysis, and the identification of risks and opportunities.
Read also: How AI is changing contracts
Best practice #5: Ensure transparency and compliance
AI systems should be transparent in their decision-making processes and comply with legal and ethical standards. This includes ensuring that data privacy and security standards are met and that the AI system is not biased or discriminatory.
Transparency is critical for building trust in AI systems. Organisations should ensure that the AI system’s decision-making processes are transparent and explainable. This means that the system should be able to provide clear explanations for the decisions it makes. This can help users understand how the system works and make informed decisions about its use.
In addition to transparency, compliance is also important. Organisations should ensure that the AI system complies with legal and ethical standards. This includes ensuring that the system meets data privacy and security standards and that it is not biased or discriminatory. It is important to establish clear guidelines for the use of AI in contract management and to ensure that these guidelines are followed.
To ensure compliance, organisations should conduct regular audits of the AI system. These audits should include a review of the system’s data inputs, decision-making processes, and outputs. They should also ensure that the AI system is aligned with legal and ethical standards, such as data privacy regulations and anti-discrimination laws, making this a great best practice of AI in contract management.
The key takeaways
AI has the potential to revolutionise contract management by optimising efficiency, accuracy, and compliance. By following the best practices outlined in this article, organisations can ensure that their AI system is aligned with their business objectives and is optimised for contract management. From defining clear objectives to ensuring transparency and compliance, these best practices can help organisations achieve a competitive advantage in today’s business environment. These are just 5 of the best practices of AI in contract management to help you get started.