Artificial Intelligence (AI) has revolutionized the way businesses manage contracts. AI contract review helps companies manage agreements in more efficient and better ways. This is important as companies have hundreds of contracts stored in different locations and files.
Manually managing these contracts becomes exceedingly tricky because a lot of time and effort is spent finding and collating information. Moreover, inadequate contract management systems can cause companies to lose money.
The use of computers and AI software can help reduce the time and labor wasted in manual systems so that more time can be spent on productive work.
With that said, let’s find out how AI software is changing contract management methods.
- Organizing, Classifying, and Extracting Information
AI systems can be used in various ways such as to:
- Classify documents – They can identify similar types of documents and group them, making it easier to search for a particular contract type. This reduces time in searching for documents of a specific type. AI systems can use natural language processing (NLP) to extract clauses, notes, dates, comments, and metadata from contracts.
- Classify contracts by type – They can group contracts by their kind, like lease, independent contractor agreements, statements of work (SOWs), Master Service Agreements (MSAs), Non-disclosure Agreements (NDAs), etc. This can help decision-makers select required contracts for modification, renewal, renegotiation, or draft new contracts.
- Classify by clause – By scanning different contracts, important clauses can be picked up and placed in groups. The clauses can then be studied and modified or improved for future agreements. In some AI systems, the software can pick out relevant clauses for a new contract that a human can review.
This classification of stored information helps companies make informed decisions and better contracts. Computers can do this classification in a fraction of the time it will take an army of humans to do the same task, making AI systems indispensable.
- Better Contract Lifecycle Management
One of the ways companies lose money is by missing important renewal dates, expiry dates, key performance indicators (KPIs), and follow-up dates. AI can step in to stem these problems and help companies keep track of important milestones in the contract lifecycle. For example, AI can help with:
- Diagnostic and Analytical Searches – These can pick up important information like expiry or renewal dates to keep compliance on track and save the company a lot of time, effort, and money. Never miss a renewal deadline with AI systems to keep track of expiry and renewal information.
- Predictive and Cognitive Support – Using AI systems’ predictive intelligence, it is possible to find out where existing contracts are failing or falling short. This is so corrective action can be taken for future contracts. It is also possible for AI systems to point out differences in clauses and contracts, making it possible for a company to standardize its contracts and clauses.
- Smart and Dynamic Contracts
AI systems can understand and pick up similar clauses from stored contracts using machine learning (ML) and NLP. The similarities and differences in clauses from different contracts can be presented for human review to draft better contracts.
Some AI systems can do this on their own, subject to a legal team’s final review, enabling faster drafting of better and accurate smart contracts.
- Smaller Teams
One of the issues with manual systems has been the need for huge teams to spend hours and days poring over documents attempting to manage and keep track of contracts. Most of the tasks involving managing contracts are repetitive.
Such tasks are very suitable for computers that can work non-stop. Therefore, computers using AI to complete the job much faster enable companies to have smaller, leaner human teams with the computers doing the hard, monotonous, repetitive work.
- Managing Quality Contracts
The use of AI systems can improve contracts’ quality because they can compare and analyze clauses in different contracts. This can enable the legal team to draft contracts with similar clauses or enhanced clauses.
- Optimizing Time Spent in Reviewing Contracts
Using AI systems’ ability to pick, understand, and highlight differences in clauses, different versions of contracts can be reviewed in shorter periods, enabling faster turnarounds times.
- AI in Contract Risk Management
AI systems can provide risk assessment information. This enables officials to visualize the potential risks and take corrective action, thus saving the company from losing money due to faulty contracts.
The ability to assess and predict risks allows contract managers to make informed and effective management decisions in much shorter times.
Some Challenges in the Use of AI Systems in Contract Management
One of the biggest challenges in AI systems is the “training” of the “intelligence.” To train the system, it has to be given many existing contracts in a similar format. First, all contracts in an organization need to be converted into a standard format that can be fed into the system.
This means they first have to locate all the contracts stored at different locations in different formats. Once contracts are located, they need to be stored in a standard format.
This is a complete exercise involving finding all existing contracts, scanning and digitizing them, and storing them in a similar format. This enables optical character recognition (OCR) to convert them into usable text and arranging them in a way that allows a machine to “learn.”
The system has to be trained to make sense of the data it has been given. Only after the system learns and understands the documents can it provide useful contract management inputs.
The benefits of using computers and AI has grown in recent times. The advantages and benefits of using AI systems include creating and managing standard contracts and keeping track of important dates and deadlines.
However, these are just a few reasons why AI software is the future of contract management.
As we understand the systems better, they are sure to improve and provide even better facilities in the foreseeable future. However, we need to realize that there is a lot of initial work that has to be done to ‘train’ the AI system before it can produce results.