Artificial intelligence (AI) is already enhancing professional work in a variety of industries. AI advancements can benefit contract management software systems, particularly if contract intelligence engines built on a foundation of machine learning are fed a nutritious diet of relevant contract data.
Inefficient contracting is estimated to cost businesses 9 percent of the value of a deal, depending on the circumstances. As a result, several businesses are embracing contract management software such as SpotDraft.
The largest issue that businesses encounter when it comes to contracts is the large number of contracts that must be tracked. These agreements are frequently incoherent and difficult to organize, maintain, and update.
There is no simple way to assess complex outsourcing agreements or compare how a condition is phrased across divisions because most organizations do not have a database of all the particulars in their contracts, let alone an efficient way for extracting it.
It not only requires a lot of labor for creating, executing, and improving contracts, but it also consumes a lot of manpower for drafting, executing, and enhancing contracting procedures and the transactions that these contracts govern. Artificial intelligence (AI) and other new technological advancements are now aiding businesses to overcome several contracting issues.
Incorporating artificial intelligence with a contract management system has converted business opportunities by reconsidering the real value of contracts that had been submerged for years in millions of folders. Artificial intelligence can be utilized for converting disorganized contract documents into organized enterprise data.
AI in contract management can aid businesses to identify business risks and opportunities. Since AI comprehends contract language and clause definitions, it converts contract management from a fixed document management system to an effective, strategy-making machine.
Below are several aspects where AI is changing contract management.
Smart Drafting
An AI-enabled Contract management system assists intelligent contract development by automatic detection and arranging of contracts. CMS employs Machine Learning algorithms for learning from historical contract track records, identifying patterns, and recommending authorized, admissible pre-defined keywords and contract clauses.
A context-based analysis is an essential component of an AI-enhanced CMS. This means that the CMS discovers the related conditions that should be used for certain contract types while formulating contracts. For example, if the dealer is based overseas and across borders, it will recommend that a currency fluctuation clause be included in the procurement contract.
Recognition of Patterns
When a contract management system receives hundreds of thousands of legal documents, manually identifying every clause for future processing can become tedious. Machine learning techniques, on the other hand, can aid in recognizing the clause’s name based on its contents.
One can submit a document into a contract management program and tags can be applied to it automatically using this trained model. If the algorithm concludes that a clause was named incorrectly, the correct label can be provided for a given text, and it should accustom itself after a few iterations of the clause and avoid repeating the same mistake.
Streamlining of Contracts
Contract managers should have a track of the time taken for completing specific tasks and the jobs which produce delays and lengthening cycle times for saving time and money caused by inefficient contract workflows. AI-powered contract management systems provide task performance monitoring and intelligent process automation.
Contract managers can track the time taken by employees for completing the assigned tasks, which encourages accountability. Tasks can then be escalated quickly to keep the contract lifecycle going and enhance timeliness.
Contract managers utilizing AI can have a track of the number of days a particular contract has been in every stage of the contract lifecycle. It also offers clear visual depictions of work data and reports.
As a result, constraints in the workflow cycle can be quickly identified, allowing ineffective contract lifecycle management approaches to be eliminated. Contract managers can reassign responsibilities and rotate task assignments as they gain a better understanding of why their contracts are being delayed.
Analytics and Perceptions
A contract management solution powered by AI provides businesses with the perceptions required for getting the most out of their analysis. It can help businesses evaluate enormous numbers of contracts and report on contractual data from the system across the contract database, locations, and languages.
User-defined dashboards can be generated as required for reporting key performance indicators (KPI), service level agreements (SLA), milestones, and more aspects. It is now possible for understanding corporate payment responsibilities or identifying all contracts that are subjected to a specific rule, like required quality assurance or contract conditions. Enhanced contract visibility improves performance tracking, compliance, and obligation management.
AI-enabled technologies utilize natural language processing for screening through documents, classifying clauses, and highlighting discrepancies between document versions. This enables the system for reading contracts and tag any conditions or provisions that are not in the best interests of the organization. It can suggest alternative terms that lower risk and protect the company.
