Many CLM solutions claim to have AI. But assessments by Forrester and others reveal that most CLM solutions are still in preschool when it comes to AI capabilities.
Designed for procurement leaders to share with their vendor selection team, this handy 12-point checklist helps you more easily assess the true AI capabilities of each solution you're considering.
Real AI enables automated ingestion of all contract languanges from historical contracts and templates in any format.
“Automated capture and metadata clause tagging of legacy or third-party contracts” is one of the AI-powered CLM solution features that deliver business value, according to Forrester.
The NLP technology used should enable a semantic similarity engine, which is another of the CLM solution features Forrester identified to deliver business value: “Semantic analysis AI to identify new issues in contracts and apply new metadata tags.”
With context-based search, real AI will find contracts and provisions without you having to search the specific term.
Real AI leverages ontologies (or knowledge graphs) to enable human-like contract comprehension. The system can compare clauses to identify missing terms and pre-requisites, such as negotiation boundaries, policy transgressions, material changes, clause and template similarity, and obligation exposure – even if the words it is comparing are not the same.
Real AI can analyze all historical contracts, templates, clauses and supplier contracting behavior (for example: which clauses were most changed by suppliers; which suppliers made the most changes to contracts; which contracts have the highest risk) and present insights accordingly.
Dashboards should be dynamic, enabling deeper analysis based on insight revealed through your search questions. This is important because risk is often lurking in hidden places you don’t even know about. (If you knew where the risk lay, you’d have addressed it already.)
An AI-powered CLM solution should enable integration and cross-analysis of contract data with data from other systems – for example, accounting. Then you can see how risk is created through the interrelationships between functions, like contracting and AP, as just one example.
This is another of the CLM solution features that Forrester identified among six that deliver business value: “Linking contracts to results to improve contract language and contracting processes.”
The major source of learning initially is the analysis of historical contracts. The system should learn from what you have signed before to make template recommendations and initial risk ratings without heavy manually intervention.
Ongoing, the system should learn when you 1) alter a risk rating or the risk points assigned to different clauses and free-form a reason why; and 2) manually tag a clause. These training abilities should be a seamless part of the application that every user can easily take advantage of.
Suppliers’ contract edits – or in ContractAI’s case, supplier choices such as which clauses are edited the most – should be taken into consideration for AI models to improve the process. Only with supplier feedback can the efficiency of the process be optimized. den places you don’t even know about. (If you knew where the risk lay, you’d have addressed it already.)
Schedule an introductory demo to see the ways in which ContractAI leverages real AI to accelerate your time to contract and reduce your risk.Schedule a Demo