With great power comes great responsibility. While AI has enormous potential in contract management, we can not turn away from its limitations.  There are also limitations to its use. To start with, one of the main limitations is data quality. Or in other words - AI is only as good as the data it is trained on.

Data quality

In order for AI to be effective in contract management, organizations need to ensure that their contract data is accurate, consistent, and comprehensive. This can be a challenge for organizations that have large volumes of contracts stored in disparate systems or formats. To tackle this problem, before investing in legacy contract analytics, it is important to clean up the entire house.

Start with reviewing all the storage spaces. Gather the entire data set. Move through categorization of document and data types, unification of the format, followed by metadata collection all the way to separate what is relevant from what isn’t. An ironic fact about this is that AI can help you get the data organized and labeled as well, in order to process it in subsequent workflows. 

Potential bias

Another limitation of AI in contract management is the potential for bias. As Sam Altman, the CEO of OpenAI, notes, "AI is only as unbiased as the humans who create and train it." This means that if the data used to train AI is biased in any way, the AI will also be biased. This can lead to inaccurate analysis and decision-making and can have serious consequences for organizations.

To help illustrate let us dive into an example. Let us pretend that we are in the medical field formulating an outcome for clinical trials. If we tested a new drug with positive results only on young male adults, will the same results automatically apply to elderly males with cancer, children, or pregnant women? It would be highly doubtful. 

That is why you want to put some thought into how you are going to select a data set for the AI to train on. Solid solution providers should be able to provide a data science team to walk you through this, making sure that AI learning and finetuning process will result in getting the most out of your favorite AI-powered CLM solution. 

Our overreliance on AI

In addition, there is also the risk of overreliance on AI in contract management. While AI can automate routine tasks and provide better visibility into contract data, it cannot replace the expertise and judgment of human contract managers. Organizations need to ensure that they are using AI to augment, rather than replace, their human workforce.

In addition to the limitations of AI in contract management, there are also risks associated with its use.

AI is not infallible

One of the main risks is the potential for errors or inaccuracies in contract analysis. While AI can analyze contracts more efficiently than humans, it is not infallible. Errors or inaccuracies in contract analysis can lead to serious legal and financial consequences for organizations. It is very important for any organization willing to adopt an AI-enabled solution, to monitor its performance and reliability at least during the adoption process. The results will improve over time, giving the organization a free hand but learning and fine-tuning are a priority for any implementation to be a success. There are multiple ways to mitigate the error rate so make sure you have a clear understanding of how to achieve perfection with your solutions provider.

Data breaches or cybersecurity threats

Another risk is the potential for data breaches or cybersecurity threats. As more organizations move their contract data to the cloud and rely on AI-powered contract management solutions, the risk of data breaches and cyberattacks increases. Organizations need to ensure that their contract data is secure and that their AI-powered solutions are protected against cyber threats. This should ideally be a cooperative effort of both, solution providers and respective organizations. Setting appropriate standards, and putting safeguards in place should minimize the threat. A good indicator of solid security standards on a provider's end can be certifications such as ISO 27001, reputable hosting services, a certain level of encryption, and also opt-out on customer data for training models utilized in their AI solution.  

In conclusion, AI has the potential to revolutionize contract management in procurement. However, organizations need to be aware of the limitations and risks associated with its use and take steps to ensure that they are using AI in a responsible and effective manner.

This includes ensuring that their contract data is accurate, consistent, and comprehensive and that their AI-powered solutions are protected against cyber threats. It also means recognizing that AI cannot replace the expertise and judgment of human contract managers and that organizations need to use AI to augment, rather than replace, their human workforce.

As organizations look to the future of contract management, AI is likely to play an increasingly important role. By embracing this technology and using it in a responsible and effective manner, organizations can drive better business outcomes and gain a competitive advantage in the marketplace.

We need to use AI to augment, rather than replace, our human workforce.

This article is part of our Transforming contract management with AI series. Check out more articles on our Blog.