How AI Can Be Applied to Contract Management Audits

Written by: Teo Spengler

April 15, 2020

5 minute read

Shared data connects the business world. To harness this connectivity, organizations must be prepared to alter their traditional business models by incorporating new artificial intelligence (AI) and machine learning technology. Read on to learn how applying this technology to automate contract management audits not only speeds up the audit process but also increases accuracy.

Traditional Auditing

Contract management auditing is traditionally an extremely time-consuming and labor-intensive process. It involves sifting through detailed data and reviewing for risks, deadlines, problem clauses and other issues. It usually involves selecting a “representative” sample of the information rather than running a complete analysis.

Traditional auditing can lead to delays and opens the process to human error. Selecting a sample set of documents for review doesn’t just take time, it carries built-in risk. If the set selected does not adequately represent the whole picture, it won’t offer a deep understanding of a company’s financial position.

Auditors and Big Data

Traditional contract management auditing is experiencing additional pressure as the world moves into the age of big data. Today, companies can generate enormous amounts of information that can be added to databases in order to make better, smarter real-time decisions. In addition, vast amounts of data available on the internet can be useful to many types of audit oversight. For example, many companies include big data from outside the company to supplement their own data and to create market advantages, manage risk, and improve performance.

The sheer amount of the data generated in today’s world mandates the evolution and digitization of audits. Auditors need to find a way to use this information to deliver accurate, high-quality contract reviews, focusing more effort on risk identification and business insight.

While new technologies increase the workload of auditors, they also offer new and better auditing solutions. Artificial intelligence, in the form of AI-powered contract software, allows machine learning tools to expedite the audit process and dramatically reduce the risk of human error.

Machine Learning Tools Note Patterns and Make Predictions

Engineers have long been intrigued by the idea that machines may be trained to learn in a way that approximates human learning. The concept of machine learning—a key subset of artificial intelligence—has evolved as data has proliferated and computer technology (such as processing speeds and storage capabilities) has advanced.

From email spam filters to the targeting ad functions of big tech companies, machine learning tools surround us in our everyday lives. But machine learning has an even greater role to play in the business world. The rapid data analysis capability it offers is changing the way many companies operate and will continue to do so in the near future. Contract management review auditing firms are among the businesses being affected.

Machine learning automates the development of analytical models that can be used to analyze data, noting patterns and making predictions. This type of AI applies an iterative approach to the analyzed data by recognizing patterns and applying those patterns to alter actions. While machine learning and traditional statistical analysis resemble each other in some ways, they are different processes that work in very different ways. Statistical analysis uses the probability theory to predict outcomes while machine learning employs mathematical equations.

AI Speeds Up Contract Review and Reduces Risk

In the past, contract review auditors had two missions that seemed to conflict directly with each other: perform contract review quickly and perform contract review accurately. In an attempt to balance these competing ends, auditors take representative samples of the contracts rather than work on the entire data population. While this results in speedier contract review, it leaves a lot of room for problems to fall through the cracks.

AI allows auditors to avoid this tradeoff. It limits the need to reduce the data through representative sampling techniques while both speeding up the entire contract review process and performing the contract review with greater accuracy than manual review, thereby significantly reducing a business’s risk exposure.

AI Technology Reviews More Data

You can find a wide range of AI contract software, and it pays to look around and compare. The best software contains machine learning algorithms that allow auditing firms to analyze more contracts or even the entire data population.

Certain software tools have been trained by industry experts to extract data from contracts quickly and accurately. The technology can sift through and identify virtually any contract language or clause. This allows audit teams to focus their testing.

AI algorithms make for good students because they learn from the auditors working with them. The software recognizes and tracks auditor conclusions on particular items, then applies their logic to similar items. This allows auditors to analyze a larger number of contracts, such as leases, in a much shorter timeframe than the traditional manual review process.

AI Provides Increased Accuracy in Audits

While the algorithms extract more information faster, the rate of precision is much higher than a slower human review. AI reduces human error dramatically and much less information falls through the cracks.

AI can also clean the data sample to make sure that the observations represent the problems accurately. An outlier is the term given to an observation that is different from other observations in some way and can result from input errors or data corruption. AI-enabled software sifts through documents for key contract terms, but it can also identify outliers. It is not possible to define and identify outliers in general because each dataset is unique, but an auditor can interpret the raw observations and decide whether an identified value is an outlier or not.

Sometimes a dataset can contain extreme values that are outside the range of what is expected and unlike the other data. This information makes it much easier for auditors to locate high-risk contacts.

For example, Kira’s contract review software quickly reviews very large volumes of documents while highlighting relevant audit data. Not only does this allow audit teams to complete the sampling efficiently, it also allows them to include larger sample sets for a more accurate result in the same amount of time.


AI and machine learning technology are fundamentally changing the way businesses operate and compete. In contract management audits, AI has the capacity to greatly improve traditional business models by enabling faster, easier and more accurate data analysis.