Risk and Reward in Contract Analysis: Why AI is Not Enough

By Ryan Drimalla, FTI Technology 

Every organisation maintains contracts, and once executed, many simply file them away without a second thought until an issue or renewal arises. On the surface, such a lack of process and protocol may seem benign, or merely inefficient. However, during an enterprise-wide event, such as a merger, divestiture, compliance issue, new regulation or other issue that requires contracts to be examined on a tight deadline, this disorganisation can become a massive problem.

Proactive organisations – or those that have faced challenges stemming from poor contract management – are beginning to address their approaches to contracts, looking to move from a non-centralised position to one that allows for mitigating risk and maximising financial returns. The growing adoption of contract analysis is also intersecting with the shift toward strategic and holistic information governance and increasing reliance on advanced data analytics and artificial intelligence applications. According to the Blickstein Group Law Department Operations survey, 34 percent of respondents currently use AI for some operations, usually involving technology-assisted review for e-discovery. However, half say they expect most law departments will begin using it for legal work in the next three years.

As corporations recognise that their data is much more than an impenetrable mass, rather a mineable source of insights that can yield BI and inform strategic decisions, they are driven to analyse it in a unified manner. In the contracts space, there has been a lot of chatter about AI and its ability to transform processes. While new tools will undeniably speed up and strengthen analysis, the technology is not a panacea. Without the right people to apply them and the processes to manage them, contract analysis efficiency gains will remain out of reach.

Building an Effective and Efficient CI Process 

There are several aspects to building a sound contract review process, and proper planning will allow organisations to reap all the benefits. Fortunately, many organisations do not have to start from scratch, and the muscles they need to implement programs have been developed in the context of e-discovery, M&A or other data management systems that have been successfully deployed.

The first step is creating the backbone of a contract analysis process: identification and collection. While finding and collecting contracts seems simple, they are, in fact, often scattered across the enterprise in a staggering variety of disparate locations. While some contracts may be accounted for in a central repository, just as many others may be ‘hidden’ in file shares, hard drives or cloud storage. For many organisations, this spans borders, adding data privacy complexities and considerations, particularly around what data can be exported from certain countries and how. Improper collection increases risk and lost efficiencies, and multiple collections or the need to correct errors can make it difficult to hit deadlines.

While identifying where data is located can be difficult for a number of reasons, organisations can use technology to search, collect and dig beneath the obvious data tags to organise documents by group and scope. Once contracts are collected and loaded onto a selected review platform, data extraction, which must include thorough identification of risk components, goals and other issues, can begin. This is when the technology team’s expertise is paramount, and can be bolstered by the strategic use of AI. When deployed thoughtfully, AI can increase efficiencies by accurately identifying and surfacing terms and conditions and clustering the documents to inform workflows and priority.

Strategic Application of Advanced Technology 

Having a strong team of professionals and a solid process in place positions the legal team to take full advantage of leading-edge tech. While many perceive AI as the pinnacle of innovation, in reality, it is one tool for solving some of the problems endemic in the process of analysing data. In the legal and compliance environment, AI can be leveraged to enable efficiency and provide predictive analysis. In the efficiency use case, it automates work that was once carried out manually by lawyers. In the predictive analysis use case, tools predict outcomes that help lawyers make informed decisions about the dataset (for example, which contracts are likely to end up in default). Below are a few key considerations for applying AI to these processes:

– Garbage in, garbage out: The results of any data analysis depends on the validity of the data loaded into the system. AI “learns” from the data, and thus “bad” information can cause exponential problems and lead to wrong decisions in processes.

– Erasing boundaries: One of the single biggest advantages AI provides is the ability to “read” unstructured documents, for example contract data that has not been abstracted into databases.

– Change management: Some people think about AI as “robot lawyers,” and worry they are going to lose their jobs. Positioning AI in relation to critical objectives with clear clarifications about what it can and cannot do will allay fears, enable a smooth transition and lead to better adoption of new tools.

– Be proactive: Contract review efforts are typically catalysed by a major corporate or regulatory event, but the processes and tools can be used to enable proactivity. AI can support broader contract management efforts that improve business hygiene and serve as part of running a sophisticated business operation.

While AI has enormous potential, it is still just software that is only as good as the people and processes around it. A successful program with the right balance of people, process and technology can ultimately enable an organisation to proactively identify problematic terms that expose the company to risk, glean previously unrecognised value from contract provisions and realise strategic business insights that reach far beyond the contracts themselves.

Ryan Drimalla leads operations and solution development for FTI Technology’s Contract Intelligence service. With over 10 years of experience in commercial legal practices, both as an attorney and contracts process subject matter expert, Ryan focuses on enterprise contracting requirements related to regulatory, compliance, risk and corporate transactions, tailored to the unique needs of notable clients across a wide range of industries.