AI & Construction law: an essential and inevitable partnership
By Simon Tolson Senior, Partner & Dr Stacy Sinclair, Senior Associate, Fenwick Elliott LLP
Some claim that we are amid an “AI Armageddon”: every level of humanity will be massively disrupted by Artificial Intelligence (AI). Whilst much of this press is hype, the reality within the practice of law is that AI is indeed beginning to have a substantial impact. Ultimately, AI will be more disruptive to the legal profession than the move in the last century from carriage typewriters to word processors. For this reason, organisations that do not prepare for the changes being driven by AI today are likely to be left behind.
In the context of construction law, one area in which AI is making a significant impact, which we explore in this article, Part 1, is risk and contract management.
Part 1: Risk and contract management
“Risk and contract management” may sound boring and dull to some. However, when it comes to keeping on top of your construction contracts, nothing could be more important. Any tool which assists in this respect and increases the chances for a project’s success is therefore essential and its use is inevitable. It is only a matter of time before they become part and parcel of daily contract and project management routines.
Assuming for the moment risk and obligation management is paramount: do you review all contracts before signing, regardless of the value? Do you have an efficient and automated means of monitoring all obligations and risks within all of your contracts and an understanding of the differences or anomalies between each one?
Whilst there is not any one piece of software which will solve all of your problems, there certainly are platforms and technologies available now which utilise AI and machine learning to assist with some of the questions posed above.
This article looks briefly at some of the current technologies available1 and begins to consider how they may assist, particularly in the context of contract review/analysis and document automation.
Step 1: Identify what you want
First, recognise and identify the issue you want to solve. What is the outcome you need or work stream you want to make more efficient? What is the risk you want to manage? In other words, identify the “use case”.
Only once we identify the outcome required or the problem to be solved, can we set off shopping for and harnessing the various platforms/technologies to realise these objectives. It is a mistake to put the cart before the horse.
There are a number of technologies that go some way to assist with contract review and analysis. For example, technologies which read documents for the analysis and extraction of data.
One such technology is an AI platform for document review, which provides insight into data and contracts. It utilises pattern recognition algorithms to understand text by context and content, not just by key word searches.
Another example goes beyond simple contract clause searching and extraction and generates a detailed party-specific summary of obligations, liabilities and other meta-data from the contracts analysed. Each agreement, and its component issues, is assigned a risk rating based on the organisations’ specific risk policies.
In the context of construction, infrastructure and energy projects it is relatively easy to see how these types of technologies can be instrumental in contract review and analysis. The possibilities are endless, for example:
- a review of a vast number of contracts to highlight and categorise possible clauses/issues which require a lawyer then to analyse. This perhaps could be helpful in the situations where the majority of the agreements are nearly similar (but not quite) or where the agreements normally would not have been reviewed at all given their perceived risk or value position; and
- an extraction of key data and obligations from contracts across the project(s), or indeed the company, into spreadsheets, reports or other software to manage and monitor risk and liability. Perhaps if needed, these obligations/data can then even be linked to programming software to monitor key dates and milestones.
With greater collaboration and innovation between lawyers, their clients and emerging technology, greater efficiency and efficacy is possible. Development of tailored solutions and services will, we suggest, minimise risks and improve the management of risk contract obligations, at a lower cost.
Document automation is also known as “contracting platforms” and are technologies that aim to speed up the generation, negotiation and completion of contract documents between contracting parties.
One such platform automates the generation of the contract and provides live-negotiation and analytics tools. It enables the user to create contract drafts which then can be negotiated with the other contracting party in real-time. Contracts can also be analysed during the negotiation process to see how they have evolved.
Again, collaboration between lawyers and their clients to establish contract templates and workflows for contract negotiations and completion, with the use of AI-enabled technologies, will minimise risks where possible and enhance efficiencies. In the construction industry where standard forms and standard terms and conditions are regularly used, and in an era of the rise of the Smart Contract, it is only a matter time before the automation of contract generation and completion becomes the norm.
With greater collaboration between lawyers and clients we suggest AI can bring superior efficiencies and efficacies to contract generation, review, analysis and management. This is but one use for AI in the context of construction law. Part 2 will consider the use of AI in predicting the outcome of disputes.
Whilst there indeed is a significant amount of blather around AI, we are of the view that AI and construction law are an essential and inevitable partnership: if you are not implementing it now, you certainly will be, to some degree, in the very near future – either by choice or by obligation.
- 1. Fenwick Elliott LLP does not endorse or recommend any of the specific companies/technologies identified in this article. They are referenced by way of example only.