Speedread: Scaling digital businesses can harness AI contract review to:
Before signing, the systems will add most value before signing on contracts received from the other party (so called third party paper) but after signing equal value can be extracted on any contract (however it was originally produced).
Are you the COO of a scaling digital business without a legal team on whom colleagues dump the difficult contracts? Or are you that first legal hire or part of a small legal team supporting a business growing exponentially. Heavy odds are that you’re smart, agile, great getting things done, good with people but overloaded.
You want to be freed-up to give business critical and strategic advice which is highly valued by your business colleagues, so you need processes and technology which keep the contracting flowing, help build a flexible risk management structure, capture data and manage both the contract negotiation and post-contract management phases.
You’ve probably already implemented some process and technology for Efficient Contract Management. For example, you may have signed-up to one of the great contract automation platforms such as Juro which can allow your business colleagues to create, approve, sign and manage routine contracts such as sales and employment agreements. Or you might have worked some simple workflow features using your shared drive.
Whether you have a contracting platform or have chosen to create, store and manage contracts in a shared drive such as G-drive or Microsoft 365, AI can take your efficiency and value creation to a new level in a number of key ways. In a nutshell, these are (i) automated contract triage (ii) review of third party paper and (iii) extracting valuable data from your executed contracts.
What is AI guided contract review?
Today’s systems come in many forms. Most combine Natural Language Processing (NLP) and Machine Learning (ML) algorithms in a way that reads a contract and extracts key data. Some like Lexical Labs’ Tiro system will also provide a digital contract playbook so that contracts can be reviewed against a set of rules, policies and preferences and automate or partially automate the process of redlining, reporting, issues list creation and data capture.
AI based contract review is used commonly on bulk contract reviews involved in M&A due diligence or large scale repapering exercises. It is increasingly used for the review of draft contracts under negotiation.
In a traditional contract negotiation, one party creates a draft contract (often using a contract automation platform) and is similar to the ‘server’ in a game of tennis. The other party ‘returns serve’ by reviewing and responding to the contract either by a redline or by a simple list of requested changes. The parties then work to finalise the contract on terms which meet both parties requirements. AI guided contract review assists the ‘returner of service’ - companies that handle a lot of ‘third party paper’ but can also help either player if there is a lot of exchange of redlines. An AI system will then capture important data from the signed contract which assists its ongoing management.
A tennis analogy helps visualise the process but poorly describes what businesses actually want. They want to avoid points scoring, long rallies and debates over theoretical issues. They want a quick process that gets to a fair outcome and one which business managers, rather than lawyers, are put centre stage. Technology is leading us to a data driven collaborative process.
Some misconceptions about AI guided contract review
Industry commentators and tech vendors have overhyped AI so its first good to clear-up some common misconceptions.
First, an AI contract review system is never a panacea or is unlikely to automate fully contract review (at least in the next few years). It can, however, speed-up human review, create opportunities for business self service (by allowing business teams to review and negotiate contracts with no or minimal legal input) and give real time data capture.
Second, the systems nowadays do not require large datasets of example contracts and clauses and mostly work ‘out of the box’ on the types of contracts handled by digital businesses. They can be implemented often with minimal upfront time and cost.
Third, AI contract review is not restricted to extracting key data from large volumes of executed contracts. It can assist also on ‘in-flight contracts’.
Uses for fast growing businesses in the digital sector
Our research shows two types of digital businesses interested in AI contract review.
The first is one that has some form of contract automation platform that handles the creation, approval, storage and management of simple contracts. Juro is particularly popular with digital businesses - particularly those generating many routine contracts such as SAAS sales and employment on their own standard terms. The major benefit is that business and HR teams can create and manage those contracts and use collaboration, approval and workflow tools in the process.
The second one is one that manages their contracts without a contract automation platform, storing contracts in a shared drive and perhaps using a CRM system such as Salesforce. They may not have the volume of contracts that justify a specialist contracting platform or generally handle ‘third party paper’.
Both types of businesses can benefit from AI contract review, but it is helpful for the AI tool to integrate well with any contracting automation platform.
Most digital businesses have to handle third party paper which is time consuming, costly and painful (see - Handling the Pain of Third Party Paper).
Even when a SAAS business uses its own form of customer contract, the customer might insist that it signs data protection, confidentiality, infosec and other agreements on the customer’s own form. These might have onerous provisions such as broad and numerous compliance and reporting provisions, uncapped liabilities or clauses which override provisions in the SAAS contract. Many other digital businesses contract on the customer’s standard purchasing terms (which could be equally onerous).
Likewise, when those businesses buy goods or services, the contract is normally drafted by the vendor.
Review of third party paper can be a major distraction from more valuable tasks for a COO or legal officer. Engaging a traditional law firm will be expensive.
AI provides some exciting solutions for this problem:
A draft contract is received and automatically reviewed, classified by contract/service type and value and triaged. Low value routine contracts can be handled by the relevant business teams. Higher value/riskier contracts are tagged and Legal or senior management informed. This solution is very easy to establish and can be one of the first things a small legal team does to establish a legal portal (otherwise known as a ‘front door to legal’). Scanning a contract automatically can save valuable time.
Most pragmatic digital businesses normally have 5-10 key points they are concerned with if they review ‘business as usual contracts’ received from their customer or vendor. Mostly, these points are retained in the heads of the legal officer or COO. They don’t have the time to write-up a manual and doubt anyone would use it. At Lexical Labs, we can quickly create a digital contract playbook within our contract review system called Tiro, reflecting these requirements after a brief zoom call with a client. Draft contracts can then be reviewed automatically against that playbook. A well trained AI system can understand the same concept written in numerous different ways.
Here is an example of how Tiro guides users through a review of indemnities and caps on liability.
A major benefit of automated contract review is that business teams can upload, review and respond on contracts without ‘going to Legal’ (or outside counsel) in the first instance. The automated review takes seconds. As importantly, a business user doesn’t have to mark-up or redline the contract. Instead, a simple issues list can be created and tracked on a dashboard. This is shared with the other party. A lawyer may still be required to help resolve something that requires an understanding of the law, but we avoid the problem of queuing (and paying) for advice from a lawyer on routine matters that anyone with business experience could resolve.
Here is an example of an automated but editable issues list that a system can create.
Larger enterprises often engage specialist managed legal service providers (sometimes called Alternative Legal Service Providers) to review and negotiate their draft contracts. These services are cheaper per contract than the traditional way of hiring a lawyer but are still unaffordable to many smaller businesses and often involve an upfront time investment. AI is bringing these services closer to smaller digital businesses.
Lexical Labs offers small businesses the ability to upload their contracts into our secure cloud portal. Our Tiro system will review in seconds and provide a draft response to the other side (by way of an issues list). Users can then decide to take this forward or can request assistance from a lawyer or contract specialist to help finalise the contract. The user has flexibility to ask for assistance on specific issues or areas of the contract and pay only for this review. This modular offering squarely meets the needs of many business users who say ‘I can handle 85% of this contract myself - I only need help with the balance’.
By combining technology and modular review, the price becomes extremely affordable to a scaling business with limited budget. We estimate that the price can be as low as $50 per contract review - great value for money compared to the current price of an external legal review (minimum $500) or saving a number of hours to an inhouse lawyer or business manager.
After signing, AI can help provide digital management of contracts. Advanced data extraction allows the tracking of important events such as renewals, reporting, price adjustments. Such features go significantly beyond the basic data extraction offered by most CLM systems (which often focus on renewals). Businesses can also track their risk across their contracts in real time and without any additional time and cost retrieving and reviewing contracts. Here is an example dashboard created in Tiro, Lexical Labs’ system.
Over the next few years, the use of AI software in the review and negotiation will become commonplace for scaling businesses in the digital industry. The industry and users will need to work hard to overcome the challenges, change mindsets and unlock the potential of AI.