The first half of 2019 was a busy time in the Legal AI Market, with over 20 significant VC investments and M&A transactions across a spectrum of Legal AI technology companies. This level of investment reflects a conviction that AI-assisted legal is here to stay and will change the way enterprises conduct legal operations.
Tracking AI market moves makes for interesting speculation, but it doesn’t answer the question of which technology will provide the best return on investment for your company. Sorting out which AI tech to buy can be like walking unprepared into a supermarket right before hosting a dinner party for your new in-laws. You realize you have no idea what they like, if they have food restrictions, or what ingredients you need to buy. You (either) end up buying the wrong items or go home empty-handed.
Planning for Legal AI
Start where there is both pain and an openness to try potentially better ways of doing familiar tasks – both of these are required ingredients for a viable opportunity. Pain can be expressed in multiple ways.
Example of Pain Points:
- It takes two months and $20/contract to outsource a review of your vendor contracts to answer a single inquiry. You repeat this process for each inquiry. You average 3-5 inquiries per period.
- Many contracts are not in the repository and there are multiple versions.
- Many contracts are not searchable.
- It can take a “long” time to find clauses and terms; you are never sure you have the latest or which have met the acceptance standard.
- The metadata associated with all of the contracts is questionable or incomplete which can result in incomplete or inaccurate reports and analysis.
- It can take 3-5 days to respond to an RFI or Sales contract review; you are putting revenue at risk.
Prioritize the pain points by impact to the organization – look explicitly for those with the most potential in terms of revenue or cost savings from an improvement. Listing possible alternatives can help provide perspective.
Now, look at who the stakeholders are for each pain point. Is the pain shared equally across the groups? Is there an appetite for, or, a mandate to change that can sustain the rollout of new technology and potential process changes? Most technology projects that fail do so because of poor user adoption.
When the level of pain and willingness to effect change align, add the use case with a target objective to your shopping list of technology ingredients.
Example Use Case with Target Objectives:
- Clean-up contract repository with 100% searchable contracts and rich metadata
- Reduce search times by 50%
- Accelerate turnaround time on Sales Contracts by 30%
- Improve M&A due diligence: accuracy, speed, and completeness
- Portfolio review in hours/days without incremental costs
- Analyze contracts for risk: provide a list of high, medium, and low-risk contracts for a selected topic
Categorize your use cases by those that have similar requirements. Combine them into a single use case for evaluation and re-verify the expanded scope of the opportunity – this will save/generate $50,000, $500,000, or $5,000,000.
Account for corporate governance and compliance requirements for both your company and those with whom you have contracted. Evaluate the risks, including the monetary and non-monetary, such as corporate brand and vendor relationships. Utilize these values to weight your use case rankings.
If you only have beer mugs, would you buy and serve expensive champagne to your new in-laws? Probably not. When planning for Legal AI, many influencing factors will shape your buyers’ journey. Accounting early for them will speed identification of the right technology for your company.
Example Factors for Consideration:
- Do you know where all your contracts are now?
- How many contracts do you have?
- Do you have existing legal technology – including contract management modules or systems?
- Have you adopted a Cloud-first IT policy or retained an on-premise approach?
- How often do you outsource legal tasks or do them in-house?
- What is your ratio of highly skilled legal experts and lesser skilled associates?
- Is the workload growing faster than the number of qualified resources?
- Do you have a dedicated AI-team with legal and domain expertise?
- How much of the legal work is entirely standard and how much on 3rd party paper?
- How often do outside factors like compliance, audits, and IBOR impact you?
- Would you benefit from being able to add new use cases quickly without initiating a new RFP?
At this point, you have compiled enough information to begin a decision tree that will quickly narrow the list of potential Legal AI technologies right for your company.
Or in other words, you know your father-in-law prefers German beer, rare rib-eye steak and a loaded baked potato. His wife drinks French Chardonnay and is a Pescatarian.
Enjoy shopping for Legal AI technology. A well-selected solution will quickly prove its worth.
If you’d like help with your buyer’s decision tree, please contact Seal.