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Knowledge management and AI, a couple of videos, some solid article links and more!
Happy Friday! The year seems to be flying by!
In this edition we dive into why knowledge management and subject matter experts will be key to implementing the next wave of technology coming to market. Even if the technology is not yet ready, it is worthwhile to start preparing by documenting processes so they are ready to be automated.
Hopefully you find it useful and interesting. Please feel free to share with anyone that may be interested and have a great weekend!
Matt Basile
If you find this content valuable, please connect with me on LinkedIn.
Leveraging Tech in Transactional Matters
📗 Knowledge Management Will Be Key to Implementing AI in Real Estate Transactions
There are two key factors that I think will determine which law firms and corporate law departments are able to leverage new AI tools as they become production ready - neither is new or unique to the technology and both are hard.
🚀 First is change management - which is especially unique in law firms but will always be a challenge in most companies.
📚 Second, which is more subtle and overlooked, but extremely critical in legal, is knowledge management. If you are trying to implement a document automation solution, you need a good set of forms. If you are going to leverage a GenAI tool that can rewrite language in a document in the way you want, you need to be able to tell it how you typically re-write similar language and why / when you rewrite the language and provide examples.
Good lawyers have this stuff clearly in their head, can apply it consistently and usually can explain 80% of it every time to a junior lawyer (they will mark-up the remaining 20% when they review the junior lawyer's work).
Great firms and practice groups spend time organizing this information so that institutional knowledge of how to do tasks is not stuck in peoples heads but is written down. This is very hard because you have to take time away from billable work to create this library. These groups will be in the best position to leverage AI tools that soon will be capable of doing these really hard tasks.
In the context of a typical real estate transaction, some examples of where good KM will be helpful to leverage AI in the near future:
🏦 Purchase and Sale Agreement Review - Do you have a list of key issues if you are representing a buyer? Do you have your typical responses to common requests if you are representing the Seller? You may also have client-specific issues to raise or $ thresholds to confirm.
😊 Loan Document Review - Similar to reviewing a Purchase and Sale Agreement, other than confirming deal specific points, there are probably a number of concepts in most sets of loan documents that need to be tweaked to make the documents more favorable to the Borrower (recourse carveouts, cure rights and you might like to add reasonably or material in hundreds of places). On the lender side, you will have corresponding fallback language to commonly negotiated provisions.
🔍 Due Diligence Review - Everyone has their preferences with respect to due diligence review and often there are client specific hot button items, but for the most part most folks should be able to review title and survey, leases, searches and opinions in a consistent manner. This can be done across a group of lawyers by creating standard protocols with notes for client preferences.
There are many other examples depending on what type of matter you are working on, but if you have written up in detail the basics of how you would like these tasks done, you will be in great shape to explain to the AI tool how you want them to complete the task when the tech is ready.
Worst case, you will have a great training tool for associates! Best case, you will also be able to supercharge your practice quickly as tools become available. 🚀🚀
Articles and News
🏆Earning Lawyer's Trust, Flat Fees & The Outlook for 2024
Solid discussion between legal tech experts Horace Wu of Syntheia and Damien Riehl of vLex in this excellent interview. Couple of really good insights to think about:
✅ The importance of developing a good reputation and earning the trust of lawyers in legal tech.
✅ Is it possible to create more profit by switching from hourly billing to fixed fees by pushing down the costs of tasks by leveraging technology?
✅ 2024 is the year people are going to build cool stuff with AI.
Love all of these points and appreciate the in-depth and fun discussion.
.📆 2023 Year in Review - LexFusion
Love the format of this LexFusion year in review. Very unique and much more engaging than a text article. The slides at the bottom are great and I completely agree that the hard work is ahead of us in 2024 finding a way to build reliable apps with AI for valid use cases. We may see barriers now that won't be there in six months, so time to push forward even if there is no clear path in sight for a particular project or use case!
🌞 Time for Legal Ops to Shine
Great article by Eric Greenberg that details why now is the perfect time for legal ops professionals to earn credit for reshaping legal processes. Often being asked to do more with less resources, in-house counsel can lean on legal ops and new technology to be better, faster, or more cost-efficient. I think this is especially applicable to real estate transactions, where volume can often increase quickly and leave the same team doing more with less time and no additional resources (other than outside counsel).
⚖ Lawyers Will Advocate, Advise and Accompany Clients
This is another thought provoking piece from Jordon Furlong that digs into the question of what will lawyers do if Gen AI does ultimately automate many billable tasks. They will advocate, advise and accompany clients in their legal matters. This is usually the part of the job most lawyers enjoy and that adds the most value.
📽 OpenAI Releases Sora
OpenAI released Sora earlier this month. If you haven't checked it out, the ability to convert text to video is pretty amazing and will turn us all into movie producers.
My Work
🌄The Future of AI and Using Domain Specific Knowledge to Build a Moat
If you are an entrepreneur building in the legal tech space, a member of a law firm innovation team or part of a forward thinking corporate law department then this short talk from Andrew Ng is well worth twenty minutes of your time.
Couple of key takeaways:
⏲ In many cases the right teams can now leverage an application layer / dev tools to create an app in a couple of days vs. what might have taken the same team up to six months a year ago. This is a huge reduction in the barrier to entry.
🏰 The defensible moat for start-ups needs to combine a solid tech team with appropriate subject matter experts. Apps built with only a thin API wrapper without user input and good UI/UX won't add much value and won't be adopted in the long term.
😊 This has been a common theme for a while, but it is all about the use case and making sure you are solving a real problem that end users will pay to use. An interesting take on this is that now with the low cost of development, teams can afford to develop and ship 10 ideas even if 8 of them don't end up getting traction.
🌎 Finally and maybe most importantly, he points out that there are probably more viable business ideas / problems that GenAI can be applied to than there are subject matter experts with the applicable skill set to solve. This should be great motivation for teams to think about the most valuable problems within their organizations and think about whether this new tool / rapid development opportunity can solve it.
Back in the fall I wrote a blog post (linked in the comments) that focused on why lawyers and knowledge management folks will be key to implementing impactful AI powered solutions. I think that ties in well with this piece and hopefully this quick watch is motivation to dig in and understand how GenAI and LLMs (really a new development tool) can be used to solve your pain points!
