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An example of how contract playbooks designed by lawyer experts can be applied to commercial contracts using GenAI.

As the revolution in large language models (LLMs) makes its way into new startups and applications, would-be customers ask: How is my private data protected? Can commercial AI providers use my input data to train their models? The emergence of retrieval augmented generation (RAG), which can inject private data into prompts, has made this an urgent issue, particularly for companies building applications on top of LLMs since they often use those services on behalf of their customers. 

The big worry is that intellectual property, trade secrets, other sensitive information, or private information is unknowingly leaked to the public via an LLM’s future output for a different customer. Here is a sample nightmare scenario: Continue Reading Fine print face-off: which top large language models provide the best data protection terms? (352)

Four key elements: caps on total liability, exceptions to cap, limitations on type of damages, and exceptions to limits.

In recent posts, I have postulated that commercial contracting is on the following path of evolution:

  1. Reliable data as to what is market for key contracting terms will become readily available as utility models, powered by large data sets and AI, become prevalent. See Post 225 (“Can contract analysis operate like a utility?”).
  2. Companies will look to remove friction from their businesses by aligning their contract terms (and negotiating practices) with market, with some companies offering better-than-market terms in an effort to achieve competitive advantage. See Post 211 (“Competition based on better commercial contract terms”).
  3. Moving to market terms will lead to contract standardization, less contract complexity, and significant returns to the companies that adopt this approach, benefitting the economy as a whole.  See Post 228 (“The cost of contract complexity”); Post 236 (“Case study: impact of AI and Big Data on low-risk contract negotiations”); Post 292 (“The emergence of data-driven contracting: notes from the field”).

The critical foundation for this evolution is that all parties to a negotiation have reasonable access to information regarding what constitutes market.  (For a discussion of the problems associated with information asymmetry, see the works of Joseph Stiglitz.)
Continue Reading What is “market” for limitation of vendor liability? A look at the data (322)

Several in-house innovators are converging on a set of best practices.

In Competition based on better commercial contract terms (211), I reviewed the current norms surrounding commercial contracting and postulated that the growing transparency regarding what is market for a particular term would cause the market for contracts to evolve from its current souk-like state to something that more closely resembles a modern e-commerce marketplace.  Since that post came out in December 2020, numerous companies have been employing AI tools such as TermScout. and crowd-sourced data such as Bonterms, to make their contracting practices more data-driven.
Continue Reading The emergence of data-driven contracting: notes from the field (292)

“Be engaged, interested in what others have to say. It’s more important to listen than to speak.”

I had the opportunity to discuss legal outsourcing with Colin Levy, who embodies the skills and mindset of the modern T-shaped legal professional.

Colin and I work on opposite ends of the spectrum: he’s an attorney who’s experienced first-hand how outsourcing to an ALSP can impact his career and place of employment. In contrast, I have expertise in helping law firms find and work with ALSPs. When law firms or legal departments choose to outsource to ALSPs, often, no jobs are lost. However, sometimes an ALSP can replace certain functions. I thought it would be interesting to hear one attorney’s perspective on whether ALSPs are a threat to attorney job security in the legal industry.

Below are notes from our discussion.
Continue Reading Legal careers in the age of outsourcing: A conversation with Colin Levy (288)

Putting complex and often intimidating topics into context.

Chapter 8, Technology

No discussion on contracting process improvements is complete without focusing on technology. Scarcely a day goes by without an article, blog, or webinar on legal technology and, more specifically, about artificial intelligence (AI). There are many conferences and webinars about contract management systems—on selecting them, on what to use them for, how to derive greatest benefit, etc. Usually, those educational programs are provided or delivered by the contract management systems providers.

Technology is always at the core of any discussion about innovation, for example, but I maintain it should not be. Before any conversation about technology takes place, there should be an assessment of the current state of the people and processes involved in contracting, which is why this chapter follows my previous chapters on People and Process. Only after a thorough review takes place, and there is agreement within the organization that the right people are doing the right steps in the best order, should a discussion about technology begin.
Continue Reading CLM Simplified Part IV: Technology, Metrics & Data, and Outsourcing (272)

Source:  Gravity Stack [Click on to enlarge]

Sophisticated investors are betting on contract tech. It’s about business, not the intricacies or importance of law.

Today’s post (256) and last week’s (255) are a two-part series on the burgeoning legal tech sector.

Whereas Post 255 focused on the explosion in the legal technology market over the past year—five new #Legaltech Unicorns, three companies go public—this post looks contract tech, which is arguably legal tech’s hottest subsector.
Continue Reading Because Everyone Else Cares: Why legal should be paying attention to contracts (256)