186 | 📝🤔 Docusign invents the Intelligent Agreement

In today’s Brainyacts:

1. Benchmarking AI Strategies

2. Teach Anything to Anybody

3. Docusign invents the Intelligent Agreement and other AI model news

4. UK antitrust concerns in AI market and other AI-related content

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To read previous editions, click here.

Lead Memo

🧐📐 Benchmarking Yours and Everybody Else's AI Strategy

If want to merely keep pace with adapting to Generative AI in the legal market, stop reading. If you want to prove you are a true leader, this one is for you.

The distinction between mere technological activity and a strategic, integrative approach to AI can mean the difference between leading the market and merely playing. For law firms aiming to set themselves apart, understanding and implementing a robust AI strategy is no longer optional but a critical imperative.

This essay delineates six fundamental categories to form a cohesive and comprehensive AI strategy. These are not just activities but pillars that support a firm's claim to innovation and leadership in AI, providing measurable inputs and outputs essential for a credible strategy.

1. Talent Acquisition and Development

Definition: Talent underpins AI initiatives. Without the right people—those who understand both the technology and its application in legal contexts—progress is stymied.

Warning: Hire makers, not managers. You need to get the right people who will work in long blocks of time (deep work) to develop an ecosystem (data, applications, code) that will fit your firm. You do not need innovation managers creating meetings and interruptions for the makers. See Maker's Schedule, Manager's Schedule

Strategy: Law firms should invest in both recruiting specialists with AI expertise and upskilling their existing workforce. This could mean hiring data scientists with experience in natural language processing or providing current legal and business staff with targeted pragmatic training in GenAI applications relevant to their practice areas and workflows. Technical training is not important. Practical training is. People need fingers on keyboards with this tech. Measurable outcomes include the number of staff trained annually and the successful integration of AI specialists into legal project teams.

2. Education and Continuous Learning

Definition: Continuous learning about AI’s capabilities and limitations ensures that a law firm can adapt and innovate responsibly.

Warning: You cannot train once and be done. AI is moving too rapidly. Sure, you can get foundations set through initial training but for deep skills to take root, focused and experiential learning must be created. See How continuous learning keeps leaders relevant in the age of AI

Strategy: Develop ongoing education programs that are accessible to all levels of the firm. These programs should cover both the technical aspects of AI and its ethical implications, preparing staff to use AI tools effectively and conscientiously. Key metrics for success might include participation rates in these programs and feedback scores that assess their impact on employees’ proficiency with AI.

3. Innovation and Development

Definition: True innovation in AI requires creating novel tools or methodologies that enhance legal services and operations.

 Warning: Most law firms are not innovative in any sense. That is not cynicism, it is fact. Innovation traditionally relies on a slew of activities such as research (as in published papers or released studies), development of IP (from the research or experiments that could lead to patents), ventures within the ecosystem (direct capital investments or resource investments), commercial partnerships (not signing a vendor contract and calling it a partnership e.g., “partnering with Microsoft to deploy Copilot” – no you signed a license agreement), and developing a leadership voice in the ecosystem (for AI that could be policy, or open-source, or Responsible AI/ethics.

Strategy: Firms should engage in research and development projects that aim to create proprietary AI solutions or improve upon existing ones. This involves more than just adopting external technologies like Copilot; it includes developing in-house capabilities that lead to patent filings or published research papers. Metrics can include the number of patents filed, research papers published, or proprietary AI solutions developed.

4. Leadership and Visionary Thinking

Definition: Effective AI strategy must be driven and supported by the firm’s leadership. Without commitment at the highest levels, AI initiatives are likely to be disjointed or underprioritized.

Warning: Where is a joint statement from a firm’s executive committee, practice groups heads, or just the managing partner? Having the Chief Innovation Officer or CIO talk on this is certainly fine and good btu they should not be the only senior voice. While this is an example taken from an Innovation Officer, the transparency and detail provided demonstrates organizational commitment to the highest level – See David Cunningham’s LinkedIn posts about Reed Smith - https://www.linkedin.com/feed/update/urn:li:activity:7176692106122461186/

Strategy: Leaders should articulate a clear vision for AI at their firm, incorporated into the overall business strategy. This vision should be communicated consistently and integrated into the operational and strategic decisions of the firm. Success can be measured by the frequency and clarity of internal communications about AI, as well as external engagements or presentations by senior leaders on AI topics.

5. Transparency and Ethics

Definition: As AI systems become more integral to legal operations, how these systems are developed and used must be transparent, with a clear ethical framework.

Warning: Do not create an AI ethics committee. Hand wringing and arms-length conjecture are distractions. Get pragmatic by understanding the core data involved. Explain what ethical use looks like in the real world. Avoid fearmongering and alleviate misconceptions. In other words, policy must come from the streets, not the ivory tower.

Strategy: Implement policies that ensure AI tools are used in a way that is ethically defensible and transparent. This could include conducting regular audits of AI tools, publishing ethical guidelines for AI use, and engaging in public discourse about the firm’s AI practices. Evaluative measures could encompass the establishment of an ethics board, the number of ethical reviews conducted, and the publication of transparency reports.

6. Engagement and External Collaborations

Definition: Building relationships with other AI practitioners and firms can enhance a law firm’s capabilities and innovation potential.

 Warning: Don’t just partner with tech vendors. They do not serve your interests alone as they are trying to grab market share and will work with any of your competitors. Find green fields where you can foster a unique advantage. It is surprising to me how few firms use law schools as a laboratory. This is either because CIOs don’t have law degrees and so don’t even think of it, or law schools are simply overlooked. Reach out to me – I know how to partner with firms and in-house teams in meaningful ways. I have the proof and experience. Also, I am joining the faculty of Indiana University to teach pragmatic skills to law students) as well as build “business of law” curriculum.

Strategy: Actively seek partnerships with AI technology providers, academic institutions, and participate in industry consortia. Such collaborations can help law firms stay at the cutting edge of AI technology and practice. This can be measured by the number of active partnerships, joint ventures, or collaborative projects undertaken each year.

Spotlight

From the Archives:

👩‍🏫 🧐 Teach Anything to Anybody

This is from Brainyacts Edition #22. It is a prompt conversation that will help you teach anything to anyone using Bloom’s Taxonomy and GenAI.

PROMPTS:

>> Please explain how to use Bloom's taxonomy in developing me to create educational content. <<

>> What are the components of the taxonomy? <<

>> Great, thank you. I am going to be giving a presentation to [describe your audience - be specific]. I will be explaining [what is the topic and what nuances are you focused on?] Can you provide specific examples for each of Bloom's levels? <<

>> In a presentation format, how might I be able to assess if these learning objectives have been achieved for each of the levels? <<

Using prior content:

>> A few weeks ago I wrote some content about [what is the content about and who is the audience]. I want to use that as the topic for an upcoming lunch-n-learn. Using Level 2 of Bloom's, can you review the following content and create 1) clear learning objectives and 2) a few assessments? Here is the content: [paste your content] <<

>> Elaborate on Number 2 "Multiple choice questions" - can you draft 10 multiple choice questions that are appropriate for this material? <<

>> Excellent, we are almost done. Now I would like you to draft a thorough and comprehensive annotated outline for this 45 minutes session on this topic. I would like the outline to include the main topics, talking points for each topic, and an example script that I can use to deliver the whole program. <<

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AI Model Notables

► Docusign, launches the Intelligent Agreement Management (IAM) platform - Intelligent agreements incorporate AI and advanced analytics to help users spot contract risks and speed up contract processes

► Apple plans to overhaul entire Mac line with AI-focused m4 chips

► One of the first AI devices comes to market: Humane AI Pin review: not even close

► Google brings AI-powered editing tools, like Magic Editor, to all Google Photos users for free

► Meta is on the brink of releasing AI models it claims to have "human-level cognition" - hinting at new models capable of more than simple conversations

News You Can Use:

➭ UK’s antitrust enforcer sounds the alarm over Big Tech’s grip on GenAI

➭ Texas is replacing thousands of human exam graders with AI

➭ New US federal bill could require disclosure of songs used in AI training

➭ Consumers would be notified of AI-generated content under Pennsylvania bill

➭ US Congressman Schiff introduces groundbreaking bill to create AI transparency between creators and companies

➭ Getty Images CEO calls for industry standards around AI

➭ Google releases new AI podcat series with 6 new conversations with global leaders on AI and society

Who is the author, Josh Kubicki?

Some of you know me. Others do not. Here is a short intro. I am a lawyer, entrepreneur, and teacher. I have transformed legal practices and built multi-million dollar businesses. Not a theorist, I am an applied researcher and former Chief Strategy Officer, recognized by Fast Company and Bloomberg Law for my unique work. Through this newsletter, I offer you pragmatic insights into leveraging AI to inform and improve your daily life in legal services.