I suggested in a previous article that AI solutions will continue to impact the way in-house teams deliver legal services. Here, I suggest certain talent and staffing actions to help teams explore AI and enhance legal service delivery. Specifically, in-house teams should consider additional skill sets when creating positions and making hiring decisions. Additionally, these teams should plan for a broader range of staffing options beyond the current mix of direct hires, contractors, LPOs, and law firms. Now is the time to experiment and learn.
People, Process & Technology Interdependence
Successful solution design and adoption strategies require you to align technology with the people and processes that technology is intended to support. The three are interdependent. If you adjust one of the constituent parts, you necessarily transform the resulting dynamic.
Draw in the reins of the left-hand horse in a troika,  the right-hand horse will (hopefully) follow course to ensure a steady ride and the driver’s safety. Give free rein to the right-hand horse and you may deviate from your intended course. Regardless, the middle horse should continue to trot along as one would expect from a technology designed to move forward safely and efficiently.
AI solution implementations are no different. Alter the process upon which an AI solution is architected, you likely will automate something that no longer aligns with the business. Ignore your people or overdesign your technology, you will find your AI solution standing still in virtual stall. Steady, firm, live, and elastic hands guide seamlessly the right mix of people, process and technology to deliver results.
What skills should in-house teams possess when considering AI solutions? Who is best positioned to deconstruct the work, understand technology, and reconstitute legal service delivery?
Legal & AI Skills
In-house teams will continue depend on subject matter experts – lawyers/counsel, paralegals, case/project managers, and contract managers. These experts possess a range of critical, traditional legal skills: research, analysis and reasoning, written & oral communication, factual investigation, interviewing and questioning, advocacy, counseling & negotiation, professionalism, and, hopefully, financial literacy. Although these skills are critical to defining the substantive underpinnings of AI solutions, can legal professionals rely upon these skills to integrate seamlessly AI solutions?
AI solution implementation leverages a totally different set of skills: statistics, machine learning, search, data and computer science, engineering, architecture, information theory, process analysis, and design. Initially, these skills seem more familiar to your company’s IT team. Look deeper and you will see increased demand for these skills across the legal ecosystem.
Business schools are incorporating AI into their curriculums. MBAs are learning about the challenges and opportunities of what AI can deliver, helping these future professionals to understand how to handle and interpret data and, importantly, “to manag[e] teams of people and machines.” Law schools, in turn, offer specific courses on AI, as well as programs and courses focused on innovation and legal project management.
Law firms are appointing innovation officers, snapping up the coders, hiring directors of data analytics, investing in legal project managers, and looking for R&D leaders and AI experts. Pricing professionals continue to change the way law firm legal services are priced and procured.
In parallel, traditional in-house roles are changing. Job postings for contract managers are now joined by managers of contract analytics. Business, systems, and financial analysts support the legal function, not as part of the IT or finance departments, but as team members. These and other positions reflect the continued demand for and scope of legal operations professionals. These professionals deliver AI solutions, thoughtfully capture and analyze relevant data, develop dashboards, benchmark results, manage pricing, implement knowledge management systems, and work with LPOs to provide optimal staffing strategies.
As in-house teams continue to evolve, it is important to consider a broader range of skills not because the Bar requires technology CLE training or there is a professional obligation to stay current with technology. Rather, legal professionals need to understand these “AI skills” because they are being woven into the fabric of legal service delivery. In-house leaders should also recognize that the changing skills and interests of new generations of legal professionals will impact approaches to training, performance and talent management.
How does the business obtain legal support? Currently, the range of options includes self-help, internal legal department hires, contractors, outsourced providers, and law firms. Some of these market players offer services together. In time, the Big 4 may prove to be a more regular option, particularly as they consider the impacts AI has on risk management and service delivery. Similarly, legal start-ups will continue to evolve “to capture work that corporate legal departments have brought back into [their] organizations.”
If you recognize AI solutions as yet another way to deliver legal service, the staffing options could get complex quickly. What might that look like?
In many instances, the decision to choose one staffing option over another is based on cost. The current state-of-the-art understanding of the cost across current options is limited. For the most part, in-house teams understand internal costs. The comparative costs of all service providers are less transparent.
The costs of AI solutions are likely more obscure. Even if there are no planned near-term AI initiatives, in-house teams need to understand these new options and the costs. What questions will you ask as you seek support from LPOs, law firms, or other providers offering AI solutions? How can you gauge the cost savings of home-grown AI solutions or those offered by 3rd parties? How will you understand the comparative costs across all options? Consider available and future in-house skills you will need to answer these questions.
AI solutions capture critical data about people and processes, ultimately impacting the speed with which decisions are made. As you consider the opportunities, start with what you know. Look at the systems and processes currently in place today. Do they capture meaningful data about your operations and people to help you understand their costs? Whether solutions are driven internally or externally, AI will expose and highlight legal process inefficiencies and cost discrepancies. In-house professionals should start the journey now, capturing data to manage and triage the issues before someone asks. At a minimum, an AI journey may help you rethink roles, performance, and value over time.
This article originally appeared on LinkedIn on October 25, 2016. Interested readers are invited to (1) use a link below to share this article on LinkedIn, Facebook, Titter, etc. and/or (2) visit the article on LinkedIn to share the article or their comments.
©2016 Peter Krakaur
- Artificial Intelligence (AI) in Law Departments: Opportunities ↑
- See The Promise of Artificial Intelligence, Executive Summary, p.1 (Accenture 2016). ↑
- Troika;PD-1923; Source ↑
- See The USDF Guide to Dressage: The Official Guide of the United States Dressage Federation↑
- See Expanding the Lawyer’s Toolkit of Skills and Competencies …, 52 Santa Clara L. Rev. 795, 821-22 (2012); Report of Legal Education Committee (Florida), p.2 (G. Glover, Mar 11, 2016); Core Competencies as a Performance (Talent) Management Tool, Slide 9 (Canadian Bar Association (Oct 25, 2011) ↑
- See Preparing for the Future of Artificial Intelligence p.26 (October 2016); 7 Key Skills required for Machine Learning Jobs; What Skills Are Artificial Intelligence Students Learning? See also Redesigning Work in an Era of Cognitive Technologies (Deloitte), pp. 16-17 (suggesting other, arguably softer, skills relevant to AI development); ↑
- Top MBA Programmes Teach Artificial Intelligence ↑
- Harvard Business School Is Teaching MBAs About Artificial Intelligence, Deep Learning — Here’s Why ↑
- See e.g., Harvard AI course; University of Pittsburgh School of Law AI course; University of Washington School of Law AI course; Yale Law School AI course; University of Texas School of Law AI course; University of Edinburgh Law School; ↑
- See e.g., LegalRnD (Michigan State); Georgetown Law School; Bucerius Law School Center of Legal Profession; Vanderbuilt Law School Program on Law & Innovation; Suffolk University Institute …; LawWithoutWalls (Miami Law); Colorado Law Tech Lawyer Accelerator; University of Calgary School of Law LPM course; Vanderbuilt Law School LPM course; Georgetown University LPM course. ↑
- See e.g., Gowlings; Bryan Cave; Dentons; Nixon Peabody; Stoel Rives; ↑
- See Will AI Rush in a Skills Renaissance in Law ↑
- See e.g., Littler; Paul Hastings Latest Big Firm to Dabble in Data Analytics ↑
- See Legal Project Managers: The New Rainmakers? ↑
- See Innovators or Luddites? Legal May Be Leading the Way in AI ↑
- See What We Know and Need to Know About Legal Procurement; LMA P3 Conference (Pricing, Practice Innovation, and Projec Management)); Buying Legal Council. ↑
- See CLOC in the news; CLOC; ACC Legal Operations. ↑
- See Introduction to Legal Analytics, Part 3: Machine Learning↑
- See Legal operations role overview. ↑
- See Fla. Rule 610-.3(b). ↑
- See Model Rule 1.1 Competence, Comment 8; Cal. Bar Eth. Op 210-179 ↑
- See The Promise of Artificial Intelligence (Accenture 2016) ↑
- See Akerman Data Law Center (Akerman LLP collaboration with Thomson Reuters); ComplianceHR (Littler collaboration with Neota Logic). ↑
- See The re-emergence of the Big 4 in Law; The Big 4 Are Putting Down Roots in the Legal Sector; Attack of the bean-counters; On the Future of Law Departments; Will All Lawyers Work for the Big 4 by 2026?; ↑
- See Why Artificial Intelligence is a Game Changer for Risk Management; “AI will become part of PwC’s DNA”; EY brings in BLP’s AI specialist Whalley to Spearhead Legal Risk Practice; The Big Law Firm of the Future – AI, Digital Robots and Blockchain. ↑
- What We Know and Need to Know About Legal Startups, 67 S.C. L. Rev. 389, 393 (2016). ↑
- Interestingly, AI solutions and LPOs are delivering more insights to some of the current costs. See previous article, legal spend analysis section. ↑
- See Automation Will Make Us Rethink What a “Job” Really Is; ↑
©2016 Peter Krakaur