Unlocking the Potential of Artificial Intelligence in English Law

1. Unlocking the Potential of Artificial Intelligence in English Law Professor Mari Sako Saïd Business School, University of Oxford Glenlegal Conference, 4 March 2019 2019

2. Research Programme 2019-2020 • Funded by the Industrial Strategy Challenge Fund's (ISCF) Next Generation Services Research Programme and UK Research and Innovation (UKRI) • Researchers from Law, Economics, Computer Science, Education, and the Business School • Five work packages • WP1: New business models in legal services (we focus on corporate legal services (B2B)) • WP2: Mapping digital justice • WP3: Frontiers of AI in legal reasoning • WP4: Coordinating skill investment and technology transfer • WP5: Legal and technology education Further details: www.law.ox.ac.uk/research-and-subject-groups/unlocking-potential-artificial-intelligence-english-law/ (c) Mari Sako, University of Oxford 2019

3. AI in law: what is at stake? International competitiveness of UK jurisdiction Growth in lawyers in England & Wales Source: Law Society and approved regulators (c) Mari Sako, University of Oxford 2019

4. Numerous AI applications in law… Source: The Law Society (2019) Legaltech Adoption Research (c) Mari Sako, University of Oxford 2019

5. Question 1: Benefits of AI • What are the top three benefits sought from adopting AI in your firm? • Enhance the quality of service delivered to your clients • Retain clients against competition from other providers • Increase internal efficiency by optimizing business processes • Provide new services through data analysis and insight • Provide alternative career paths for associates • Improve recruitment and retention of employees • Other (SPECIFY) • Don’t know (c) Mari Sako, University of Oxford 2019

6. Question 2: Barriers to adopting AI • What are the top three barriers to adopting AI within your organization? • Lack of client demand • Client concern about giving access to, or storage of, data • Lack of buy-in from key decision-makers inside the firm • Nervousness inside the firm about negative impact on skills and roles • Insufficient employee skills to use AI effectively • Difficult to decide which AI platform to commit to • High costs of initial proof of concepts, licensing and platform fees • Costs of training/customising AI products for application by the firm • Absence of financial metrics to justify investment in AI • AI technologies for legal applications are not yet robust • Other (SPECIFY) • Don’t know (c) Mari Sako, University of Oxford 2019

7. How is AI affecting law firms? We focus initially on automation using supervised machine learning (ML) (c) Mari Sako, University of Oxford 2019

8. Two key questions in our research • How is AI technology impacting professional knowledge and legal careers? • How does AI adoption affect law firms’ governance choices as they shift their business models? (c) Mari Sako, University of Oxford 2019

9. Question 3: Talent • How many non-fee earning professionals does your firm employ relative to fee-earning lawyers? • Fee-earning lawyers > non-fee earning professionals • Fee-earning lawyers = non-fee earning professionals • Fee-earning lawyers < non-fee earning professionals • Don’t know NOTE: Professionals who are not fee earning include business development managers, project managers, knowledge management professionals, data scientists and technology experts. • What proportion of your client-facing fee earning professionals are non-lawyers? • None • Less than 1% • 1% - 5% • 6% - 20% • 21% - 50% • More than 50% (c) Mari Sako, University of Oxford 2019

10. Two key questions in our research • How is AI technology impacting professional knowledge and legal careers? • How does AI adoption affect law firms’ governance choices as they shift their business models? • Business model: the way a firm creates and captures value • Governance • Intra-firm governance (partnerships and alternatives) • Inter-firm contractual governance (c) Mari Sako, University of Oxford 2019

11. Question 4: Data and technology • From where do AI models that your firm train come from? Tick all that apply. • Own model • Vendor model • Client model • Other • On which data does your firm train models? Tick all that apply. • Own data • Client data • Data from providers (e.g. LexisNexis, PLC, Westlaw) • Public data (e.g. SEC filings, court decisions) • How is AI investment funded at your firm? Tick all that apply. • Retained earnings • Client disbursement • Loans • Equity stake in technology and data providers (e.g. legal tech startups) (c) Mari Sako, University of Oxford 2019

12. Question 5: Build or Buy? • What is your firm’s preferred strategy for legal technology, including AI? Tick all that apply. • Create an in-house legal technology team in the firm • Create a separate legal technology subsidiary • Take an equity stake in tech firms, including via incubator • Buy from vendor • Collaborate with a vendor • Collaborate with a client • Collaborate with other party (e.g. academic institution) • Not yet decided • Don’t know (c) Mari Sako, University of Oxford 2019

13. Our (interim) answers • How is AI technology impacting professional knowledge and legal careers? • Value migration from humans to computers  Sell products as well as services • Value migration from lawyers to non-lawyers  variety of career progression routes; hierarchical control, not peer control, inside law firms • How does AI adoption affect law firms’ governance choices as they shift their business models ? • External funders  preference for ownership form with access to external investors • Technology and data providers  contractual governance is becoming more important (c) Mari Sako, University of Oxford 2019

14. Value migration in the legal ecosystem Global market size Global legal: $850 billion (2017) ALSP: $10.7 billion* Investors Data vendors Professional associations • Alternative legal service providers (ALSPs) include: • LPO providers • Big Four • Managed legal service providers • Value migration drivers • Insourcing by general counsel • Demand for greater efficiency and transparency • Shift from input-based to output-based pricing * Alternative Legal Service Providers 2019 We will study value migration within organizations (from lawyers to non-lawyers), and between organizations. (c) Mari Sako, University of Oxford 2019

15. Business model and governance options for law firms Which (mix of) models will emerge as dominant in the market? (c) Mari Sako, University of Oxford 2019

16. Thank you for your attention!Mari.sako@sbs.ox.ac.uk