From Shadow AI to Strategic Adoption: An In-House Legal Roadmap

Joseph R. Tiano, Jr, CEO | Legal Decoder

Joseph R. Tiano, Jr., Esq. is the Founder and Chief Executive Officer of Legal Decoder, Inc. After practicing law for nearly 20 years, Joe founded Legal Decoder because he saw that clients and their law firms lacked the analytic tools and data to effectively price and manage the cost of legal services delivered by outside counsel. He set out to build an intelligent, data-driven technology company that would revolutionize the way legal services from outside counsel are priced and economically evaluated. Legal Decoder’s data analytics technology is used in law firms of all sizes from AmLaw 50 law firms to boutique firms, in Fortune 500 legal departments, and in major lawsuits and Chapter 11 bankruptcy cases, including PG&E, Purdue Pharma, Toys R Us, and Rite Aid, where legal fees are scrutinized.

• Education & Credentials

Joe received his J.D. from the University of Pittsburgh School of Law in 1995 and graduated from Georgetown University in 1992 with a Bachelor of Science Degree in Business Administration.

• Recognition & Leadership

Joe has been recognized as a 2026 LawDragon Top 100 AI & Legal Tech Advisor, a 2025 ACC Value Champion, and the TVPi 2025 Pricing Expert of the Year. He is also an Adjunct Professor of Law at the Arizona State University Sandra Day O’Connor Law School, currently teaching a course on Artificial Intelligence & Legal Ethics to 2L and 3L students.

• Professional Involvement

Joe is a prolific author, having (co-)authored a forthcoming West Academic textbook on AI and legal ethics and eleven law review articles published in scholarly journals. He has written articles for numerous blogs and other online media on substantive legal issues and the legal industry and regularly presents at CLEs and other seminars and courses on topics ranging from artificial intelligence, LegalTech, and legal data analytics to legal ethics and legal malpractice.

• Experience

Joe practiced law for nearly 20 years before founding Legal Decoder. He was previously a Partner at Pillsbury Winthrop Shaw Pittman, LLP and Thelen LLP, where he grew and managed all aspects of a multi-million-dollar cross-border finance practice. His career began as a venture capital lawyer representing transformative technology companies, including Blackboard Inc. and many of the outgrowths of Blackboard (WeddingWire/The Knot, Presidium, Starfish Retention Solutions, and others).

SESSION 1 — Level Set: AI Adoption and the Shadow AI Problem | 12:00pm – 12:10pm

Review the current state of AI adoption across legal and corporate environments, examine the scope and risk profile of shadow AI usage inside organizations, and establish the baseline data that frames every strategic decision discussed throughout the program.

SESSION 2 — The Strategic AI Imperative: Owning the Strategy | 12:10pm – 12:20pm

Examine why AI strategy cannot be delegated outside the legal function, how successful adoption differs from ineffective experimentation, and the consequences for organizations that fail to take a proactive ownership role in structuring their AI initiatives.

SESSION 3 — Guiding Principles: Adoption vs. Failure | 12:20pm – 12:30pm

Work through the four core principles that distinguish meaningful AI adoption from failed pilots, including alignment, measurability, accountability, and iteration, and learn how each principle is applied to evaluate proposed initiatives before resources are committed.

SESSION 4 — Benchmarking as Your Blueprint: Billing History | 12:30pm – 12:40pm

Learn how to use billing history and the three categories of legal work as the foundation of a data-driven benchmarking analysis, identify high-value use cases supported by actual workload data, and translate benchmarking output into a defensible prioritization framework.

SESSION 5 — Measuring ROI: Five Value Dimensions | 12:40pm – 12:50pm

Apply the five value dimensions used to measure AI return on investment, map each dimension to the stakeholder audience that cares most about it, and learn how to build measurement structures that produce credible ROI figures across leadership, operations, and end-user constituencies.

SESSION 6 — Foundation Prerequisites: Five Pre-Launch Essentials | 12:50pm – 12:55pm

Identify the five foundational prerequisites that must be established before any AI initiative launches, including governance, data, infrastructure, change management, and policy, and learn how to assess whether your organization is actually ready to move from planning to execution.

SESSION 7 — The Nine-Stage Framework: Implementation Roadmap | 12:55pm – 1:00pm

Walk through the full nine-stage AI implementation framework on a month-by-month basis, covering the activities, deliverables, and decision gates at each stage, and learn how to adapt the roadmap to organizations of different sizes, maturity levels, and resource profiles.