AI Innovation Attorney - Litigation

Cozen O’Connor is building a multidisciplinary Legal AI & Practice Transformation team to rethink how legal services are delivered. Our mission is to use AI and other emerging technologies to help our lawyers deliver the best possible advice and outcomes for clients. We are not just adding AI tools to existing ways of working; we are building the expertise and capabilities needed to redesign how legal work gets done. The AI Innovation Attorney – Litigation will partner with the firm’s litigation practices to identify and implement high-value opportunities to use AI, redesign workflows, and improve how legal work is delivered. The role combines practice innovation, AI enablement, product implementation, and change management—helping lawyers use AI effectively on real matters and turning successful experiments into repeatable, scalable firm capabilities.. This is an opportunity for an experienced litigator who is actively using generative AI and wants to help shape how litigation is practiced in an AI-enabled future. The ideal candidate will bring strong AI fluency, an informed point of view about how generative AI can improve litigation, sound judgment about its limitations, and the credibility to serve as a trusted peer. Partner with litigation practices and redesign workflows Build trusted relationships with practice leaders, lawyers, and other professionals and develop a detailed understanding of how work is handled across practices and matters. Analyze litigation workflows, identify pain points, and prioritize opportunities for AI and process improvement. Advise lawyers on where AI can meaningfully improve legal work and where it cannot or should not be used. Help litigators use AI in live matters by selecting the right tools, structuring effective prompts and context, and bringing in cross-functional expertise—while preserving legal judgment, confidentiality, quality, and appropriate lawyer oversight. Develop and scale AI-enabled capabilities Lead pilots and initiatives from problem definition through design, testing, implementation, adoption, and continuous improvement. Serve as a power user and practice-facing expert for the firm’s AI platforms, building and testing prompts, workflow agents, and matter-specific solutions. Establish clear success criteria and evaluate solutions using representative matters, exemplar work product, lawyer-defined quality standards, and structured feedback. Convert successful approaches into reusable playbooks, prompts, templates, and knowledge assets that can be adapted across practices, matters, and clients. Bring together practicing lawyers and experts in legal engineering, applied AI, knowledge management, data, technology, training, project management, and vendor solutions to develop high-impact AI-enabled solutions. Enable lawyers and drive adoption Provide practical guidance through consultations, demonstrations, working sessions, office hours, and individual support. Design and deliver training and practical resources that translate AI capabilities, limitations, and governance requirements into concrete use cases and help lawyers determine when to use available tools, structure effective workflows, and evaluate outputs.. Advance client value and firm strategy Partner with lawyers and client teams to develop differentiated approaches to litigation delivery and support client-facing proposals, demonstrations, and engagements. Stay current on AI, agentic workflows, litigation technology, legal service delivery, and the vendor market, translating developments into practical recommendations. J.D. from an accredited law school and active bar membership in good standing. At least five years of substantive litigation experience. A deep understanding of litigation workflows, lawyer decision-making, quality standards, and the demands of client service. Active, hands-on experience using generative AI in legal work, with an informed point of view about where it can impact quality, efficiency, and outcomes in litigation. Ability to translate among legal, technical, and business audiences and turn ambiguous needs into practical solutions. Strong project ownership, organization, and follow-through, with the ability to manage multiple initiatives and stakeholders. A practical, curious, and low-ego mindset, including a willingness to experiment, learn from failure, challenge assumptions constructively, and remain accountable for results.