Matt Todd is a co-chair of the Licensing & Transactions practice and Restrictive Covenants & Trade Secrets Litigation practice and is a member of Polsinelli’s Blockchain and Web3 Steering Committee. He has over two decades of experience structuring and negotiating domestic and international complex intellectual property and technology-related transactions. In addition to his transactional experience, Matt has demonstrated knowledge in assisting clients with deploying and commercializing artificial intelligence and machine learning, blockchain and cybersecurity technologies. He has advised clients in a variety of industries including energy, semiconductor, automotive, defense, software and financial services. Matt is also one of Polsinelli’s leading authorities on open-source software use, licensing, deployment and integration.

In addition to his legal experience, Matt has more than 10 years of experience in network administration and operations.

Education

  • University of Oxford (M.B.A., 2010)
    • St. Mary's University School of Law (J.D., 1998)
      • University of Texas at Austin (B.B.A., 1995)
        • Accounting

      Bar Admission

      • District of Columbia, 2003
      • Virginia, 2001
      • Texas, 1998

      Professional Affiliations

      • Houston Angel Network
      • University of Oxford, Said Business School Regional Ambassador
      • University of Houston Law Center, Adjunct Professor, Privacy and Data Security Law
      Publications
      All Publications
      Court Rules on How Client Use of AI for Legal Strategy is Not Protected
      Key Takeaways A federal court ruled that a defendant’s independent use of a publicly available AI platform was not protected by attorney-client privilege or the work product doctrine. The decision highlights how confidentiality and counsel involvement remain central to privilege analysis, even as AI tools evolve. Organizations should take a proactive approach to AI governance and risk mitigation, especially with the current technological shift from generative AI to Agentic AI. A new federal court ruling highlights why defendants should think twice before independently consulting AI tools. Last week, a federal judge in the Southern District of New York issued a 12-page decision in USA vs. Heppner, a case involving allegations of fraud in which the defendant independently used generative AI to prepare elements of
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      Utah Approves AI for Prescription Refill Process as States Test AI Governance Models
      Key Takeaways Utah’s approval of a new Regulatory Mitigation Agreement (RMA) to pilot AI in the prescription refill process adds to a growing wave of state activity, as the speed and scale of AI adoption has prompted states to consider hundreds of AI laws in a variety of contexts and industries. Even as industry standards rapidly evolve, an expanding patchwork is emerging due to fears that the AI revolution is outpacing guardrails for consumers, developers and deployers. Utah and Texas now offer structured pilot frameworks that may satisfy the AI Litigation Task Force’s call for “minimally burdensome” oversight, offering potential models for AI developers seeking to test high-risk use cases within a structured regulatory environment. This month, a leading global provider of professional services
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