Engineering firms are bringing AI into more parts of their work, from analysis and design to coordination and project delivery. That brings new questions around accuracy, data security, intellectual property, contracts, and professional liability. Who remains responsible when AI contributes to an engineering decision? What should firms check before using an AI tool? This webinar looks at the practical risks of AI adoption and the safeguards firms can put in place. Learn how to approach AI with clear validation, documentation, cybersecurity, and human review.
What You'll Learn
- Where AI is changing engineering workflows and service delivery
- Risks around data security, confidentiality, and intellectual property
- How AI can affect professional responsibility and liability
- What to look for in AI-related contracts
- Ways to validate AI-generated outputs
- Practical QA/QC and documentation practices
- Where human review should remain part of the process
Meet the Speaker: Satya Marar, Research Fellow, Mercatus Center at George Mason University
Satya Marar specializes in competition, innovation and governance, with a focus on emerging technologies and critical sectors such as healthcare. He regularly writes and speaks on AI policy and antitrust issues. Satya holds a Bachelor of Arts and Bachelor of Laws with honors from Macquarie University. He also holds master’s degrees in economics and US law from George Mason University.
