MCP, Agentic AI Risk, and the Governance Decisions Leaders Must Make Now Webinar
Speakers

Sean D. Goodwin is a Principal in the Cybersecurity (DenSecure) group at Wolf & Company, P.C., where he leads both offensive and defensive security engagements for clients across highly regulated and technology‑driven industries.
Sean leads Wolf’s cybersecurity practice across offensive security, including security reviews, penetration testing, social engineering, threat emulation, and red‑team engagements that stress‑test an organization’s defenses against real‑world threat actors. On the defensive side, he oversees virtual CISO (vCISO) consulting programs, helps design and mature security programs, and leads digital forensic investigations that support incident response and recovery. He also serves as Wolf’s Lead QSA, responsible for overseeing PCI DSS assessments and mentoring teams that support complex compliance environments.
With over a decade of consulting experience, Sean has worked extensively with financial services, healthcare, education, software, and other data‑intensive sectors, helping organizations improve their security posture and resilience against modern cyber threats. His work spans the intersection of compliance and security, frequently advising leaders on PCI DSS scope, the difference between “checking the box” and true risk reduction, and how to build trust‑driven, business‑aligned security programs. Sean regularly speaks and shares insights on topics such as social engineering psychology, AI‑driven threats, cyber deception, tabletop exercises, and why cybersecurity has become a core business survival issue rather than a pure IT function.
Beyond his client work, Sean contributes to the broader cybersecurity community as a board member of the Eastern Massachusetts (ISC)² chapter and a mentor with the Mass Cyber Center. He also serves as an Auxiliary Member in the USCG Auxiliary Cyberspace Flotilla, supporting Coast Guard cyberspace defense and operations through the AUXCYBER program. Sean is a frequent guest on podcasts, webinars, and industry forums, where he translates complex security concepts into practical guidance for executives, boards, and technical leaders.
Sean holds a Bachelor of Science in Information Systems Audit and Control from Bentley University and a Master of Science in Information Security Engineering from the SANS Technology Institute. He has earned an extensive portfolio of industry certifications, including GSE (GSE #271), CISSP, CCSP, CISA, QSA, PCIP, and multiple GIAC credentials such as GSEC, GCIH, GCIA, GCWN, GCCC, GCUX, GCPM, and GDAT, reflecting deep technical and governance expertise across the cybersecurity landscape.

Philip H. Wess is a nationally recognized speaker and technology executive specializing in artificial intelligence, data strategy, analytics, and digital transformation. With more than 20 years of experience building enterprise software, data platforms, and advanced analytics solutions, he helps organizations navigate the intersection of AI innovation, governance, security, and business transformation. Philip works with executive and technology leaders to develop the modern data foundations required to support AI at scale, while addressing emerging challenges around agent governance, cybersecurity, risk management, and regulatory oversight. His experience spans data architecture, software engineering, analytics modernization, AI implementation, and organizational change management.
A frequent speaker to financial institutions and industry groups across the country, Philip focuses on helping organizations move beyond AI experimentation and build secure, governed, and scalable AI capabilities that deliver measurable business value.
SUMMARY
In this Revenue Room™ CXO member exclusive webinar, Philip H. Wess and Sean D. Goodman covered the business case and security risks of MCP-connected AI agents: Philip framed the revenue upside (personalization, rev ops automation), while Sean flagged authentication, auditability, and authorization as the top risks, citing that 97% of AI-related breaches stem from poor authentication and that attackers exfiltrate data in ~90 minutes versus ~187 days to detect it. Q&A focused on accountability, board communication, and penetration testing frequency.
CONTENT & TRANSCRIPT
