Strategy & Transformation
Translate organizational priorities into AI adoption roadmaps, evaluation criteria, delivery decisions, and cross-functional alignment.
Enterprise AI Strategy & Transformation
AI Governance
& Assurance
I’m Jess J. Montgomery—an enterprise AI strategy and governance executive connecting responsible AI, decision accountability, and technology transformation.
01Explore the work
Explore My Work
Leadership, writing, and research for your audience.
AI Adoption With Accountability
AI strategy, technology transformation, and governance that reach the teams doing the work.
Strategy Into Delivery
AI adoption roadmaps, platform modernization, and cross-functional alignment.
Explore AreaAI Is the New Cloud
What enterprise AI can learn from the last major technology transformation.
Read PublicationGovernance Where Decisions Matter
Practical conversations about adoption, ownership, and assurance.
Explore Area02Executive AI Leadership
Lead AI Transformation,
Own the Decisions
My leadership focus connects enterprise AI strategy with the platforms, governance, and people needed to deliver it responsibly.
Discuss a Leadership OpportunityGovernance & Assurance
Make ownership and intervention authority explicit. Connect responsible-AI expectations to implementation, monitoring, escalation, and evidence.
Cloud & Platforms
Modernize secure cloud and data environments while managing dependencies, access boundaries, reliability, and organizational change.
Leadership Grounded in Service
I served as a U.S. Army Veterinary Corps non-commissioned officer from 2002 to 2012, including a combat tour in Iraq in 2010–2011. I led teams, training, readiness, quality standards, and veterinary mission execution under demanding conditions.
That experience shaped how I lead today: clear accountability, sound judgment under pressure, and a commitment to the people responsible for the mission.
03Veterinary & animal-health AI
Technology Leadership With a Commitment to Care
My veterinary background, animal-services executive experience, and technology leadership inform a deliberate career focus on AI in animal health.
I’m interested in director-level roles shaping AI strategy, responsible adoption, and governance in veterinary technology companies and animal-health organizations.
The work I want to lead connects product and platform decisions with practice workflows, appropriate data use, professional oversight, and value for the teams delivering care.
Explore Veterinary AI Speaking TopicsAcross the Full Technology Lifecycle
Clinical and practice workflows · Business operations · Products and platforms · Data and vendors · Ongoing monitoring and intervention
04Research & Standards
What Changed After the Governance Decision?
My independent research examines the authority and evidence needed to establish that an intervention achieved its intended effect.
Independent Research
Decision Authority, Intervention, and Assurance Evidence
Who can challenge or withdraw AI influence? Does that decision reach dependent workflows? What proves the intended outcome—and that it remains in effect?
Read the Research PreprintStandards Participation
Practitioner Contributions
Co-developed and submitted NIST AI RMF proposals on accountable ownership, decision authority, and enforceability of governance interventions. Contributed input to NIST AI Standards Zero Draft activities and participate in the IEEE P3591 working group.
Research and Paper Collaboration
I’m open to collaborating on research and coauthored papers in AI governance, enterprise AI, veterinary technology, and animal welfare.
Discuss a Research Collaboration
Doctoral Research · In Development
AI-Assisted Decisions for Companion Birds
My proposed research examines decision support in shelters, sanctuaries, and veterinary settings, with attention to professional judgment and changing evidence.
Decision Trace explores recommendation validity and downstream actions through a fictionalized/composite macaw case inspired by Bella. Research and case development; no clinical deployment or validation claimed.
05Speaking
AI Governance Across the Business
Discuss a Speaking EngagementPractical talks for enterprise leaders, business and technical teams, veterinary organizations, and animal-welfare audiences.
OCT062026
IEEE Lone Star · San Antonio Scheduled
Beyond the Framework: Operationalizing AI Governance Where Failure Matters
OCT12–142026
AI Gov World · Las Vegas Conference dates
The AI Governance Readiness Gap: Why Risk Registers Aren’t Enough
OCT272026
ISACA · San Antonio Confirmed
AI Risk Registers Won’t Save You: Operationalizing AI Governance in Security Programs
Enterprise topics
From AI Ambition to Accountable Action
AI strategy, adoption, and governance across the business environment. Influencing business and technical partners. Integrating governance into products, platforms, and workflows. Appropriate governance responses to privacy and sensitive-data risk. Decision rights, executive accountability, lifecycle oversight, vendor evaluation, monitoring, escalation, and organizational change.
Veterinary & animal-health topics
Governance Across Veterinary Technology
I speak on governance across veterinary technology: AI in care, documentation, client communication, operations, and products; data and vendor oversight; validation, performance and risk monitoring; escalation; and animal welfare. I welcome invitations from veterinary and animal-health organizations.
06Selected writing
Ideas for Leaders
Questions for Research
Enterprise and animal-AI commentary, coauthored work, research preprints, and upcoming writing.
AI Is the New Cloud—and We’re Repeating the Same Mistakes
Lessons from cloud transformation for enterprise AI adoption.
June 12, 2026Read Publication
Your AI Risk Register Is Not an Incident Response Plan
Connecting documented AI risks to authority and response.
July 13, 2026Read Publication
Compassion Is Not a Control: What Veterinary Practices Reveal About AI Governance
Practical oversight for AI adoption in veterinary practice.
August 18, 2026Read Publication
What the 3M ChatGPT Case Reveals About AI Governance
AI interactions as evidence around consequential decisions.
September 14, 2026Read Publication
Who Owns AI When It Breaks? The Convergence of AI Governance and Cybersecurity Accountability
With Joshua Copeland. Decision ownership and authority to intervene in AI-enabled work.
2026Read Publication
From Governance Decision to Operational State: An Assurance-Case Perspective on AI Governance Interventions
Conceptual research on evidence that a governance intervention achieved its intended effect.
2026Read Preprint
When Prediction Becomes Disposition: Governing AI-Assisted Decision Making in Animal Shelters
How predictive AI can shape resource allocation, human authority, and the opportunities available to shelter animals.
September 2026Read Preprint
What a Cockatoo Can Teach Us About the Evidence AI Wasn’t Built to Hear
What animal intelligence reveals about the evidence we recognize—and the evidence AI systems may miss.
Planned for October 15, 2026Forthcoming
07About Jess
Executive Leadership for Enterprise AI
I lead AI integration, enterprise technology transformation, and governance that prepares AI for responsible deployment. Across 24 years of leadership, I’ve combined executive accountability with the technical depth to align business priorities, secure platforms, and cross-functional teams.
AI Integration and Deployment Readiness
I lead AI integration and secure-cloud execution across engineering, architecture, cybersecurity, operations, vendors, and government leadership. I coordinate decisions, risk, and readiness across approximately 27 DevSecOps contractors and 20+ government and active-duty stakeholders.
I define governance and deployment-readiness controls for AI-enabled CI/CD integration in AWS GovCloud: approved data use, access and environment boundaries, validation, auditability, traceability, human oversight, monitoring, escalation, and production-readiness evidence.
Governance, Risk, and Vendor Oversight
I translate RMF, continuous monitoring, system authorization, access-control requirements, Zero Trust expectations, environment segregation, and change and release governance into implementation criteria and evidence. I evaluate AI, cloud, and cybersecurity vendors for data handling, access controls, FedRAMP posture, workflow integration, corrective-action visibility, and third-party operational control boundaries—then turn the findings into risk and implementation decisions.
Using incident patterns and workflow analysis, I reduced recurring incident noise by approximately 30%, improving signal quality, prioritization, and consistency of response decisions.
Enterprise Transformation and Executive Decisions
I led cross-functional cloud and data modernization, aligning platform strategy, cybersecurity, compliance, operational risk, customer priorities, vendors, resources, and executive decision-making. I directed a Splunk-to-AWS modernization using Cribl supporting approximately 12 TB/day of security and observability data movement, with controlled data flows, access, traceability, resilience, acceptance criteria, and operational readiness.
I built governance cadences, executive dashboards, risk narratives, dependency controls, escalation, and corrective-action routines to inform priorities, staffing, readiness, investment, and remediation. I partnered across business and technical teams to manage delivery and change trade-offs while preserving auditability, continuity, security, and regulatory expectations.
Responsibility for People and Operations
As an Executive Director, I led a 62-person municipal animal-services agency with responsibility for strategy, workforce, budgets, veterinary operations, policy, and crisis response. As a Vice President in Qatar, I led a 30+ person international animal-welfare operation representing 12 nationalities.
I bring that executive accountability to enterprise AI and animal-health technology: align the organization, make decisions, and own the consequences.
U.S. Army Veterinary Corps · Non-Commissioned Officer · Combat Veteran · Former Registered Veterinary Technician · Former Certified Animal Welfare Administrator
Education
- M.S. in Artificial Intelligence & Machine Learning
- Colorado State University Global
- Master of Business Administration
- Texas A&M University–Corpus Christi
- Bachelor of Applied Science in Veterinary Technology
- St. Petersburg College
- Associate of Applied Science
- Cedar Valley College
- Doctor of Computer Science in AI & Big Data Analytics In Progress
- Colorado Technical University
People, Technology, Animals - Let’s Connect
Let’s talk about executive AI leadership, speaking, research collaborations, and coauthored papers across enterprise and animal health.