AI Governance & Risk Management
Tony Santiago
Managing Director | AI Practice Leader | ex-AWS
CapNexus
"CTOs want to build the AI use case. CIOs want to know how to stop it from blowing up the business."
Who Is Tony Santiago
The Governance-First Voice Behind Enterprise AI Adoption
Tony Santiago is the Managing Director and Global Head of AI and AWS Practice at CapNexus, and spent more than six years at Amazon Web Services leading global partner strategy for generative AI and machine learning across the world's largest System Integrators. As Worldwide Senior Partner Solutions Architect and Global Lead for Generative AI and ML within AWS's GSI and GSP organization, he worked directly with the consulting firms responsible for deploying AI at the largest enterprises on the planet, giving him a rare vantage point on what actually works when AI moves from a pilot to production.
Tony is a co-author of the AWS Cloud Adoption Framework for Artificial Intelligence, Machine Learning, and Generative AI, the reference framework hundreds of enterprises and consulting partners use to plan and govern their AI adoption. He also co-authored the AWS Cloud Adoption Framework Platform Perspective. He is now developing his own next iteration of that framework as original thought leadership, built specifically for the governance and risk questions the first version did not fully address.
At CapNexus, Tony leads a consultancy built around a specific, underserved gap: upper mid-market and lower-enterprise companies that want the rigor and operating discipline of a Global Systems Integrator, but are too small for the big GSIs to prioritize. His pitch is built around what he calls the CIO lens versus the CTO lens. CTOs want to build the impressive AI use case, while CIOs are the ones asking how to stop data leakage and manage risk before it puts the business at risk. That governance-first framing, earned from years inside AWS's largest AI deployments, is his differentiator.
Experience
Companies Tony Has Worked With
Why Tony Is a Great Guest
The Right Fit for Your Audience
Tony speaks to CIOs, CTOs, enterprise IT leaders, and mid-market business leaders trying to make sense of AI governance and risk. His conversations work because he is not selling the flashy "look what we built" angle. He brings the discipline of a framework co-author and the perspective of someone who has sat inside AWS's largest AI deployments and seen exactly where governance breaks down.
- Co-authored the AWS Cloud Adoption Framework for AI, ML, and Generative AI, the industry reference most enterprises use to plan AI adoption
- Spent 6+ years leading AWS's global Generative AI and ML strategy for the world's largest Systems Integrators
- Brings the CIO lens vs. CTO lens framing: governance and risk management, not just the flashy use case
- Currently developing his own next-generation adoption framework as original thought leadership
- Speaks directly to an underserved market: upper mid-market and lower-enterprise companies too small for the big GSIs
- Named Solutions Architect of the Year in 2017 and holds AWS, NVIDIA, and VMware certifications
Career Highlights
- Co-author, AWS Cloud Adoption Framework for Artificial Intelligence, Machine Learning, and Generative AI
- Co-author, AWS Cloud Adoption Framework Platform Perspective
- Worldwide Sr. Partner Solutions Architect, Global Lead for Generative AI and ML, AWS GSI/GSP
- 6+ years at Amazon Web Services across senior partner solutions architecture roles
- Solutions Architect of the Year, 2017
- AWS Certified Solutions Architect, NVIDIA-Certified Associate in AI Infrastructure and Operations, VMware VCAP-CID
Podcast Topics
Ready-Made Episodes for Your Audience
Five focused conversations Tony brings to your show, each one a standalone episode your audience will find immediately practical and relevant.
The CIO Lens vs. the CTO Lens: Why Enterprise AI Needs Two Different Conversations
GOVERNANCE-FIRST THINKING FOR ENTERPRISE AI
Most AI conversations happen from the CTO's chair: what can we build, what's the coolest use case, how fast can we ship it. Tony argues the more important conversation is happening in the CIO's office, where the questions are about data leakage, risk exposure, and what happens when an AI system fails inside a live business. He breaks down why enterprises that only have the CTO conversation are setting themselves up for a governance problem they won't see coming.
Audience takeaway: A framework for separating what a company can build from what it should build and control.
Inside the AWS Cloud Adoption Framework for AI: What It Got Right, and What Comes Next
FROM CO-AUTHORING THE FRAMEWORK TO BUILDING ITS NEXT ITERATION
Tony co-authored the AWS Cloud Adoption Framework for Artificial Intelligence, Machine Learning, and Generative AI, now used across hundreds of enterprise AI deployments. In this conversation, he walks through what the framework was built to solve, where it has held up, and why he is now developing his own next iteration focused more heavily on governance and risk, built from what he has seen break in real deployments since it was published.
Audience takeaway: A first look at where enterprise AI governance frameworks are headed next.
The Underserved Middle: Why Upper Mid-Market Companies Can't Get GSI-Level AI Rigor
CLOSING THE GAP THE BIG SYSTEMS INTEGRATORS LEAVE OPEN
The largest System Integrators are built to serve the largest enterprises, and upper mid-market and lower-enterprise companies are often too small to get their full attention, even though they need the same operating discipline. Tony explains why he built CapNexus around this gap specifically, what GSI-level rigor actually means in practice, and what these companies should be demanding from any AI partner they hire.
Audience takeaway: A practical definition of enterprise-grade AI governance that any size company can apply.
Data Leakage, Shadow AI, and the Risk Conversation No One Wants to Have
WHAT ENTERPRISES ARE UNDERESTIMATING IN THEIR AI ROLLOUTS
Every enterprise racing to adopt generative AI is also racing past the questions that matter most: where is data going, who has access to it, and what happens when an employee feeds sensitive information into a tool no one approved. Tony draws on his years inside AWS's largest AI deployments to explain what data leakage actually looks like in practice and how a governance-first approach catches it before it becomes a headline.
Audience takeaway: A clear-eyed look at the risks enterprises are underestimating in their AI rollouts.
From AWS to Founder: Building an AI Practice Around What the Biggest Deployments Taught Him
A FOUNDER'S STORY GROUNDED IN THE LARGEST AI DEPLOYMENTS IN THE INDUSTRY
Tony spent over six years at AWS in progressively senior partner roles, working directly with the world's largest Systems Integrators as they deployed generative AI and machine learning at enterprise scale. He talks about what that seat taught him, why he left to build CapNexus, and how those lessons directly shaped the governance-first practice he runs today.
Audience takeaway: A founder's story grounded in direct experience with the largest AI deployments in the industry.
Connect with Tony
Reach out on LinkedIn or send a booking inquiry to bring Tony on your show.
Watch Tony in Action
A deeper look at Tony's perspective on AI governance
Watch Tony in Action
Recent clips from Tony on AI governance and enterprise risk
What Your Audience Will Take Away
Where AI Ambition Meets Enterprise Risk
Tony's goal on every show is to reframe something familiar. Most leaders know AI is moving fast, and most sense there's risk they haven't fully mapped. Tony gives that risk a name, a cause, and a governance-first path forward, grounded in the frameworks he helped write and the deployments he has seen up close.
Why the CIO's questions about risk matter more than the CTO's questions about features
What the AWS Cloud Adoption Framework for AI got right, and what its next iteration needs to fix
How data leakage and shadow AI quietly build up risk inside enterprises
Why upper mid-market companies are stuck without GSI-level AI governance
What separates a governed AI rollout from one waiting to become a headline
Lessons from six years inside AWS's largest AI deployments, applied to any size company
Ready to Book Tony?
Bring a governance-first perspective on enterprise AI to your audience, grounded in the AWS Cloud Adoption Framework for AI and years inside the largest AI deployments in the industry. Practical, credible, and immediately relevant.