Through AI Governance, MSPs Can Lead Safe and Scalable Adoption
AI adoption is moving fast, but governance is struggling to keep up. In this episode, Chris sits down with Ignacio Lopez, founder of Work-Smart.AI and Fractional Head of AI, to discuss how MSPs can help clients move from AI experimentation to secure, scalable adoption.
Drawing on his experience in auditing, risk management, and enterprise technology, Ignacio explains why governance must come before tools. They explore AI policies, connector risks, access controls, model governance, data foundations, token economics, and the growing threat of shadow AI.
Ignacio shares a practical roadmap for MSPs to evolve from tool resellers to trusted AI advisors by leading assessments, enforcing guardrails, managing deployments, controlling costs, and building governance programs that withstand security, compliance, and business scrutiny.
If you're looking to help clients adopt AI safely and effectively, this episode offers a clear blueprint for turning AI from a shiny tool into a business capability.
Most family offices, wealth firms and family-owned companies have stayed out of AI for one reason. The data is too sensitive to risk. That instinct is correct. It is also solvable.
I am a Fractional Head of AI, and I build. The assessment, the roadmap, the governance and the actual code. When you hire me you get the advisor and the engineer in the same person.
What I build is a Custom AI Operating System. Your files in one structure AI can work with, and written rules for what AI can see and what it can never touch. Then private assistants trained on your own documents, automation for the work nobody should do by hand, and a command center so you see everything running.
Recent work:
-> A wealth advisory firm had 12 years of knowledge trapped in Outlook. I turned 104 documents into 539 answers its team finds in seconds, and no client data touched a public tool.
-> A multi-family office serving Latin American families brought me in to set up AI from scratch. Governance first, the kind a compliance officer can defend, then the automation.
-> A fourth-generation real estate developer was rebuilding quarterly investor reports by hand. I wrote the engine that produces them now. A person reviews the exceptions.
-> A property management firm was coding every vendor invoice by hand. I built the engine that matches each invoice to the right property and proposes the coding. Their team confirms.
-> Capataz, a private AI assistant for Argentina's largest construction group.
-> Victoria, a WhatsApp intake agent for Gru… Read More