AI & Technology Governance
How should we decide?
How the organization decides what receives resources, what scales, what continues, and what stops.
Govern what to fund, what to scale, and what to stop.
Challenges
The situation
Technology arrives continuously—new AI capabilities, platform releases, security requirements, vendor offerings—while many decision structures were built for a slower cycle. New AI capabilities and technologies are arriving faster than most healthcare organizations can prioritize and absorb them. That increasingly includes AI agents—built, shared, and updated continuously, each needing an owner, a boundary, and a way to shut it off.
What we do
Where SMA comes in
SMA works with executives to review existing governance and establish clear, nimble governance that connects technology investment to enterprise priorities, operational capacity, and measurable value. The AI lane goes deep—risk tiers, decision rights, AI economics, and clear ownership of operational outcomes—while the surrounding technology-governance environment is assessed in context. The system governs the enterprise technology-change portfolio; AI is its deepest and most urgent lane.
Risk, cybersecurity, and compliance live inside the decision architecture, and your specialists remain the authorities in their domains. This is not AI compliance consulting, AI strategy consulting, or cybersecurity consulting. It is the operating system for technology decisions.
How the engagement runs
Assess → Act → Advance
Fixed-fee and principal-led, sized to the scope: an AI deep dive with the enterprise decision, intake, and value architecture around it, or a broader enterprise governance assessment that adds executive and board architecture. You leave with a decision-rights gap map, a governance maturity read against national benchmarks, a 90-day build roadmap, an AI and technology portfolio heat map (scale, continue testing, reassess, stop, not ready), and an executive governance scorecard leadership keeps using after SMA leaves.
Design, stand-up, operate through live decisions, refine, and transfer. SMA doesn't leave when the artifacts exist—real technology and AI decisions run through the system before transition.
A standing seat in the governance cadence—portfolio challenge, value validation, and recalibration as platform, AI, and vendor capabilities evolve.
A governance operating system—not AI compliance, AI strategy, or cybersecurity consulting.
More capability ≠ more value
Talk to Us
Start with the decision question
Tell us how technology and AI decisions get made today, and where they're getting stuck. We'll review it and follow up directly.
Talk to Us