Healthcare AI Executive | GTM Strategist | Board Advisor
26 Years Building the Commercial Infrastructure of Healthcare AI
Healthcare AI and presales executive with 26 years scaling solutions organizations, commercializing AI-driven platforms, and leading technical teams through the full arc of enterprise growth — from early-stage clinical AI to billion-dollar SaaS adoption across 3,000+ health systems covering 70% of the North America market.
How I Engage
Core Service Offering
Healthcare organizations building AI capability in 2026 face a structural trap that the market created and most vendors have no incentive to solve. A health system deploying AI comprehensively today can realistically find itself managing contracts and compliance obligations across 20 to 30 separate AI vendors. Each one is a separate attack surface. Each one is a separate audit exposure. Each one has its own governance gap. And none of them were designed to work together in any centralized, governed, or auditable way.
This is not an AI strategy. It is an AI liability built one vendor contract at a time.
A 2026 Black Book survey found only 22% of hospitals can produce a defensible 30-day AI audit trail — meaning 78% of health systems are operating AI they cannot fully account for, govern, or defend. Seventy percent have experienced at least one AI pilot failure due to weak integration, workflow misalignment, or data gaps. And the regulatory environment has stopped waiting — Texas, California, Colorado, and a growing number of states now impose hard legal requirements on AI governance, audit documentation, and clinical AI transparency, with enforcement effective 2026.
Enterprise AI Governance & Orchestration is a complete consulting and custom implementation service that designs, builds, and governs a unified AI stack for healthcare organizations — replacing point-solution sprawl with a single, centrally managed architecture that is audit-defensible, compliance-designed, and built to operate at enterprise scale.
Every engagement is fully bespoke. No off-the-shelf stack is forced on the client. The architecture is purpose-designed around the organization's existing systems, clinical workflows, EHR environment, compliance posture, and strategic objectives. Where custom development is required — custom integrations, purpose-built tooling, proprietary governance logic — that software is designed and built as part of the engagement.
The result is a unified AI stack managed through a single pane of glass governance console — one centralized view that gives clinical informatics leadership, the CISO, the compliance function, and the board complete real-time visibility into every AI tool running in the organization, what data each one is accessing, how each one is performing against defined clinical and compliance boundaries, and a continuous, exportable audit trail that covers everything.
Before architecture can be designed, the full AI landscape must be understood. Most organizations significantly underestimate the AI already operating inside their environment — vendor-embedded models, departmental point solutions procured outside IT, and unsanctioned tools that procurement and governance committees have never reviewed. Every engagement begins with a comprehensive AI inventory and exposure assessment. Complete visibility is the foundation. Without it, governance is theater.
HIPAA, HITRUST, and the expanding patchwork of state AI law — Texas TRAIGA, California AB 489, Colorado's AI Act, and others taking effect through 2026 — are built into the architecture from the first design decision, not mapped on retroactively after vendors are selected and contracts are signed. Organizations that retrofit compliance onto a pre-built AI stack face costly remediation, contract renegotiation, and in some cases full rebuilds. The architecture stage is the only point at which compliance can be embedded without those costs.
Every AI model, every agent, every data access event — logged, traceable, and reportable from one centralized governance layer. The single pane of glass governance console gives the CISO, compliance officer, clinical informatics leadership, and board the same real-time picture: what AI is running, what data it is touching, how it is performing against defined boundaries, and a continuous audit trail exportable on demand. This is the infrastructure that transforms an AI governance committee on paper into an AI governance function in practice.
Consumer-grade AI hallucination rates are a nuisance. In clinical settings, they are a patient safety issue and a liability event. Anti-hallucination guardrails, human-AI handoff thresholds, clinical workflow boundaries, and autonomous decision prevention are designed into every layer of the stack. The architecture defines precisely where AI operates independently, where it supports a clinician, and where a human decision is non-negotiable — protecting both patient safety and organizational liability exposure.
Cannot produce a 30-day AI audit trail
Source: Black Book 2026
Have experienced AI pilot failure
Separate AI vendor relationships in a fully AI-enabled health system
This service is designed and delivered by a 26-year veteran of enterprise healthcare AI deployment across 3,000+ health systems — not an advisor who has studied the problem, but an operator who built governance infrastructure at the scale most organizations are now trying to reach.
Annual pipeline governed under HIPAA, HITRUST, and enterprise AI compliance frameworks
Health systems and IDNs — direct knowledge of where real-world AI integration fails
Building, deploying, and governing enterprise clinical AI at Nuance and Microsoft
Single deal architected and closed — security, compliance, data governance, multi-system integration
| Mode | Engagement Type | Description |
|---|---|---|
| ADVISORY | Strategic Advisory | Governance architecture design, AI landscape audit, vendor selection framework, and compliance roadmap. Delivered as a strategic engagement with defined deliverables. Ideal for organizations in early planning stages or those validating an existing AI strategy. |
| FRACTIONAL | Fractional Chief AI Officer | Embedded executive leadership across the full governance and AI strategy function. Provides ongoing decision authority, vendor management, board reporting, and operational oversight without permanent headcount. Structured as a retained engagement with defined scope and availability. |
| BUILD | Full Implementation Partnership | End-to-end design, custom build, integration, and deployment of the unified AI stack and single pane of glass governance console. The complete engagement from initial audit through production go-live. One accountable partner owns the full outcome. |
For organizations that proceed with a full implementation engagement — where custom software is designed and built as part of the stack — ongoing governance retainer and operational support are available. The organization retains the architecture and code. Commercial terms for retainer and partnership arrangements are tailored to the scope of what was built and the ongoing needs of the engagement.
Comprehensive inventory of every AI tool running in the organization — sanctioned, vendor-embedded, and unsanctioned. Compliance posture mapping, data access footprint analysis, vendor contract review, and governance gap assessment.
Purpose-designed unified AI architecture built around the organization's EHR environment, clinical workflows, compliance requirements, and strategic objectives. All compliance requirements embedded at this stage — not retrofitted later.
Full implementation: commercial platform integrations, custom software development where required, EHR and clinical system integration, governance console deployment, audit trail infrastructure, and responsible AI guardrail implementation.
Go-live management, clinical workflow validation, governance console commissioning, audit trail verification, staff enablement, and regulatory readiness documentation.
Continuous governance operations, architecture evolution, regulatory monitoring, AI performance oversight, and board reporting support. The organization is never left holding a complex system without a knowledgeable operational partner.
"One architecture. One governance console. One accountable partner. Built to last longer than the next vendor contract renewal cycle."
Go-to-market strategy, presales organization design, and commercial infrastructure for healthcare AI startups and platforms scaling from early traction to enterprise revenue.
Independent board director and strategic advisory engagements for healthcare technology companies. Bringing 26 years of enterprise AI commercialization and C-suite relationship depth.
Board & Advisory
Selectively available for independent board director and strategic advisory board positions with healthcare technology companies where deep AI commercialization experience, enterprise GTM credibility, and a genuine C-suite network across the North America healthcare market create tangible governance and strategic value.
Commercial oversight — GTM strategy, revenue model design, and presales infrastructure
Healthcare AI governance — responsible AI practices, clinical workflow compliance, HIPAA/HITRUST
Market access — direct relationships across 3,000+ health systems, IDNs, and Life Sciences organizations
M&A and integration experience — Nuance/Microsoft acquisition leadership, commercial team integration
Available for consulting partnerships, board discussions, and executive advisory engagements in healthcare AI.
Executive Profile
The credentials on this page were earned inside two of healthcare technology's most consequential AI platforms — Nuance Communications and Microsoft — over 26 years of progressive leadership from individual sales engineer through senior director of presales and revenue operations. The career summary below is provided for visitors conducting due diligence on a partnership, board, or advisory engagement.
"Most executives advise on healthcare AI transformation. This background was built inside it — 26 years designing, selling, governing, and scaling the enterprise AI platforms that now run inside 70% of North American healthcare."
The career at Nuance Communications — and later Microsoft, following the 2022 acquisition — began in 1999 as a sales engineer delivering healthcare technology demonstrations and supporting clinical deployments for hospital clients. Over the next 26 years, the role evolved through every stage of enterprise presales and commercial leadership: individual contributor, team manager, senior director of a global presales organization, and ultimately the senior revenue operations and AI governance authority for one of the largest healthcare AI portfolios in North America.
The most significant chapter was leading the presales commercialization of Dragon Ambient eXperience (DAX) — the ambient AI clinical documentation platform now embedded in 30+ EHR ecosystems and used by tens of thousands of clinicians daily. This meant leading the organization through the complete arc of an AI product's life: early clinical validation and proof-of-concept deployments, enterprise SaaS adoption at scale, competitive market leadership, and the governance and compliance infrastructure required to operate at $1B+ pipeline scale across 3,000+ health systems.
Microsoft Corporation / Nuance Communications · June 1999 – September 2025 · 26 Years
Microsoft
Nuance / Microsoft
Nuance Communications
Nuance Communications
Dictaphone Corporation (Acquired by Nuance)
Unified AI stack · Single pane of glass governance · Shadow AI elimination · Audit trail infrastructure · Compliance by design · Responsible AI guardrails · HIPAA · HITRUST · State AI law
Ambient AI · DAX Copilot · Dragon Medical One · EHR integration · FHIR · HL7v2 · Epic · Cerner · Athena · Meditech · Clinical workflow AI · Prior authorization automation
Go-to-market strategy · Presales organization scaling · AI platform commercialization · Revenue operations · Commercial infrastructure · Proof-of-value design · Salesforce CPQ
C-suite engagement (CIO/CMIO/CFO/CNO) · Complex negotiations · Contract structuring · MSA · BAA · DPA · Pricing strategy · Multi-year modeling · $1M–$32M deals
SE organization building · Coach-Care leadership · Value-based selling · Demo excellence · Technical discovery · Competitive intelligence · Executive advisor development
Claude · Microsoft Copilot · ChatGPT · Azure AI · AI-augmented workflow · Prompt engineering · AI platform strategy · Life Sciences real-world data
01
The organizations that scale AI successfully are not the ones that ran the most pilots. They are the ones that built the governance infrastructure, commercial frameworks, and team capability that made consistent performance repeatable. Every engagement is designed to leave that infrastructure behind — not a report that needs a follow-on engagement to execute.
02
Twenty-six years of direct engagement with CIOs, CMIOs, CFOs, and General Counsel at major health systems produced a simple conviction: C-suite stakeholders can distinguish between an advisor who has studied their problems and one who has solved them. The credibility that matters in a board room or a partnership negotiation is the kind that comes from having been accountable for the outcomes.
03
Most organizations treat AI governance as a compliance burden. The organizations that build genuine governance infrastructure discover it is a competitive advantage: faster regulatory approvals, stronger board confidence, cleaner audit outcomes, and the ability to move into new AI capabilities without rebuilding compliance posture from scratch each time.
04
The fragmented vendor model — where five vendors each own one piece and no one owns the outcome — is the structural failure at the center of most healthcare AI disappointments. Every engagement is structured so there is one accountable partner for the full arc from design through deployment. That accountability does not transfer to the client until the system is running and the governance is operational.
Expected Completion: 2026
Western Governors University (WGU), Salt Lake City, UT
Internal executive leadership programs covering AI strategy, healthcare data architecture, enterprise presales leadership, and inclusive team development. Active daily practitioner of Claude, Microsoft Copilot, and ChatGPT as part of consulting workflow, content development, and solution design.
Full professional record, recommendations, and endorsements available on LinkedIn
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