About

About Frank Sellhausen

Three careers spent standing between powerful capabilities and the people they affect — and keeping them honest about reality. Now helping organizations redesign work systems for AI.

“The unit of AI transformation is the outcome-producing work system — not the task where AI enters.”

AI amplifies the system it enters. Clean process or broken process. Most AI rollouts make one task faster and call it transformation. Real transformation changes the work system — roles, coordination, authority, expertise, and evidence — so the whole production function improves.

Transformation that cannot survive examination, audit, procurement, or oversight is incomplete. Governance is a property of the work system, not a layer stapled on top.

Who the work is for

Organizations where AI decisions land on real people — and someone has to answer for them.

Regulated financial institutions building AI into lending, underwriting, and customer decisions. Federal agencies operating under M-25-21 and the frameworks downstream of it. Military programs deploying AI into decisions that touch service members and mission outcomes. Large enterprises with consequential decisions, regulatory exposure, or coordination that doesn’t scale.

Anywhere the work system produces outcomes that affect people — and someone has to be able to explain what happened, why, and on what evidence.

Three vantage points

The same discipline across three careers: stand between a powerful capability and the people it affects, and keep it honest about reality.

Federal bank examiner. As a Risk Management Examiner in Charge at the FDIC, I examined institutions from small community banks to multi-billion-dollar asset holders against federal standards. Led model risk and third-party risk reviews. Conducted IT and BSA/AML examinations. Briefed findings to bank management, boards of directors, and regulatory leadership. What that work built: the reflex to look at a document with skepticism before belief, and the discipline to put findings on paper that survive examination.

Builder inside a Fortune 50. Five years progressing across analytics, data engineering, and AI product management. My team built the account-level data layer that served as the single source of truth across the enterprise — reconciling a landscape of disparate systems that had been producing different versions of the same facts. I authored the Data Engineering Playbook for my organization (provenance, lineage, controls, data contracts) and later owned the AI use-case approval process for the product management organization, defining the requirements, documentation, and acceptance criteria for AI features built on vendor-supplied models. What that work built: a builder’s read on what governance has to actually look like inside the build, not stapled on top.

Sixteen years in uniform. U.S. Army Drill Sergeant and Observer-Controller/Trainer at a Combat Training Center — the unit type that originated the After-Action Review. Observed units operating under pressure, assessed performance against standards, delivered structured, evidence-based feedback. Functionally, the same discipline as a model risk review: observe, document, defend the assessment, hand back something the next team can act on.

Credentials

MBA (Texas A&M) · BS Computer Science (WGU) · BBA Finance (UW-Milwaukee)

PMP · UT Austin AI/ML · UT Austin Full Stack

In progress: Stanford LEAD · Georgia Tech MS CS · IAPP AIGP · ISO 42001 Lead Auditor

Sellhausen Consulting LLC

Round Rock, TX

SAM.gov UEI
RQJEPZ47MK68
Texas CMBL
14229761185
Federal designation
Service-disabled veteran-owned business (SDVOSB certification in process)
NAICS codes
541611 · 541512 · 541519 · 541618 · 541690 · 541511

Next step

Ready to redesign a work system?

Start with the free Field Guide or talk about a work system that already feels the strain.