This is what a governance accountability review actually produces
Real output from the AI Governance Accountability Review, built on a mid-market packaging manufacturer with active PE oversight. Decision accountability map, posture score, heat map, board readiness, EU AI Act exposure, and priority gap register — not a framework slide.
Mid-market flexible packaging manufacturer — PE-backed, June board cycle
A company with $340M in revenue, four converting facilities, and a PE sponsor requesting an AI governance update at the upcoming June board meeting. The CFO and audit committee chair have both asked pointed questions about AI risk and decision reliability in the past 90 days.
“We have AI running in production — SAP IBP for demand forecasting, a vision-based quality inspection system across three lines, and a handful of vendor-embedded tools we activated through Salesforce and Pricefx. None of them went through a formal governance review before deployment. The board hasn’t asked about AI governance yet, but our PE sponsor’s operating partner mentioned that their LPs are starting to ask about it. We need to understand where we actually stand before June.”
Governance exposure summary
Deployment surface, accountability gaps, governance structure assessment, and EU flag — produced after Stage 1 inputs.
Pinnacle Packaging Solutions currently operates five AI-enabled systems across core workflows. The SAP Integrated Business Planning (IBP) demand forecasting module, live since January 2025, generates weekly demand signals that directly drive approximately $18M in quarterly raw material purchase commitments and production scheduling at all four facilities. The Cognex ViDi vision-based defect detection system operates on three converting lines, making pass/fail decisions on finished goods rolls prior to shipment — including product destined for EU food-contact customers. A vendor SaaS pricing optimization tool (Pricefx) and Salesforce Einstein lead scoring both have human review before any binding effect. A predictive maintenance pilot at the Louisville facility is in shadow mode and has not yet influenced operational decisions. The IBP and vision systems represent the two consequential exposures: both influence multi-million dollar commitments or product safety outcomes, and neither has formal documented accountability.
Current governance structures are nominal and not decision-relevant. Existing policies address only generative AI use by employees and do not touch operational or vendor-embedded AI. The IT steering committee has not taken or documented any governance decision regarding actual AI deployments. No AI risk committee, no system inventory, and no documented pre-deployment review exist. No evidence shows these governance structures have been invoked to manage any production AI system.
Decision accountability map
Named accountability, override path, board visibility, and EU Act relevance — one row per consequential system.
Governance posture score
Four dimensions scored on a 1–4 scale. 1 = Critical gap requiring immediate action. 4 = Embedded and board-visible.
Accountability heat map
At-a-glance governance status across consequential AI systems.
| System | Accountability | Override Path | Board Visibility | EU Act Relevant | Overall |
|---|---|---|---|---|---|
| SAP IBP demand forecasting module | ✗ | ✗ | ✗ | ✓ |
RED
No formal accountability, override, or board visibility for a system making high-value procurement decisions with EU implications.
|
| Vision-based defect detection (Cognex ViDi) | ✗ | ✗ | ✗ | ✓ |
RED
No accountable party, override documentation, or incident tracking for a high-risk system with direct EU food-contact exposure.
|
Human-in-the-loop assessment
Whether your oversight model would hold up under compliance review or board questioning — not whether human review exists in principle.
The SAP IBP demand forecasting process relies on informal review by a demand analyst who compares forecasts to a personal Excel model and flags anomalies. No formal override thresholds exist. The one significant override in the past year — a resin forecast running 28% above market signal — was not formally logged, and escalation criteria are undefined. There is no evidence of regular override drills, scenario testing, or formal training for the analyst handling the output. The analyst is not equipped to challenge the AI model’s logic or detect systemic failure modes.
The vision-based defect detection system failed to catch a quality issue in February 2026 — a batch passed inspection at Cincinnati and was rejected by a customer for color registration errors. The system had been running outside calibration range due to a lighting change. This was handled as a quality event under ISO 9001, not examined as an AI system failure, and was not logged as an AI incident.
Board readiness analysis
What you can credibly state today, what you cannot, and the questions your board is likely to ask first.
Your Board Governance Review
This reflects what your governance model reveals under scrutiny, not what it intends to be.
- We have identified the AI systems in use in operational decision-making.
- We can describe the core business processes those AI systems affect.
- Functional owners intervene in AI-driven decisions when anomalies are detected.
- We have a formally documented system of accountability for AI-enabled decisions.
- We maintain a log or evidence of AI overrides or incidents.
- We have reviewed our systems for EU AI Act high-risk classification or conformity.
- Our board receives regular, system-level reporting on AI risk and performance.
- Who is accountable — by name — for the reliability and risk of these AI systems?
- If the EU regulator asked for our conformity assessment next week, what could we provide?
- How do we know human overrides are being used appropriately, and are these tracked?
- What is our plan and timeline to close the EU AI Act compliance gaps before August 2026?
- Have AI-driven decisions already caused any near-misses or operational issues we have not discussed at board level?
EU AI Act exposure
System-level classification, enforcement timeline, and immediate action required.
The vision-based defect detection system directly controls product quality on goods entering the EU food-contact market and meets multiple Annex III high-risk criteria. There is no evidence of conformity assessment, system inventory, accountability assignment, incident logging, or formal oversight documentation. Enforcement begins August 2, 2026, and fines can reach 7% of global annual turnover. The SAP IBP module also influences purchasing decisions with EU supplier impact and has not been reviewed.
Priority gap register
The five gaps that represent the highest risk — ranked by regulatory exposure and operational consequence, with named owners and action deadlines.
Download the Executive Brief
This is what a finished AI Governance Accountability Review delivers — the document an executive would take into a June board meeting or PE operating partner conversation. Decision accountability map, posture score, EU AI Act exposure, and priority gap register in a single PDF.
Download PDFThis is an Executive Access tool
The AI Governance Accountability Review is available exclusively to Executive Access members. It produces a complete two-stage board governance review, including the accountability map, posture scoring, heat map, EU AI Act classification assessment, and priority gap register — structured for a PE operating partner conversation or board pre-read.
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Most advisory conversations start with someone who has already used the tool and wants to take the output into a real decision. If the gaps this review surfaces require remediation planning, peer benchmarking, or board preparation, advisory support is available.