ENTERPRISE AI/ML PLAYBOOK v7.4

Enterprise AI/ML Playbook

12-Month Production Roadmap for Regulated Environments

Problem
Enterprise AI programs fail from missing evidence: unclear intent, no acceptance criteria, no telemetry contracts, no rollback plans, and no operating owners
Solution
A 12-month phased roadmap with governance contracts, economic kill criteria, and failure autopsies that force decisions earlier—before they become expensive
AI/ML Playbook
12Month roadmap
139Chart taxonomy
4Failure autopsies
3ROI gates

Most programs fail from missing evidence, not missing models.

After analyzing dozens of failed enterprise AI initiatives across financial services, healthcare, e-commerce, and insurance, clear patterns emerged. Teams weren't failing because of technical limitations—they were failing because of organizational gaps.

The common thread: skipped phases create compounding debt. When teams skip ontology work, they encode wrong assumptions. When they skip discovery, they build for the wrong problem. When they skip validation, they ship hallucinating systems.

$47MInvisible Drift
$123MCompliance Surprise
18moAvg recovery time
Failure Autopsies — $180M+ in Losses
Invisible Drift$47M
Financial Services
Helpful Hallucination$2.3M
Healthcare
Orphaned Model$8.2M
E-Commerce
Compliance Surprise$123M
Insurance

Failure Autopsies — Pattern Recognition

Four documented failures with root cause analysis and prevention strategies.

The Invisible Drift
Financial Services
$47M direct losses
Root: No economic kill threshold, tracked ML metrics not business outcomes
Prevention: Cost Telemetry Contract with kill thresholds
The Helpful Hallucination
Healthcare
$2.3M settlement + 18mo delay
Root: Skipped Phase 7 validation, no hallucination detection
Prevention: Domain expert sampling, red team evaluation
The Orphaned Model
E-Commerce
$8.2M lost revenue
Root: Retraining pipeline on departed engineer's laptop
Prevention: Named owner assignment, Model Card requirement
The Compliance Surprise
Insurance
$123M (fine + class action)
Root: Legal consulted at end not beginning, zip code as race proxy
Prevention: Phase 3.4 regulatory constraint mapping

A year of deliberate organizational change, not twelve months of model building.

The playbook describes 12 phases across 4 quarters. Each quarter solves a human problem before it becomes a technical or financial one. The sequence matters— skipping phases creates debt that surfaces later, usually at the worst possible time.

Q1 Diagnostics: Align people on reality before building anything expensive. Q2 Architect: Reduce ambiguity so teams stop arguing and start shipping. Q3 Engineer: Build with guardrails so operators don't carry risk. Q4 Enable: Make the system survivable after handoff.

Gate Types

HJG Human Judgment Gate (not automatable)
$ Economic Gate (ROI validation required)
⚠ Irreversibility Flag (costly to unwind)
CT Cost Telemetry Contract (kill bindings)
Phase Exit Contracts
Truth Contract
Reality is shared
Economic Contract
Model pays for itself
Risk Contract
Risk designed out
Ownership Contract
Named owner assigned

12-Month Production Roadmap

Quarterly view with monthly phases. ROI gates at Phase 4, 8, and 12.

Q1: DiagnoseQ2: ArchitectQ3: EngineerQ4: EnableJanFebMarAprMayJunJulAugSepOctNovDecGate 1Gate 2Gate 3Q1: DiagnosticsQ1: Diagnostics Jan - Mar✓01 Ontology01 Ontology Jan - Jan✓02 Problem Space02 Problem Space Feb - Feb✓03 Discovery03 Discovery Mar - Mar✓Q2: ArchitectQ2: Architect Apr - Jun✓04 Alignment & Design04 Alignment & Design Apr - Apr✓05 Integration05 Integration May - May✓06 Build06 Build Jun - Jun✓Q3: EngineerQ3: Engineer Jul - Sep✓07 Validation07 Validation Jul - Jul✓08 Pre-Production08 Pre-Production Aug - Aug✓09 Hypercare09 Hypercare Sep - Sep✓Q4: EnableQ4: Enable Oct - Dec✓10 Production10 Production Oct - Oct✓11 Reliability11 Reliability Nov - Nov✓12 Continuous Improvement12 Continuous Improvement Dec - Dec✓
Q1: Diagnose
Q2: Architect
Q3: Engineer
Q4: Enable
ROI Gate

Phase Exit Contract Framework

Every phase requires four explicit contracts before proceeding. No exceptions.

Phase Exit Contract Framework

Every phase requires explicit contracts before proceeding

1
Truth Contract
▼
2
Economic Contract
▼
3
Risk Contract
▼
4
Ownership Contract
▼

Monthly Phase Detail

Each phase has specific deliverables and exit criteria.

MONTH 01
Ontology
Domain expert ID, concept harvesting
MONTH 02
Problem Space
Boundary definition, validation
MONTH 03
Discovery
Stakeholder interviews, data assessment
MONTH 04
Alignment
Priorities, pipeline design [ROI]
MONTH 05
Integration
Cloud selection, IaC modules
MONTH 06
Build
Reproducible builds, telemetry
MONTH 07
Validation
Tests, bias checks, pen testing
MONTH 08
Pre-Prod
Staging, load testing [ROI]
MONTH 09
Hypercare
Launch readiness, rapid iteration
MONTH 10
Production
Deployment, rollback plans
MONTH 11
Reliability
Logging/tracing, on-call
MONTH 12
Continuous
Automation, documentation [ROI]

"Done" is a capability that can be measured, audited, and re-learned by a new team.

The playbook includes a taxonomy of 139 charts across 13 categories, mapped to specific phases. Categories include MLOps & Model Lifecycle (22 charts), Data Quality (14), SRE/Operations (16), Compliance & Audit (10), Human-in-the-Loop (6), and more.

For executives, we defined 6 monthly monitoring signals: Unit Economics Health, Model Performance Decay, Error Rate by Consequence, Human Override Rate, Time-to-Rollback, and Compliance Drift.

139charts in taxonomy
13chart categories
8LLM risk patterns
139-Chart Taxonomy
22
MLOps
14
Data Quality
16
SRE/Ops
10
Compliance
6
HITL
12
Business
8
Cost
9
Security
7
Risk

Executive Control Surface — Monthly Signals

6 monitoring signals for CIO/CTO with critical thresholds.

9
Complete
0
On Track
0
At Risk
0
Behind
target
Unit Economics Health
Finance • CFO
86%
▶
Cost per inference < $0.02
0.018 / 0.02 $
90%
Value per inference > $0.15
0.21 / 0.15 $
100%
Break-even within 6 months
4 / 6 mo
67%
trending
Model Performance
ML Engineering • Director
52%
▶
shield
Operational Resilience
SRE • VP Engineering
NaN%
▶

LLM-Specific Controls

Risk patterns L.1-L.8 with named owners and mitigation strategies.

RiskPhaseMitigationOwner
L.1 Prompt InjectionBuild (6)Input sanitization + allow-listSecurity
L.2 Tool-Call DriftBuild (6)Schema version pinningPlatform
L.3 Retrieval ContaminationValidation (7)Signed data sourcesData
L.4 Context Window DecayPre-Prod (8)Max length + truncation auditML
L.5 HallucinationValidation (7)Factual grounding + samplingML
L.6 Output ValidationPre-Prod (8)PII scrubbing + format checkSecurity

Systems that work, are trusted, and remain governable after leadership attention moves elsewhere.

The playbook includes implementation templates for RACI Matrix (T.1), Risk Register (T.2), Model Cards (T.3), Datasheets for Datasets (T.4), Cost Telemetry Contracts (T.5), and Incident Response Runbooks (T.6).

Without Playbook

  • ✕ Unclear ownership
  • ✕ No kill criteria
  • ✕ Late compliance
  • ✕ Tribal memory

With Playbook

  • ✓ Named owners at every phase
  • ✓ Economic kill thresholds
  • ✓ Compliance from Phase 3
  • ✓ Documented, transferable
Implementation Templates
T.1RACI Matrix
T.2Risk Register
T.3Model Card
T.4Datasheet
T.5Cost Telemetry
T.6Incident Runbook

Playbook Adoption Trends — 12 Month View

Key metrics showing adoption across organizations and implementation improvements.

Organizations Using
↑125%
45
Min: 2Max: 45
Avg Implementation Time
↓39.3%
8.5mo
Min: 8.5moMax: 14mo
Phase Completion Rate
↑38.2%
94%
Min: 68%Max: 94%
Compliance Pass Rate
↑19.5%
98%
Min: 82%Max: 98%

The goal is durability—systems that work after leadership attention moves elsewhere.

A good year ends with: fewer arguments (reality is shared), fewer heroics (risk is designed out), fewer surprises (incentives and ownership are explicit), and continuity (system functions when original team leaves).

Organizations using the playbook report 39% faster implementations, 98% compliance pass rates, and the ability to say "no" as confidently as "yes"—because the economic and risk analysis is explicit.

14 months→8.5 monthsImplementation Time
68%→94%Phase Completion
82%→98%Compliance Pass Rate
Value Summary
$144M
Value Protected
39%
Faster Implementation
98%
Compliance Pass

Failure Prevention Value — $144M Protected

Breakdown of potential losses prevented through playbook governance patterns.

$0M$50M$100M$150MPotential Loss: +$180M$180MInvisible Drift ($47M): $-47M$-47MHelpful Hallucination ($2.3M): $-23M$-23MOrphaned Model ($9.6M): $-10M$-10MCompliance Surprise ($123M): $-64M$-64MValue Protected: +$36M$36MPotential LossInvisible Drift ($47M)Helpful Hallucination ($2.3M)Orphaned Model ($9.6M)Compliance Surprise ($123M)Value Protected
Total
Increase
Decrease

Key Principles

What "Done" Means
  • "Done" is not a model that runs—it's a capability that can be measured, audited, and re-learned
  • Architecture is in contracts between modules, not in code
  • Models are processes not products
What Breaks Teams
  • Compliance treated as sign-off not design constraint
  • Economic viability treated as constraint to work around
  • Autonomy treated as default rather than earned privilege

"Skipping phases creates debt that surfaces later—usually at the worst possible time. The playbook forces those decisions earlier."