Worksheet5 files · Assess
AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
baciu.com service area
Technology incident AI readiness kit
A technology operations kit for preparing AI-assisted incident triage, owner routing, release evidence, and support handoffs before production escalation.
How we approach it
We start with the business process, the users, and the failure modes. Then we choose the smallest architecture that can be measured, reviewed, and operated safely.
Explore pageWhat good looks like
A good AI system leaves traces: source evidence, evaluation history, cost and latency telemetry, and clear escalation rules for the cases that should not be automated.
Explore pageReadiness before autonomy
- Score business value, data readiness, action safety, evaluation coverage, and operational ownership.
- Separate assistant workflows from agentic workflows before authority expands.
- Turn weak scores into specific remediation work instead of vague risk notes.
Subject expansion
Pages that drill deeper into this delivery surface
AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Explore pageGovernance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Explore pageRetrieval evaluation set
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Explore pageModel operations runbook
A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Explore pageExecutive AI roadmap brief
A board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.
Explore pageAI incident tabletop
A tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.
Explore pageAgent operating model
A practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.
Explore pageWorkflow intake template
A structured intake template for deciding whether a process should become an assistant workflow, agent workflow, or deterministic automation.
Explore pageDelivery artifact
Technology incident AI readiness kit
Use these files as the starting point for a workshop, operating review, or delivery handoff.
Narrative outlineIncident kit
A technology operations kit for preparing AI-assisted incident triage, owner routing, release evidence, and support handoffs before production escalation.
Incident signal mapCSV signal mapSignal map for alerts, traces, tickets, ownership metadata, change records, customer impact, and AI triage use.
Routing matrixCSV matrixRouting matrix for severity, service, owner, escalation path, evidence packet, and response expectation.
Incident schemaJSON schemaStructured incident fields for AI summaries, source evidence, severity, owner, confidence, and handoff state.
Incident bridge briefBridge briefIncident bridge brief for AI-prepared context, suspected cause, customer impact, owner actions, and rollback status.
Postmortem mapJSON mapPostmortem mapping for detection gap, routing delay, evidence quality, rollback decision, and knowledge update.
Resource library
Delivery artifacts that make the site operational, not just informational.
Use these outlines as starting points for assessments, runbooks, governance reviews, and executive planning.
352artifacts
10phases
202formats
Matrix5 files · Govern
Governance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Eval set5 files · Validate
Retrieval evaluation set
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Delivery atlas
Advanced navigator for capabilities, programs, and systems.
Filter, compare, and jump into detailed pages for AI architecture, execution, and governance.
Implementation library
Adoption enablement kit
An enablement kit for driving trusted AI adoption through training, champion networks, feedback loops, and behavior metrics.
Agent cost allocation model
A finance model for attributing AI runtime cost by workflow, department, customer segment, provider, and outcome.
Agent incident communications plan
A communications plan for AI incidents covering internal escalation, customer updates, regulatory notice, and postmortems.
Agent operating model
A practical operating model for assigning ownership across AI product, platform, risk, operations, and business teams.
Agent release governance kit
A release governance kit for managing prompt, model, policy, retrieval, and tool-authority changes in agentic systems.
AI data loss prevention kit
A data-boundary kit for preventing sensitive data leakage across prompts, retrieval, logs, model providers, tools, and exports.
AI data processing addendum
A review outline for documenting AI data handling, retention, subprocessors, residency, and customer control requirements.
AI economics benchmark pack
A benchmark pack for measuring AI value across baseline cost, adoption, unit economics, and value-review decisions.
AI economics control plane kit
A control kit for managing AI value through adoption curves, unit economics, operating cost, quality signals, and scale decisions.
AI incident communications kit
An incident communications kit for AI failures covering internal escalation, customer messaging, regulatory notice, and postmortem evidence.
AI incident tabletop
A tabletop exercise for AI services that can produce wrong answers, unsafe actions, policy violations, or outage cascades.
AI operating cadence pack
A cross-functional operating cadence for weekly AI service reviews, monthly value decisions, release gates, and escalation ownership.
AI portfolio prioritization kit
A portfolio prioritization kit for ranking AI opportunities by value, feasibility, risk, operating readiness, and learning leverage.
AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
AI service SLO template
A service-level objective template for AI latency, quality, cost, availability, escalation, and degraded-mode behavior.
Automation rollout runbook kit
A rollout runbook for moving AI-assisted workflows from pilot to controlled scale with queue gates, training, controls, and adoption metrics.
Autonomy risk register
A risk register for tracking AI authority, reversibility, sensitive data exposure, failure modes, mitigations, and owners.
Cost and latency dashboard
A dashboard outline for monitoring provider mix, cost drift, latency budgets, fallback rates, and quality regressions.
Customer support AI operations kit
An operations kit for AI-assisted support queues covering triage policy, containment metrics, escalation, QA, and customer communications.
Data source inventory
A source inventory for mapping owners, freshness, permissions, quality issues, retention rules, and ingestion priority.
Evaluation regression suite kit
A regression suite for AI releases covering task quality, source grounding, safety, tool behavior, latency, and cost movement.
Evaluation release gate
A release-gate template that connects evaluation results, known regressions, approval decisions, rollback, and launch notes.
Executive AI roadmap brief
A board-ready outline for connecting AI initiatives to outcomes, risk gates, build sequence, and decision cadence.
Executive steering pack
A steering-committee packet for connecting AI portfolio decisions to milestones, risks, spend, and operating outcomes.
Finance close automation evidence kit
A finance operations kit for AI-assisted reconciliation, variance explanation, close controls, reviewer evidence, and audit-ready reporting.
Financial services model risk ops kit
A model risk operations kit for financial services AI systems covering evidence, approvals, monitoring, controls, and audit readiness.
Governance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Healthcare AI safety intake kit
A healthcare AI safety intake kit for triaging clinical-adjacent workflow ideas before pilot, procurement, or production rollout.
Human approval policy
A policy template for defining which AI decisions require approval, who approves them, and what evidence is required.
Insurance claims AI control kit
A claims operations kit for using AI across intake, coverage evidence, adjuster review, leakage monitoring, and customer communications with explicit controls.
Logistics exception control tower kit
A logistics operations kit for detecting shipment, inventory, carrier, supplier, and customer-commitment exceptions with evidence-backed recovery paths.
Manufacturing quality intelligence kit
A manufacturing AI kit for connecting quality signals, maintenance notes, production exceptions, and operator feedback into governed intelligence loops.
Memory and context governance kit
A context-governance kit for deciding what AI systems may remember, retrieve, personalize, retain, forget, and expose to users.
Model fallback decision tree
A decision tree for routing between models, cached answers, degraded mode, escalation, and temporary shutdown.
Model observability telemetry kit
A telemetry kit for model-backed services covering request traces, quality signals, cost, latency, fallback, and incident triggers.
Model operations control plane kit
An operating kit for model routing, runtime incident triage, provider fallback drills, release gates, and remediation ownership.
Execution lab
Interactive planner for AI implementation roadmaps.
Tune delivery tempo, autonomy, and risk profile to inspect recommended phases, dependencies, and control gates.
Risk profile
Delivery tempo
Recommended phases
W1+2
Data readiness
No retrieval without source discipline
W3+3
AI product design
Trust is a product feature
W6+4
Tool orchestration
Action with accountability
W10+3
AI evaluation lab
Every release earns trust
W13+2
AI governance
Control where the work happens
W15+2
Enablement and handoff
Client teams can operate independently
Capability radar
Interactive map of AI implementation priorities.
Select an operating perspective and horizon to inspect relevant tracks, signals, and linked decision pages.
Priority tracks
Adoption enablement kit
Adoption managed as an operating system
Open pageExecutive AI roadmap
Strategy with an implementation path
Open pageDelivery governance
Governance in the delivery loop
Open pageStudio delivery model
Delivery designed for durable ownership
Open pageAI governance
Control where the work happens
Open pageExecution blueprint
How this capability expands into production service.
Each area is delivered through explicit definition, measurable validation, and operating governance that client teams can inherit.
Operating checklist
What gets delivered with this work.
01
Architecture
A clear system map covering models, tools, data, workflows, users, and failure modes.
Explore page02
Evaluations
Task sets, regression checks, and release criteria for measurable AI behavior.
Explore page03
Controls
Human approval, access, logging, data-boundary, and incident-response rules.
Explore page04
Handoff
Documentation and ownership so the client can operate the system after launch.
Explore pageOperating risks to control
- Expanding autonomous authority without calibrated approval policies.
- Stale or conflicting sources that silently degrade decision quality.
- Insufficient traceability for automated actions and human interventions.
- Release processes that skip relevant regression scenarios.
Frequent questions
How do we choose where automation starts?
Start with repetitive, reversible workflows where outcomes and failure boundaries can be measured.
How do we prove quality before launch?
Use eval sets, adversarial scenarios, and explicit go/no-go criteria tied to business impact.
How does the team stay in control?
With authority boundaries, confidence thresholds, escalation packets, and complete execution traces.
What happens when model behavior changes?
Treat model and prompt changes as releases: test, review, approve, and roll out with rollback paths.
Coverage map
Companion pages for this delivery area
AI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Explore pageGovernance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Explore pageRetrieval evaluation set
A starter evaluation set for testing source grounding, citation behavior, permission boundaries, and answer quality.
Explore pageModel operations runbook
A production runbook for model routing, fallback, cost controls, latency, tracing, degraded mode, and release review.
Explore pageRelevant pages
Representative AI deployments, rewritten as reusable patterns.
Resource library
Downloadable implementation outlines for teams planning, evaluating, governing, and operating production AI systems.
Explore pageAI readiness scorecard
A scoring worksheet for deciding whether a workflow is ready for autonomous or semi-autonomous execution.
Explore pageGovernance control matrix
A control matrix that maps AI capability scope to data access, tool authority, approvals, logging, and incident response.
Explore page