AI Academy

Outcome: An adoption plan with role changes, training, shadow-mode evidence, feedback channels, workload measures, and transition gates.

Outcome: An AI access, logging, and retention standard mapped to roles, data classes, and evidence needs.

Outcome: An autonomy decision that states whether the use case needs a fixed workflow or agent-like behavior.

Outcome: A production evaluation plan with monitored indicators, rollback triggers, incident roles, and evidence requirements.

Outcome: A source-grounded account brief with known facts, hypotheses, open questions, risks, and a call objective.

Outcome: A receivables workflow map with matching rules, dispute routing, customer controls, and approval boundaries.

Outcome: An audit-support workflow preserving source lineage, preparer review, approval, and evidence retention.

Outcome: A campaign test plan linking segments, hypotheses, variants, approvals, and outcome measures.

Outcome: A channel-by-channel repurposing brief with source fidelity and approval checks.

Outcome: An exception taxonomy with escalation triggers, owners, service levels, and closure evidence.

Outcome: A document-review protocol defining extraction fields, evidence links, exceptions, and sign-off.

Outcome: A conversion-copy test brief with evidence-backed claims, variants, approval, and measurement.

Outcome: A lead-support schema with evidence fields, qualification boundaries, CRM checks, and rep approval.

Outcome: A controlled onboarding workflow with approved sources, checks, escalation, and learning evidence.

Outcome: A proposal-and-handoff specification defining approved inputs, claims, commercial approvals, CRM fields, and delivery commitments.

Outcome: A close-support design with break categories, evidence requirements, reviewer ownership, and sign-off.

Outcome: An SOP assistance design with source ownership, version controls, and exception handling.

Outcome: A case-routing specification with labels, ownership, priority rules, thresholds, and review paths.

Outcome: A voice-of-customer evidence set separating observed language, themes, frequency, and interpretation.

Outcome: An evidence-based timeline connecting major AI shifts to current business capabilities.

Outcome: A documented vendor assessment covering data, security, model controls, contracts, operations, and exit.

Outcome: An email-routing taxonomy with confidence thresholds and an escalation matrix.

Outcome: A de-identification protocol with data inventory, transformation rules, residual-risk testing, and approval.

Outcome: A recurring-report specification with governed inputs, output schema, checks, and accountable sign-off.

Outcome: A newsletter production workflow with approved sources, issue schema, fact checks, and sign-off.

Outcome: A summarizer specification with document boundaries, output schemas, source links, tests, and review.

Outcome: A review-console specification covering evidence, actions, permissions, queues, audit logs, and metrics.

Outcome: A bot architecture specifying identity, message flow, permissions, limits, fallback, logging, and tests.

Outcome: A classifier blueprint containing the label schema, output contract, test set, thresholds, review path, and refresh policy.

Outcome: A RAG MVP specification with approved sources, retrieval tests, citations, access controls, and maintenance.

Outcome: An extraction product specification with schema, validation, confidence, evidence, exceptions, and tests.

Outcome: A harness specification with test-set versioning, result schema, release gates, monitored indicators, rollback triggers, and ownership.

Outcome: A governed source inventory, access model, freshness policy, and retrieval test set.

Outcome: A spreadsheet-assistant design with read/write boundaries, formula checks, approvals, rollback, and tests.

Outcome: A baseline routing specification and reproducible evidence record.

Outcome: A small evaluation set with explicit groundedness, citation, and abstention checks.

Outcome: A unit-economics model covering inference, latency, review effort, and business value.

Outcome: A feedback-analysis specification with taxonomy, evidence, sampling, evaluation, review, and refresh rules.

Outcome: A prototype evidence report covering grounding, recommendation quality, reviewer control, failures, and production gaps.

Outcome: A data-readiness inventory with owners, access conditions, quality risks, representativeness gaps, and remediation actions.

Outcome: A private-inference architecture decision covering threat model, operations, cost, controls, and ownership.

Outcome: A prototype evidence report comparing summaries with source facts, omissions, reviewer effort, and production gaps.

Outcome: A decision-support evidence report covering reproducibility, backtesting limits, uncertainty, and prohibited claims.

Outcome: An expense taxonomy with evidence fields, confidence thresholds, exceptions, and approval controls.

Outcome: A forecasting protocol separating source data, assumptions, scenarios, model output, and accountable judgment.

Outcome: An evidence-backed persona separating observed signals, hypotheses, uncertainty, and validation needs.

Outcome: A source-grounded content specification with audience, channel, quality, duplication, and approval rules.

Outcome: A versioned evaluation pack with representative cases, expected outputs, scoring rules, and release thresholds.

Outcome: A risk-tiered review matrix defining triggers, evidence, approvers, correction logging, and escalation.

Outcome: A scored AI use-case assessment with an owner, success measure, and stop/go decision.

Outcome: An exportable governed-pilot brief with scope, evidence, controls, ownership, economics, and a gate decision.

Outcome: A prototype evidence report covering policy grounding, permissions, citations, abstention, escalation, and gaps.

Outcome: A prototype-readiness assessment covering representative inputs, routing accuracy, review load, failure cases, and production gaps.

Outcome: A prototype evidence report covering field accuracy, source evidence, exceptions, review load, and production gaps.

Outcome: A justified model-family decision for one business problem.

Outcome: A hostable-model shortlist assessed for task fit, license, hardware, security, evaluation, and support.

Outcome: A current-state process map with inputs, decisions, exceptions, owners, baseline metrics, and automation candidates.

Outcome: A reusable prompt specification with inputs, constraints, output schema, and review criteria.

Outcome: A method-choice record explaining the selected pattern, rejected alternatives, evidence needed, and review boundary.

Outcome: A retrieval-system decision specifying sources, citations, permissions, and abstention.

Outcome: A technology-choice record selecting the simplest adequate automation approach.

Outcome: An invoice exception matrix linking extraction confidence, control failures, reviewers, and payment boundaries.

Outcome: A meeting-output schema for decisions, actions, owners, deadlines, and unresolved questions.

Outcome: A system map identifying the model, context, tools, controls, and operating owner.

Outcome: A failure-mode register mapping likely errors to detection and containment controls.

Outcome: A data-routing decision matrix covering sensitivity, authorization, contracts, retention, and safer alternatives.

Outcome: An accounting use-case matrix separating suitable assistance from prohibited or controlled decisions.

Outcome: A goal-specific advanced study plan using primary papers and technical references.