Free AI Project Plan Template
An AI Project Plan covers the work stages, the task list in each stage, and who needs to do what to get to handover.
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The promise sounds easy, then real data shows up with messy history, permissions, and latency, and the “AI” turns into a fragile demo. This AI Project Plan keeps the work moving in the order it has to happen, with a 24-card board that starts at Onboarding and kickoff and ends at Handover and operations, so a release doesn’t get blocked by missing access or untested assumptions.
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- Onboarding and kickoff Cards cover the kickoff workshop, stakeholder list and success metrics, access and credentials, and scope and rollout approach.
- Discovery and data inventory Cards track source systems and data flows, sample extracts, business definitions and KPIs, and data quality gaps to close.
- Architecture and design Cards capture the target data model, ingestion and pipeline patterns, platform and tooling choices, and the security and access model.
- Build and iterate Cards cover ingestion pipelines, transformations and warehouse models, training and deployment pipelines, plus LLM connectors and RAG flows.
- Validation and governance Cards run integration and performance tests, model evaluation and bias checks, monitoring and alerting, and governance and access controls.
Each column names a stage and the cards call out the actual checks and build steps: stakeholder and success metrics up front, a data inventory that maps sources and definitions, then architecture choices like schemas, pipelines, tooling, and a security model. The build stage covers ingestion, transformations, training and deployment pipelines, plus LLM connectors and RAG flows, and the validation stage puts testing, evaluation, monitoring, and governance before anyone treats results as production-ready... so the team sees risks early instead of after launch notes are written. The board uses Syne headings with Inter body text, with a powder-coat teal base and red-oxide accents that keep the focus on engineered delivery rather than sales copy. The columns keep the order; the dates come from you, not the template, and the cards get assigned to whoever’s doing the work, from data engineering through machine learning and business intelligence handover.
We went from spending hours on every proposal to creating fully customized ones in under 5 minutes. That's not an exaggeration - we timed it.
What is on this board
6 columns carrying 24 cards. Adding it builds the whole thing as a project in your workspace, with every column and card in place.
| Column | What is in it |
|---|---|
Onboarding and kickoff | Cards cover the kickoff workshop, stakeholder list and success metrics, system access and credentials, and the agreed scope and rollout approach.
|
Discovery and data inventory | Cards map source systems and data flows, pull sample datasets, document definitions and KPIs, and flag data quality gaps that affect results.
|
Architecture and design | Cards define the target schema, ingestion and pipeline patterns, platform and tooling options, and the security and access model.
|
Build and iterate | Cards cover ingestion and transformations, warehouse modeling, training and deployment pipelines, and the LLM connector and RAG work.
|
Validation and governance | Cards track tests, evaluation and bias checks, monitoring and alerting, and the governance and access controls needed for production.
|
Handover and operations | Cards cover runbooks and ownership, knowledge transfer, cutover and rollback planning, and the shift into ongoing operations billing.
|
What happens when you install it
- A project is created with its board, 6 columns and 24 cards already there.
- Nothing carries a due date, because a board holds the order the work runs in rather than a calendar. The dates go on once you know when the job starts.
- Every card opens as a task with its own description, assignee, dates, subtasks and files, and columns are renamed, reordered or deleted like any other.
Who it is for
Teams shipping data & ai work, including internal product groups and client delivery shops, when the project needs a board that gets from discovery to operations without skipping governance.
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Questions about this project template
What do you need from us in week one to get moving?
The first column covers kickoff scheduling, agreeing success metrics, gathering stakeholders, and getting system access and credentials. The board doesn’t set dates, so the team adds timing and assigns owners as part of kickoff.
Are we rebuilding our whole stack, or can you work with what we have?
The plan includes an architecture and design stage that records platform and tooling options alongside ingestion, pipeline patterns, and the target schema. The project can capture decisions that keep existing systems where they make sense and change only what blocks delivery.
How do you stop an LLM from making things up with our data?
The build stage includes RAG flows and LLM connectors, and the validation stage includes evaluation and bias checks plus monitoring and alerting. That combination pushes hallucination and reliability concerns into testable work instead of a slide-deck promise.
What happens before anyone trusts results in production?
Validation and governance covers integration and performance tests, model evaluation, monitoring, and access controls. The column sits before handover, so testing and governance don’t get treated as optional clean-up.
Who owns the pipelines and models after the project ends?
Handover and operations includes runbooks and ownership plus knowledge transfer sessions. The last cards cover cutover and rollback planning and the transition into ongoing operations billing.
How many stages are in the project plan?
The board has six columns: onboarding and kickoff, discovery and data inventory, architecture and design, build and iterate, validation and governance, and handover and operations. Each column contains cards that spell out the work for that stage.
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