Kyle Branchesi Email

Work / AI curriculum and use guide

When to use AI, task by task

AI training is really about helping people make good calls on when to use it. At United Way Worldwide, staff had AI tools before there was an AI policy, and every organization in the network sets its own rules. I designed a use guide that lets low-risk work go ahead fast and sends only high-stakes decisions to formal approval. The learning path starts with that guide and runs from AI basics to how AI agents work. IT and the Office of General Counsel approved the guide. See the full enablement plan.

AI curriculum and use guide, designed and built in 2026 and not yet rolled out. United Way Worldwide. Both draw on two public standards: NIST’s framework for managing AI risk, from the U.S. government, and OWASP’s security guidance for AI agents.

The use guide

The use guide

Everything in the guide comes down to two questions: what am I giving the tool, and what happens if the answer is wrong? Sort eight tasks the way the guide would, or check one of your own.

The two questions

Is this task safe to give AI? Ask two things: what am I giving the tool, and what happens if the answer is wrong? Together, the answers decide whether AI touches the task, and who has to approve it.

The use guide as a grid. Across: what you give the tool, from public to internal to personal or confidential. Up: what happens if the answer is wrong, from easy to catch to costly to fix to a decision about people or organizations. Green only for public information where a mistake is easy to catch. Red for anything personal or confidential, and for anything that feeds a decision about people or organizations. Everything else is Yellow.
A decision about people or organizations RedStop for formal approval RedStop for formal approval RedStop for formal approval
Costly to fix YellowApproved tool, named owner YellowApproved tool, named owner RedStop for formal approval
Easy to catch GreenUse it, check it YellowApproved tool, named owner RedStop for formal approval

Green

Use it, and check the result.

For example: summarize a published public report.

Yellow

Approved tool, and a named person owns the draft.

For example: draft an update from an internal plan.

Red

Stop for formal approval.

For example: rank partners for investment from their public websites. The information is public, but it feeds a decision about organizations.

Past the blue line, a task stops for formal approval.

Anything inside the line can go ahead quickly. Safe work shouldn’t sit waiting.

Being too careful counts as a failure too. The target: no more than 10% of safe tasks blocked.

One of four questions to answer before you put AI to work.

Based onThe guide sits at the center of a short AI literacy course I designed at United Way Worldwide, called AI Foundations.

Task 1 of 8

Summarize a published industry report for your team

Choose where the guide would put this task.

Right 0 of 0. Safe tasks over-restricted 0.

Where each task lands, by what you give the tool and what a wrong answer costs.

Agents

Would you deploy this agent?

An agent acts on someone’s behalf, so when an organization adopts one, the real decision is what it’s allowed to do. This one drafts the monthly update to 200 member organizations and sends it. Set its permissions, then click Run the test.

Based onThis comes from the same course, in its module on workflows and agents. Learners practice giving an agent one new permission at a time, and catching a hidden instruction someone has slipped into a document.

What the agent touches. Gray lines are permissions it doesn’t have. Blue is a person deciding.

What the agent is allowed to do

  • The job needs this
  • The job needs this

Before it launches

Test evidence: not tested yet.

What happened

    Run the test to see what this agent does with these permissions.

    Permission to draft isn’t permission to send. The test passes only when the system blocks what the job doesn’t need and a person approves what goes out.

    Course

    AI Foundations

    Most staff don’t need to build an agent. All of them have to decide, task by task, whether AI belongs in their work. This course is built around that decision, including the limits for agents that act on someone’s behalf. It opens the curriculum, and I designed it for people with no technical background.

    7 minStart with a real task
    12 minWhen a result earns trust
    12 minGreen, Yellow, Red
    9 minUse it, check it, own it
    9 minWorkflows and agents
    9 minFinal practice
    30 minOptional live clinic

    Six self-paced modules, 58 minutes in all, plus an optional live clinic.

    Six decisions I made

    1. I opened it with a piece of real work, not a definition or a product tour.
    2. I made every decision in it come back to the use guide’s two questions.
    3. I gave agents limits the system enforces, not just the wording of a prompt.
    4. I designed the activities from six skeptical perspectives, including privacy, equity and job security.
    5. No one needs an AI account to take it. Deciding not to use AI can be good judgment, and blocking safe work counts as a miss.
    6. I kept it to one core course, with an adaptation kit each independent organization can choose to use.

    Curriculum

    AI for Impact

    Every course starts from a real task and ends with a useful work product, a workflow the learner can repeat, and the judgment to see where AI improves the work and where it doesn’t belong. The path runs in four stages, from understanding AI to building assistants and agents with set limits.

    No one is meant to take every course. The path is built so that most staff would take the first course and the one for their own kind of work, managers would add the leadership course, and a smaller group would go on to redesign workflows and build assistants and agents.

    The four stages. Each one goes deeper and is meant for fewer people.

    1

    Understand

    Most staff

    For most staff: one short course built around the use guide.

    1AI FoundationsEnds with a real task placed with the use guide
    Starts from
    A task from the learner’s own week, not a definition of AI.
    The workflow
    Ask the use guide’s two questions of every task, place it Green, Yellow or Red, and check a result before trusting it.
    Format
    58 minutes, self-paced, in six modules, with an optional 30-minute live clinic.
    Where a person decides
    The learner decides whether AI belongs in the task at all.

    Try the use guide

    2

    Apply to real work

    Each function; managers add the leadership course

    Five of the six courses here are studios, one for each kind of work, and the sixth is for managers. Each one ends with a reviewed work product.

    2AI Learning Design StudioEnds with a reviewed course outline
    Starts from
    A subject expert’s notes for a short course.
    The workflow
    Set what learners must be able to do. AI drafts the outline and practice questions from the notes. The designer checks every claim against the notes, and the expert signs off at set checkpoints.
    Work product
    A reviewed outline, one practice activity, and the prompt that drafted them.
    Where a person decides
    Nothing reaches learners until the expert signs off.
    3AI Communications StudioEnds with one story in three formats
    Starts from
    An approved quarterly report.
    The workflow
    AI drafts a newsletter story, a social post and a short talk track in the house voice. A person checks every fact, figure and quote against the report and edits for tone.
    Work product
    A set ready to publish, and a voice check the team can reuse.
    Where a person decides
    Someone’s own words or story are used only with their consent, and nothing is published unreviewed.
    4AI Research and Impact StudioEnds with a sourced brief
    Starts from
    Several public reports on the same question.
    The workflow
    AI summarizes and compares the sources, citing the page for each point. A person checks every figure against its source and writes the conclusion.
    Work product
    A two-page brief where every figure traces to a source.
    Where a person decides
    Raw survey responses with names stay out of general tools, and the conclusion is a person’s call.
    5AI Fundraising StudioEnds with a reviewed update and proposal section
    Starts from
    Approved materials about the organization’s programs.
    The workflow
    AI drafts an update and a proposal section from the approved materials. A person tailors them to the reader and checks every figure and promise.
    Work product
    An update and a proposal section ready to send, and a prompt the team can reuse.
    Where a person decides
    Personal records never go into a general tool, and every promise is checked, because the organization has to keep it.
    6AI Operations StudioEnds with a tested procedure and its owner
    Starts from
    A recurring process, such as a monthly report or an intake request.
    The workflow
    AI turns rough notes into a written procedure and a checklist. A person runs the procedure once, exactly as written, to find the step the draft missed.
    Work product
    A procedure anyone on the team can run, with a named owner.
    Where a person decides
    Employee and financial records stay out, and AI never approves a payment or a decision about a person.
    7Leading Human-Centered AIEnds with a team AI agreement
    Starts from
    The manager’s own team and its work.
    The workflow
    Map where AI helps the team and where it does not, agree what stays with people, and plan how to hear concerns about workload and jobs.
    Work product
    A one-page team agreement and a date to revisit it.
    Where a person decides
    AI output is never used to judge a person’s performance.

    3

    Redesign the process

    Workflow owners

    This course is for the people who own a workflow. The earlier courses work on single tasks. This one changes the whole process.

    8Systems Thinking with AIEnds with a before-and-after workflow map
    Starts from
    One whole workflow, start to finish, with the people who do it.
    The workflow
    Map every hand-off and where work waits. Decide, step by step, whether AI, a person or a simple rule fits best. Measure the current time before changing anything.
    Work product
    A redesigned workflow with an owner for each step and a baseline to measure against.
    Where a person decides
    The people who do the work review the redesign before it changes.

    4

    Build

    AI champions

    The last two courses are for the staff who go on to build assistants and agents, with limits the system enforces.

    9Build a Useful AI AssistantEnds with a tested assistant and its owner
    Starts from
    A question the team answers again and again.
    The workflow
    Write the assistant’s instructions, limit it to approved sources, then test it with real questions and with questions meant to trip it up.
    Work product
    An assistant with a named owner, its test results and a maintenance plan.
    Where a person decides
    Finishing the course does not launch the assistant. It first needs a named owner, test evidence and a maintenance plan.
    10Responsible AI AgentsEnds with an agent design, its permissions and its tests
    Starts from
    A multi-step task, such as gathering updates and drafting a summary.
    The workflow
    Grant permissions one at a time, enforced by the system rather than requested in a prompt. Test whether a hidden instruction inside a document gets through.
    Work product
    An agent design with its permissions, a test log and an approval step.
    Where a person decides
    Every send waits for someone’s approval.

    Try the AI Foundations version of this test

    Every course follows the same six steps. The review, in blue, can send the work back.

    Try it

    Map the work

    Map the work before AI touches any of it. Part by part, learners decide what AI drafts and what stays with a person. Some parts have to change first. Either the information can’t go into a tool, or the step shouldn’t exist at all.

    Based onMapping the work is the second step in every course.

    The work

      A dashed square means AI drafts it, and it stays a proposal until a person checks it. A blue square means a person does it. A crossed square means that part has to change first.

      0 of 5 parts decided

      Rules I hold the curriculum to

      1. Finishing a course shows someone learned. It doesn’t give them permission to use a tool, upload information or launch an assistant or agent. Those are separate decisions.
      2. I made a named owner, test evidence and a maintenance plan the bar for launching any assistant or agent.
      3. In the agents course, a prompt can’t grant a permission. The system enforces each one, and nothing is sent out without human approval.
      4. I set targets only after measuring a baseline. And I don’t report time saved on drafting as organizational savings on its own, because the hours saved on drafting can pile up again in review.

      Related

      Back to all work