Workflow template for Tallyfy

AI Employee Training Program

This template walks your team through a structured AI training program - from gauging where everyone's starting from to setting up ongoing learning and mentorship. You'll cover foundational concepts, hands-on practice, and knowledge checks so your people feel confident using AI in their day-to-day work.

11 steps

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Information Technology Human Resources AI training

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Process steps

Assess current AI skill levels

1 day from previous step

task

Find out where your team members are starting from. Run a short survey or quick 1-on-1s to understand who has hands-on AI experience, who has only read about it, and who has never used it at all. You'll use these results to group people into learning tracks.

Define learning objectives by role

1 day from previous step

task

Not everyone on your team needs to learn the same AI skills. In this step, you'll map out what each role actually needs - marketers need prompt writing, analysts need AI for data tasks, and managers need to know how to review AI-generated outputs.

Select training materials and platforms

1 day from previous step

task

Pick the courses, videos, and practice environments that match your team's learning objectives. You'll want a mix of self-paced content for foundational concepts and live or interactive content for tool-specific practice. Document your selections so everyone knows where to go.

Schedule training sessions

1 day from previous step

task

Block calendar time for each training track. Spread sessions out so your team isn't overloaded - a few hours per week tends to work better than a full-day marathon. Share the schedule with participants well in advance and include any pre-reading or prep they need to do.

Deliver foundational AI concepts

1 day from previous step

task

Cover the basics: what AI is, how it works at a high level, what it's good at, and where it falls short. Your team doesn't need to be engineers - they just need enough context to use AI tools with good judgment. Keep it practical and use real examples from your industry.

Hands-on tool-specific workshops

1 day from previous step

task

Get your team working directly with the AI tools they'll use on the job. Walk through the interface together, demonstrate common tasks, and then let participants try it themselves. Pair people up so they can help each other when they get stuck.

Practice with real work scenarios

1 day from previous step

task

Give your team actual work tasks to complete using AI tools. Pull examples from your team's real workload - draft a report, summarize a document, write a job description. This is where people start building confidence and discovering which tasks AI actually helps with.

Test knowledge retention

1 day from previous step

task

Run a short quiz or practical assessment to see how much has stuck. This doesn't have to be formal - a short written task or a quick group discussion works well. The goal is to find out where your team still has gaps so you can address them before moving on.

Collect participant feedback

1 day from previous step

task

Ask your team what worked and what didn't. A short anonymous survey gets you more honest answers than a verbal debrief. Focus on: which parts were most useful, what was confusing, and what they'd change. Use this to improve the program for future cohorts.

Create ongoing learning resources

1 day from previous step

task

Build a shared library your team can return to - prompt templates, short how-to guides, a channel or wiki for tips, and a list of recommended external resources. AI tools change fast, so you want a way for your team to keep learning without starting from scratch each time.

Set up mentorship pairings

1 day from previous step

task

Pair up team members who are more confident with AI with those who are still getting started. Even 30 minutes a week of informal coaching makes a big difference. Document the pairings, set a check-in schedule, and give mentors a short guide on how to help without just doing it for their partner.