01
Writing and planning
Explore ways to draft, restructure, or organize material while keeping a person responsible for the final work.
DAGZER / AI TRAINING
AI for Teams: A Practical Productivity Workshop
A productivity-focused workshop that uses relevant team tasks to explore helpful AI habits, safe boundaries, and shared ways of working.
Help a team explore practical AI-assisted ways of working, practice reviewing outputs, and discuss where human expertise remains essential.
Looking for another format? Explore all AI training.
Learning path / illustrative
AI for Teams
01
Understand
Build a clear foundation
02
Practice
Explore a relevant task
03
Review
Use human judgment
Learning outline is tailored to the audience and confirmed scope
WHO IT’S FOR
Teams who want practical, collaborative learning around AI and everyday productivity.
FORMAT
Productivity workshop
DURATION
Duration: to be confirmed
Learning outcomes
Useful learning, with clear expectations.
The final learning objectives are confirmed with DAGZER for the audience, tools, and agreed session scope.
- Practice task-focused prompting
- Review generated output before use
- Identify team-specific opportunities and guardrails
01 / TEAM TASKS
Start from work people already do.
Select realistic, low-risk examples that make the practice relevant. Specific exercises are chosen with the team and should not use sensitive information unless approved.
02
Research and synthesis
Practice summarizing supplied information and checking claims against original sources.
03
Ideas and preparation
Use AI to explore options or prepare an outline, then apply team expertise and context.
02 / PRACTICE TOGETHER
Build habits for better AI-assisted work.
Participants try a repeatable approach: give context, specify the task, review the result, and refine or verify before using it.
01
Prompt with purpose
Describe the intended outcome, audience, context, and format.
02
Iterate
Use follow-up questions to improve clarity and usefulness.
03
Verify
Check important facts, assumptions, tone, and completeness before sharing.
03 / TEAM AGREEMENTS
Make room for responsible, consistent use.
A team workshop can help surface questions and possible working agreements. Organizational policy decisions remain with the organization.
01
Information boundaries
Use only tools and data-sharing practices permitted by organizational guidance.
02
Human accountability
Decide who reviews and owns work that has been AI-assisted.
03
Shared opportunities
Capture promising tasks and identify who should assess them further.
How the learning flows
A guided path from introduction to reflection.
This is a learning outline, not a fixed agenda. Order, timing, exercises, and materials are confirmed for the final session.
- STEP 01
Choose useful tasks
Agree team goals and suitable learning examples.
- STEP 02
Learn the pattern
Introduce prompting, iteration, review, and verification.
- STEP 03
Practice in context
Try guided exercises matched to the team’s work.
- STEP 04
Share & reflect
Discuss boundaries, lessons, and possible next steps.
Format & investment
Tailored to the people taking part.
Audience, tools, access requirements, preparation, group size, and final agenda should be agreed before the session.
Pricing: Custom quote
For sessions where duration or tool requirements are not listed above, DAGZER will confirm those details during scoping.
Before you enquire
Training questions.
Need to confirm a detail for your group? Ask DAGZER about this session.
Can the workshop focus on our team’s work?
The offering is described as a productivity workshop for teams. Exercises can be discussed during scoping, subject to available time and approval to use the selected examples.
Which AI tools will we use?
Specific tools are not listed. DAGZER should confirm the tools, account requirements, and any organizational approvals before training.
How long does the workshop run?
Duration is to be confirmed based on team size, learning objectives, and the selected exercises.
Will this automate our team’s tasks?
The offering is training. Any workflow design, automation build, or organizational rollout would be separately assessed and scoped.
More ways to learn
Explore other AI training.
Build Your Own AI AgentMove from agent concepts to a working learning exercise: define a focused task, configure an agent, test its behavior, and understand its limits.No-Code Automation TrainingA practical introduction to designing no-code automations around real tasks—with clear triggers, rules, testing, and ownership.Corporate AI TrainingA team-specific learning engagement shaped around your audience, roles, existing AI guidance, and the tasks employees actually do.
Plan a learning session
Tell us who’s learning and what they need.
We’ll discuss audience, objectives, tools, timing, and the right format for your group.