AI Training for Organizations
Training built on your actual work.
Generic AI training teaches people prompts they forget by Friday. This is built around one real workflow from your own organization, so the thing your team practises on is the thing they go back to work and do.
One real workflow rebuilt
Not a demo. An actual process your team uses, running on AI by the end of the program.
Documentation your team maintains
SOPs, monitoring checklists, and an update schedule built as part of the training.
Skills to build the next one
Your team identifies, builds, and manages future workflows without depending on us.
What your team actually learns
Three skill areas. Each one builds on the last. You practice on your own workflows, not invented case studies.
How to identify automation opportunities
Not every process should be automated. Learn to spot workflows where AI saves significant time vs. workflows where manual work is faster.
Ranked automation backlog- Map current workflows and find bottlenecks
- Calculate time savings vs. implementation effort
- Prioritize based on ROI and risk
- Avoid automating broken processes
How to build AI-powered workflows
We rebuild one of your actual workflows together. Proposal generation, data entry, research summarization, report creation: whatever costs you the most time.
Working prototype: 5-15 hrs/week saved- Design the workflow steps (input, process, output)
- Build prompts that produce consistent results
- Connect AI to your existing tools (CRM, spreadsheets, databases)
- Test for accuracy and handle edge cases
How to manage AI systems over time
AI workflows need maintenance. Learn to monitor quality, update prompts when business needs change, and handle errors without breaking everything.
Operations playbook + monitoring checklist- Set up quality monitoring (spot-check outputs)
- Define who approves changes to AI workflows
- Document processes so new team members can maintain them
- Handle data privacy and compliance requirements
Choose your entry point
The three programs serve different stages. New to AI: start with Foundations. Ready to build: go straight to the Lab. Already running workflows that need fixing: enter at Operations Practice.
For executives and managers who need to evaluate AI projects, set policies, and build adoption roadmaps before any building starts.
- How to evaluate AI vendor claims and ROI projections
- Define who approves AI tool purchases and monitors outputs
- Create policies for data privacy, AI usage, and error handling
- Build a 90-day AI adoption roadmap for your organization
Pick one workflow: sales pipeline, customer onboarding, report generation. We rebuild it with AI automation while training your team to maintain it.
- Week 1-2: Map current workflow + design AI-powered version
- Week 3-5: Build prototype with your team (hands-on)
- Week 6-7: Test with real data, refine based on results
- Week 8: Training on maintenance + handoff
For teams that already have AI workflows running. Learn to monitor quality, update systems, and maintain compliance as your business changes.
- Set up monitoring systems (track output quality over time)
- Update prompts and workflows when business needs change
- Handle errors and edge cases systematically
- Maintain compliance with data privacy regulations
How this works
Discovery Call (20 minutes)
We discuss your business workflows, identify automation opportunities, and determine which program fits your needs. We'll draft a training plan within 48 hours.
Custom Program Design
We build a training plan specific to your workflows and tools. Actual automation of your processes using your data. Not generic ChatGPT tips.
Hands-On Training Delivery
Mix of workshops (learn concepts), working sessions (build together), and coaching (refine and troubleshoot). Your team works on real workflows throughout.
Working Prototype and Handoff
You leave with a functional AI workflow, documentation to maintain it, and the knowledge to build more on your own.
What teams have built
Examples from client engagements across industries. Results vary based on workflow complexity, team size, and implementation quality.
Sales Team
Time saved on proposal generation. From 4 hours to 30 minutes of review per proposal.
Finance Team
Monthly reporting accelerated. 16 hours of manual Excel work reduced to 2 hours.
Support Team
Ticket capacity increase. 60% of common requests now handled automatically.
Marketing Team
Research time cut. Weekly competitive reports: 8 hours down to 1 hour.
Operations Team
Onboarding time saved. Lead form to CRM to welcome email: 2 hours reduced to 10 minutes.
HR Team
Screening time reduced. 6 hours of initial review per role cut to 45 minutes.
Is this right for you?
Good fit if:
- You have at least one workflow taking 10+ hours per week
- You want your team to own and maintain AI systems
- You're ready to invest 6-10 weeks in implementation
- You want working solutions, not theoretical frameworks
Not right if:
- You want us to build and run everything for you
- You're looking for quick ChatGPT tips and tricks
- You're just exploring AI possibilities without commitment
- You need immediate results (training takes time)