Turn AI into a capability your people actually use.
Giving employees access to AI doesn’t mean they’ll know where it creates value, how to use it effectively, or how their work should change around it.
Margins trains executives, managers and employees around the AI opportunities, tools and workflows that matter to their actual roles — from foundational understanding to hands-on adoption.
Built around your business. Your people. Their actual work.
Giving people AI tools doesn’t make a company AI-enabled.
- Employees can have ChatGPT.
- Microsoft Copilot can be deployed.
- An internal AI assistant can be launched.
- A custom AI system can enter production.
None of those things guarantee that people will change how they work.
- Some won’t know where AI helps.
- Some will use it poorly.
- Some will use it for things they shouldn’t.
- Some will continue working exactly as before.
- Others will develop powerful new ways of working that never spread beyond their team.
The technology can be deployed in a day. Changing how an organization works takes deliberate enablement.
The goal isn’t to teach AI. It’s to teach people how to work differently with it.
Most employees don’t need to understand transformer architecture.
They need to understand
- 01Where AI can help in their role.
- 02Which tasks are worth changing.
- 03How to get consistently useful results.
- 04What information should and shouldn’t be shared.
- 05When AI can be trusted.
- 06When human judgment is still required.
- 07How AI fits into existing processes.
- 08How to recognize new opportunities.
The objective isn’t AI literacy for its own sake. It’s better work because AI is available.
One AI course for the entire company doesn’t make sense.
What a CEO needs from AI is different from what a salesperson, operations manager or finance employee needs. Training is designed around roles and responsibilities.
Understand what AI changes.
Executives don’t need prompt-engineering courses. They need enough understanding to make better decisions about where AI matters.
- AI capabilities and limitations
- Where AI creates business value
- Identifying meaningful opportunities
- AI economics
- Build vs buy
- Data and ownership
- Risk and governance
- How AI changes operating models
- Evaluating AI investments
Redesign work around new capabilities.
Managers sit between strategy and execution. They need to understand how AI changes processes, roles and team performance.
- Identifying AI opportunities inside a process
- Breaking work into AI + human components
- Designing human-in-the-loop workflows
- Measuring productivity gains
- Managing adoption
- Recognizing failure modes
- Creating new operating procedures
Use AI effectively in everyday work.
Employees need practical skills tied directly to their responsibilities.
- Effective AI interaction
- Company-approved AI tools
- Research and analysis
- Document work
- Communication
- Data interpretation
- Workflow automation
- Verification and judgment
- Role-specific use cases
Build capability inside the organization.
Some employees naturally become advanced users. We help develop them into internal AI champions who support adoption and identify additional opportunities across the business.
- Advanced use
- Peer support
- Opportunity spotting
- Internal enablement
Your employees don’t work in generic examples. Neither should their training.
Generic AI trainingSummarize a fictional document.
When people recognize their own work in the training, AI stops being abstract.
- Preparing for customer visits.
- Analyzing purchasing patterns.
- Writing commercial communication.
- Working with product information.
- Understanding customer history.
- Creating management reports.
- Processing documents.
- Investigating discrepancies.
- Preparing client communication.
- Analyzing financial information.
- Working across policies and regulations.
- Planning.
- Exception management.
- Customer communication.
- Operational reporting.
- Analyzing delivery information.
Training can reveal AI opportunities engineering never sees from the boardroom.
Employees know where the friction is. So training shouldn’t only transfer knowledge — it should create a mechanism for capturing opportunities.
- 01Which report takes four hours every Friday.
- 02Which spreadsheet gets copied between three systems.
- 03Which customer question requires searching through six documents.
- 04Which decision depends on one experienced employee.
- 05Which repetitive task everyone hates.
- 01Learn
- 02Apply
- 03Identify friction
- 04Discover AI opportunity
- 05Validate
- 06Implement
- 07New way of working
Every trained employee can become another sensor for where AI could create value.
The system isn’t implemented until people know how to work with it.
That’s why training is part of our implementation lifecycle.
- What the prediction means.
- How confident it is.
- What action they should take.
- When they should ignore it.
- What feedback the system needs.
- What it can do.
- What it can’t do.
- When to delegate work.
- When to verify it.
- When to intervene.
- Where responsibility remains with them.
- 01Build
- 02Deploy
- 03Train
- 04Adopt
- 05Operate
- 06Improve
Deployment puts AI into the company. Training puts it into the workflow.
Knowing what to do and actually doing it are different problems.
Training creates understanding. Adoption changes behaviour. That’s why our work can continue beyond the training session.
Train
Understand the capability.
Practice
Use it against real work.
Apply
Introduce it into everyday workflows.
Support
Help users when reality creates questions.
Measure
Understand whether people are actually using it.
Improve
Adjust the system, workflow or training based on what we learn.
Training is an event. Enablement is a process.
From AI fundamentals to role-specific application.
The actual program is configured around your organization — not sold as a catalogue.
AI Fundamentals
Understand what modern AI can and cannot do and where different technologies fit.
Practical Generative AI
Use language models effectively for everyday knowledge work.
Role-Specific AI
Apply AI directly to sales, operations, finance, management and other functions.
AI for Executives
Understand AI economics, opportunities, risk and strategic implications.
AI for Managers
Redesign processes and teams around AI capabilities.
AI Tools & Workflows
Learn the approved AI systems available inside the organization.
Custom AI Systems
Train employees around AI applications specifically implemented for their business.
AI Opportunity Identification
Teach teams how to recognize work that may be suitable for automation or augmentation.
Responsible AI Use
Understand company rules, data boundaries, verification and human responsibility.
People learn AI by using it.
The most valuable part of AI training isn’t listening to someone explain AI. It’s applying it.
- 01Understand
Short, practical explanations of the capabilities and limitations that matter.
- 02See
Demonstrations based on recognizable business situations.
- 03Do
Participants work through tasks themselves.
- 04Apply
Exercises move into the participant’s actual role and workflows.
- 05Reflect
Identify where AI worked, where it didn’t and where human judgment remains necessary.
- 06Repeat
Turn useful techniques into repeatable ways of working.
Employees need to know not only what they can do with AI, but what they should do.
When employees adopt public AI tools independently, organizations can lose visibility into how company information is being used. The objective isn’t to make employees afraid of AI — it’s to give them enough understanding to use it confidently within the company’s rules.
- Company data
- Customer information
- Confidential documents
- Personal data
- Intellectual property
- AI-generated output
- Verification
- Human accountability
- Approved tools
- Escalation
ChatGPT is useful. It isn’t your AI strategy.
Public AI tools can dramatically improve individual productivity. Enterprise AI goes further.
Individual AI
Helps one employee perform a task.
Team AI
Changes how a group works.
Workflow AI
Becomes part of an operational process.
Enterprise AI
Connects proprietary data, systems, knowledge and processes across the business.
We train people to use the AI available today while preparing the organization for the AI capabilities it will build tomorrow.
Some of your most valuable knowledge lives inside your people.
Experienced employees know things that aren’t documented anywhere — and that knowledge can disappear when someone changes role or leaves. Capta helps capture expertise and convert it into structured organizational knowledge that the business, and its AI systems, can use.
Training helps people work with AI. Capta helps AI learn from your people.
Explore CaptaBuilt around your organization.
A typical structure — not a two-hour workshop. Packages are configured per organization.
- 01
Understand
Assess AI maturity, existing tools, policies, roles and business objectives.
- 02
Segment
Identify what different groups actually need to know.
- 03
Design
Build role-specific training around relevant tools, workflows and use cases.
- 04
Train
Deliver practical sessions with hands-on exercises.
- 05
Apply
Participants use AI against real work and workflows.
- 06
Capture
Identify recurring questions, friction and new AI opportunities.
- 07
Enable
Support champions, managers and teams as new ways of working take hold.
- 08
Measure
Understand adoption and where additional enablement is required.
A completed training session isn’t the outcome.
Attendance is easy to measure. Transformation isn’t. Depending on the program, useful signals could include:
Are employees actually using the approved AI capabilities?
Has AI become part of recurring work?
Are employees applying it to valuable tasks?
Is measurable work being eliminated or accelerated?
Are employees producing better outcomes?
Do people know when and how AI should be used?
Are teams identifying additional high-value applications?
The objective is changed behaviour and better work — not certificates.
Technology changes the capability. People change the company.
Margins combines AI Strategy, Engineering, Training, Forward Deployed Engineering and Managed AI so technology and organizational adoption don’t become separate initiatives owned by disconnected partners.
- Strategy
- Data
- AI systems
- Integrations
- Infrastructure
- Operations
- Understanding
- Skills
- Adoption
- Judgment
- New workflows
- New behaviours
Different roles. Different responsibilities. Different training.
- 01Executives
Strategic understanding and investment decisions.
- 02Managers
Process redesign and adoption.
- 03Knowledge Workers
Everyday AI productivity.
- 04Operational Teams
AI-enabled workflows.
- 05AI Champions
Internal enablement and opportunity discovery.
- 06Technical Teams
Working effectively with enterprise AI systems.
Training from people who actually implement AI.
Practitioners, not trainers alone
Our perspective comes from designing and deploying real AI systems.
Business-specific
Programs are built around the customer’s roles, processes and opportunities.
Connected to implementation
We can train employees around the actual AI systems entering their workflows.
Technical depth
Questions don’t stop when the conversation moves beyond ChatGPT.
Opportunity discovery
Training can surface additional opportunities for automation and AI implementation.
End-to-end capability
When a valuable opportunity is discovered, Margins can take it from idea through engineering and into production.
Related capabilities
AI Transformation
Build AI into the way the organization operates.
Explore AI Transformation →AI Discovery Sprint
Identify where AI can create meaningful value across your business.
Explore AI Discovery →Capta
Turn employee expertise into organizational intelligence your company owns.
Explore Capta →Forward Deployed Engineering
Keep technical expertise close to users as new AI workflows meet reality.
Explore FDE →
What could your people do differently with AI?
We’ll help you identify what different parts of the organization need from AI, design training around their actual work, and turn new capabilities into everyday ways of working.
Discuss AI trainingDon’t train people on AI in the abstract. Train them for the work they’ll do with it.