METHODOLOGY // 01
THE DIRECT IMPACT LEARNING METHOD
AI training methodology designed to change what people do at work.
Our AI training methodology goes beyond explaining technology. It helps people understand the concept, see it applied, practise it themselves, and connect the learning to their everyday work.
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FROM CURIOSITY TO CAPABILITY
Understanding AI is only the starting point.
Direct Impact Learning is built around a simple principle: people develop capability by doing. Training combines clear explanation, realistic demonstration, hands-on practice, workplace application, and professional judgment.
01
PRACTICAL
Use concrete examples, useful techniques, and realistic workplace activities rather than abstract demonstrations.
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02
BUSINESS FOCUSED
Connect learning to the quality, speed, communication, decision-making, productivity, and client impact of real work.
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03
BUILT FOR APPLICATION
Give participants opportunities to test, refine, evaluate, and apply what they learn during the training itself.
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A REPEATABLE LEARNING FLOW
Our AI training methodology: from concept to workplace application.
Each learning experience follows a consistent progression so participants understand why a skill matters, learn how it works, practise it, and connect it to their own responsibilities.
01
FRAME
Establish why the topic matters and connect it to a recognizable workplace challenge or opportunity.
02
EXPLAIN
Make the concept understandable in plain business language without unnecessary technical complexity.
03
DEMONSTRATE
Show the approach in action using realistic workplace examples and tasks.
04
PRACTICE
Participants use the approach themselves, compare results, refine their technique, and learn from the process.
05
APPLY
Connect the learning to the participant’s real work, responsibilities, tools, and decisions.
06
COMMIT
Identify a practical next action participants can use after the session to continue building capability.
WORKPLACE RELEVANCE
Learn with the kind of work waiting back at your desk.
Workplace AI capability becomes meaningful when employees can connect the technology to tasks they already understand. Training is therefore built around recognizable business activities rather than artificial exercises.
COMMUNICATION
Emails, summaries, reports, explanations, stakeholder messaging, and everyday business writing.
Workplace Application: Apply AI to everyday writing, messaging, and communication tasks.
RESEARCH AND INFORMATION
Organizing information, reviewing documents, summarizing material, exploring questions, and preparing for meetings or decisions.
Workplace Application: Use AI to organize, review, summarize, and prepare information for action.
ANALYSIS AND PROBLEM-SOLVING
Comparing options, identifying patterns, challenging assumptions, structuring problems, and exploring possible approaches.
Workplace Application: Use AI to compare options, surface patterns, and structure better decisions.
ROLE-BASED WORK
Adapt examples to the responsibilities of teams such as leadership, sales, business development, administration, and professional services.
Workplace Application: Apply AI to the real responsibilities, workflows, and priorities of each team.
RESPONSIBLE APPLICATION
Less watching. More doing.
Participants should spend meaningful time working with AI during training. Practice helps employees understand how small changes in context, instructions, constraints, examples, and evaluation can materially change the usefulness of an AI-generated result.
01
TRY
Use AI to complete a realistic workplace task.
Hands-on execution with real task context and workplace scenarios.
Active Execution
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02
COMPARE
Examine different approaches and identify what makes one result more useful than another.
Evaluate clarity, completeness, tone, accuracy, and operational value.
Critical Evaluation
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03
REFINE
Improve the instructions, context, evaluation, and human judgment applied to the task.
Hands-on execution with real task context and workplace scenarios.
Iterative Mastery
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RESPONSIBLE APPLICATION
Capability without judgment is not enough.
Responsible AI use is incorporated into the learning process rather than treated as an afterthought. Participants are encouraged to think critically about what information they provide to AI, what outputs require verification, when human expertise is necessary, and how organizational policies should guide use.
PRIVACY AND CONFIDENTIALITY
Consider whether information is appropriate to provide to an AI tool.
ACCURACY AND VERIFICATION
Recognize when outputs require checking before they are relied upon.
HUMAN OVERSIGHT
Keep professional judgment and accountability with the person using the technology.
ORGANIZATIONAL POLICY
Use AI within the tools, policies, and expectations established by the organization.
CONSISTENT METHOD. RELEVANT CONTEXT.
The method stays consistent. The examples change.
Our AI training methodology stays consistent across programs. Examples, tools, exercises, and complexity can be adapted to the audience and the work they perform.
AUDIENCE
Adapt examples to the roles and responsibilities of the people in the room.
EXPERIENCE LEVEL
From employees beginning to use workplace AI through to teams developing more advanced application skills.
APPROVED TOOLS
Training can reflect the AI environment available to the organization, including Microsoft Copilot and other approved enterprise AI platforms.
WORKPLACE CONTEXT
Examples and activities can reflect the types of tasks and decisions participants regularly encounter.
PRACTICAL AI TRAINING
Move your people from curiosity to capability.
Tell us about your team, the tools they use, and the work you want them to perform more effectively. We can start with a practical conversation about the right training approach.