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AI TRAINING: Cultivate AI Competencies

Use AI Safely, Confidently

Orchard’s AI training programs equip teams with the knowledge, skills and judgement needed to extract value from AI tools while managing risk responsibly.

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AI tools are only valuable and safe if your team has the ability to use them effectively and responsibly.

Without proper training, AI investments deliver disappointing results — tools sit unused, staff revert to familiar workflows, outputs contain undetected errors and traps, privacy violations abound, and leadership starts asking whether AI was worth the investment.

Most organizations approach AI training inadequately — offering brief vendor demos or optional lunch-and-learn sessions, or simply expecting staff to “figure it out” independently.

The consequences:

Low Adoption: Staff don’t use AI tools because they don’t understand AI’s value or how to apply it to their work

Poor Quality Outputs: Users accept AI-generated content without critical evaluation, allowing errors and hallucinations

Privacy Violations: Staff share sensitive information with AI tools without understanding the data protection implications

Bias Perpetuation: Users don’t recognize when AI outputs reflect or amplify bias

Misapplied AI: Tools are used for inappropriate use cases where AI shouldn’t be applied

Resistance and Cynicism: Bad early experiences create lasting resistance to AI adoption

Wasted Investment: AI tools sit idle or under-utilized because capability wasn’t built to enable them


Effective AI training prevents these failures, building capability, confidence, and responsible use practices.

Contact us for more information about our training options, or stay on this page to explore our healthy crop of AI training formats and topics!

Training Formats that Suit Your Team

  • In-Person Workshops

    Benefits: High engagement, hands-on practice, immediate Q&A, relationship building
    Format: Half-day or full-day sessions, interactive exercises,
    small groups (12-20 participants ideal)
    Best for: Major AI rollouts, complex tools, fostering organizational buy-in.

    Request In-Person Workshop

  • Virtual Workshops

    Benefits: Geographic flexibility, lower cost, convenient scheduling
    Format: 2-4 hour sessions (shorter than in-person to maintain engagement), interactive tools (polls, breakouts, chat)
    Best for: Distributed teams, budget constraints, quick topic coverage

    Request Virtual Workshop

  • Hybrid Delivery

    Benefits: Combines in-person and virtual benefits
    Format: Core training in-person, virtual follow-up sessions,
    ongoing support through virtual office hours
    Best for: Large organizations, multi-location teams

    Request Hybrid Training

  • Self-Paced Learning

    Benefits: Flexibility, learn at own pace, reference materials
    Format: Video modules, interactive exercises, knowledge checks, supplemented with live Q&A sessions
    Best for: Ongoing onboarding, refresher training, geographically dispersed teams

    Request Self-Paced Learning

  • Custom Training

    Training designed to match to your organizational culture,
    geographic distribution, budget, and timeline.

    Request Custom Training

AI TRAINING SERVICES: Five Branches of AI Training Excellence

AI Literacy

AI Fundamentals

  • What is AI? (demystifying terminology — machine learning, generative AI, large language models)
  • How AI makes decisions (understanding pattern recognition, not magic)
  • AI capabilities (what AI does well)
  • AI limitations (what AI cannot do reliably, common failure modes)
  • The evolution of AI tools (why AI has improved so dramatically, and what’s coming next)

Critical Evaluation Skills

  • Recognizing AI hallucinations (confident but incorrect statements)
  • Detecting bias in AI outputs (fairness across demographics, perspectives)
  • Fact-checking AI-generated content (verifying claims, checking sources)
  • Assessing AI confidence (when to trust outputs vs. verify independently)
  • Understanding uncertainty (AI doesn’t “know” things the way humans do)

AI Literacy for All

Everyone in your organization should understand AI basics — not to become AI experts, but to make informed decisions about when and how to use AI responsibly.

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Privacy and Security

  • Data handling by AI tools (what happens to information you share)
  • Canadian vs. US platforms (data sovereignty implications)
  • Sensitive information protection (what never to share with AI)
  • Organizational policies (your specific AI usage rules)
  • Regulatory considerations (personal and safety information in AI systems)

Responsible Use Principles

  • When AI use is appropriate or inappropriate
  • Human oversight requirements (when humans must approve AI inputs or review AI outputs)
  • Transparency and disclosure (when to tell others AI was used)
  • Intellectual property considerations (AI-generated content ownership)
  • Ethical considerations (fairness, transparency, accountability)

Tool-Specific Training

Hands-On Skills for Your AI Platforms

Generic AI literacy helps everyone understand fundamentals. Tool-specific training gives users hands-on skills with the AI platforms your organization has deployed.

Microsoft Copilot

  • Copilot in Word, Excel, PowerPoint, Outlook, Teams
  • Effective prompting techniques
  • Agentic development and application
  • Use cases by role (marketing, operations, analysis, administration)
  • Privacy settings and controls
  • Organizational policies for Copilot use
  • Integration with Microsoft 365 workflows

ChatGPT and Claude

  • Account setup and interface navigation
  • Prompt engineering fundamentals
  • Use case applications (research, drafting, analysis, brainstorming)
  • Advanced tools such as command-line and co-work interfaces
  • Conversation management and context
  • Fact-checking outputs
  • Privacy considerations (what not to share)
  • Organizational usage policies

Google Gemini

  • Workspace integration (Docs, Sheets, Gmail)
  • Multimodal capabilities (text, images, data)
  • Effective prompting for different use cases
  • Advanced features and interfaces
  • Privacy and data handling
  • Organizational policies

Workflow Automation Tools

  • Common tools such as Power Automate, Zapier, and Make
  • Workflow design principles
  • Common automation patterns
  • Testing and troubleshooting
  • When to automate vs. keep and enhance manual processes

Sector-Specific AI Tools

  • Industry-tailored platforms
  • Regulatory compliance considerations
  • Best practices for your sector

Training Format

  • Hands-on workshops (participants use tools during training)
  • Role-specific training (marketing, operations, analysis, administration)
  • Use case libraries (examples relevant to participant roles)
  • Practice exercises and coaching
  • Quick reference guides and job aids
  • Post-training support period

Responsible Use Policies and Guidelines

AI training must include your organizational policies — what’s appropriate, what’s prohibited, privacy requirements, and disclosure obligations.

Appropriate vs. Inappropriate Use Cases

  • When to use AI (suitable applications)
  • When not to use AI (human judgement required, high-stakes decisions, sensitive topics)
  • Grey areas requiring approval or consultation
  • Examples and case studies

Confidentiality and Data Protection

  • What information never to share with AI tools (confidential, proprietary, sensitive, controlled, personal)
  • Canadian data sovereignty considerations (US vs. Canadian or international platforms)
  • Client information protection (contractual obligations, professional duties)
  • Regulatory compliance (PIPEDA, sector-specific requirements)

Intellectual Property

  • Ownership of AI-generated content
  • Copyright considerations (AI training on copyrighted material)
  • Attribution requirements (when to disclose AI use)
  • Client deliverables (disclosure policies for AI-assisted work)

Establish Guardrails for AI

A well-trained team protects your organization from AI risk and helps manage compliance.

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Human Oversight Requirements

  • When human review is mandatory (high-consequence decisions, client-facing content, regulatory submissions, irreversible decisions)
  • Review depth expectations (quick scan vs. thorough verification)
  • Accountability (who’s responsible for AI-assisted work)

Disclosure and Transparency

  • When to disclose AI use (client deliverables, stakeholder communications, decisions affecting people)
  • How to disclose (transparency without undermining confidence)
  • When disclosure not required (internal drafting, research assistance)

Prompt Engineering and Advanced Techniques

Extract Maximum Value from Generative AI

Generative AI quality depends heavily on prompt quality. Well-crafted prompts produce better outputs. Poor prompts waste time and produce unusable results.

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Training Format

  • Hands-on workshops (participants use tools during training)
  • Role-specific training (marketing, operations, analysis, administration)
  • Use case libraries (examples relevant to participant roles)
  • Practice exercises and coaching
  • Quick reference guides and job aids
  • Post-training support period

RELATED SERVICES

AI Implementation: Training is essential component of AI implementation—we provide integrated deployment and training services.
AI Implementation Services →

AI Readiness: Training needs identified during readiness assessment inform training program design.
AI Readiness Assessment →

Cyber Safety Training for SMEs: Privacy and security topics overlap between AI training and cyber safety training.
Cyber Safety Training →

Change Management: AI adoption is organizational change—we provide change management expertise.
Change Management Support →