Faysal Aziz
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Training

GenAI for Productivity

AI

GenAI for Productivity

Learn to work faster, think sharper, and use AI like a capable business partner in day

Generative AI has moved beyond novelty. Teams now use tools like ChatGPT, Claude, Gemini, Microsoft Copilot, AI agents, deep research, data analysis, and connected workplace assistants to draft, analyse, automate, summarise, brainstorm, and support decision-making. Anthropic’s Claude now plays a major enterprise role, including Claude Opus 4.8 for professional and agentic work and Claude’s growing workplace integrations such as Slack-based collaboration. OpenAI’s ChatGPT Enterprise also now includes agents, deep research, data analysis, file uploads, projects, and enterprise controls.

This 1-day course is designed for practical business users, managers, analysts, executives, and professionals who want hands-on, modern AI skills without turning the session into an academic lecture. The instructor has over 30 years of industry experience and will use real industry-demanded content, practical workflows, and workplace-ready methods.

Learning Outcomes

By the end of this course, participants will be able to:

  • Understand how modern generative AI tools fit into daily business work
  • Use ChatGPT, Claude, Gemini, and Copilot more effectively
  • Write better prompts for business, analysis, communication, and decision support
  • Compare when to use ChatGPT versus Claude
  • Use AI for documents, emails, reports, meetings, research, and ideation
  • Understand AI agents, RAG, MCP, and connected workplace tools at a practical level
  • Apply responsible AI practices for privacy, accuracy, and governance

Prerequisites

  • Basic computer and internet skills
  • Familiarity with office productivity tools
  • No programming knowledge required
  • Access to at least one AI tool such as ChatGPT, Claude, Gemini, or Copilot is recommended

Training Outline

  1. Introduction to Generative AI for Modern Work
    1. What generative AI can realistically do today
    2. How business teams are using AI in 2026
    3. LLMs, multimodal AI, AI assistants, and AI agents
    4. Productivity versus automation versus augmentation
    5. Common misconceptions and practical limitations
  2. Modern AI Tools Landscape
    1. ChatGPT and ChatGPT Enterprise
      1. GPT-5.5 capabilities
      2. Deep research
      3. Data analysis
      4. File uploads
      5. Projects and workspace agents
      6. Enterprise security and admin controls
    2. Anthropic Claude
      1. Claude Opus 4.8
      2. Claude for professional work
      3. Claude for long-context analysis
      4. Claude for writing, summarisation, reasoning, and coding support
      5. Claude Tag and workplace collaboration
      6. Claude Enterprise and Team use cases
    3. Google Gemini
      1. Workspace productivity use cases
      2. Research and summarisation workflows
      3. Multimodal interaction
    4. Microsoft Copilot
      1. Microsoft 365 productivity workflows
      2. Word, Excel, PowerPoint, Outlook, and Teams scenarios
      3. Business user adoption considerations
    5. Choosing the Right AI Tool
      1. ChatGPT versus Claude
      2. Claude versus Gemini
      3. Copilot versus standalone AI assistants
      4. Tool selection by business task
      5. Cost, privacy, accuracy, and usability considerations
  3. Prompt Engineering for Business Users
    1. Prompting fundamentals
      1. Role
      2. Task
      3. Context
      4. Format
      5. Constraints
      6. Examples
      7. Evaluation criteria
    2. Prompting for better outputs
      1. Clear instruction design
      2. Structured response formats
      3. Iterative refinement
      4. Tone and audience control
      5. Asking for assumptions and limitations
      6. Reducing vague and generic responses
    3. Business prompt patterns
      1. Executive summaries
      2. Email drafting
      3. Proposal support
      4. Meeting preparation
      5. Report writing
      6. Policy drafting
      7. Customer response drafting
      8. Brainstorming and ideation
      9. Decision comparison
      10. Risk identification
  4. Using AI for Workplace Productivity
    1. Writing and communication
      1. Professional emails
      2. Reports and memos
      3. Presentations
      4. Meeting notes
      5. Minutes of meeting
      6. Executive updates
      7. Customer-facing communication
    2. Research and analysis
      1. Topic exploration
      2. Market scanning
      3. Competitor review
      4. Document summarisation
      5. Long-document analysis
      6. Source checking
      7. Insight extraction
    3. Data and spreadsheet support
      1. Data cleaning concepts
      2. Formula assistance
      3. Trend interpretation
      4. Chart explanation
      5. KPI analysis
      6. Management reporting
    4. Creative and strategic work
      1. Campaign ideas
      2. Product positioning
      3. Training content
      4. Internal communication
      5. Scenario planning
      6. Problem framing
  5. Claude in the Business Workflow
    1. Where Claude performs especially well
      1. Long-form writing
      2. Large document review
      3. Policy and legal-style drafting support
      4. Complex reasoning
      5. Careful summarisation
      6. Natural business communication
    2. Claude compared with ChatGPT
      1. Writing style differences
      2. Reasoning differences
      3. File and document workflows
      4. Enterprise collaboration scenarios
      5. Practical selection guidelines
    3. Claude and modern workplace collaboration
      1. Claude in Slack
      2. Team-based AI interaction
      3. Context-aware workplace assistance
      4. Task tracking and summarisation
      5. Enterprise access controls
  6. AI Agents and Automation Concepts
    1. Understanding AI agents
      1. Assistant versus agent
      2. Task delegation
      3. Tool use
      4. Multi-step workflows
      5. Human approval points
    2. Practical agent use cases
      1. Research agent
      2. Report preparation agent
      3. Meeting follow-up agent
      4. Customer support assistant
      5. Data analysis assistant
      6. Internal knowledge assistant
    3. Model Context Protocol and connected AI
      1. What MCP is
      2. Why tool connectivity matters
      3. AI access to business systems
      4. Secure data connections
      5. Enterprise integration considerations
  7. Responsible and Safe AI Usage
    1. Accuracy and verification
      1. Hallucinations
      2. Fact-checking
      3. Source validation
      4. Human review
      5. Confidence checking
    2. Privacy and confidentiality
      1. Sensitive data handling
      2. Customer data
      3. Internal documents
      4. Enterprise policy alignment
      5. Data leakage risks
    3. Governance and compliance
      1. Acceptable use policies
      2. Approval workflows
      3. Auditability
      4. Bias and fairness
      5. Copyright awareness
      6. Risk management
  8. Practical AI Adoption Roadmap
    1. Identifying high-value use cases
    2. Selecting quick wins
    3. Building prompt libraries
    4. Creating team AI guidelines
    5. Measuring productivity impact
    6. Encouraging responsible adoption
    7. Moving from experimentation to daily workflow

Disclaimer

This training outline is intended as a professional guideline only. The trainer may amend, restructure, expand, reduce, or replace any topic, activity, sequence, or emphasis as deemed appropriate based on participant needs, organisational requirements, available tools, time constraints, and industry developments, without prior notice.

Practical, connected learning

My wider training approach brings hands-on implementation and systems thinking together, connecting technology with real operational needs.

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