MA-2042: AI in Business: Tools & Techniques

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About this Course

AI Fundamentals Bootcamp prepares professionals to use generative AI as a daily working tool. The course replaces the survey-style “AI awareness” curricula of the early 2020s with a capability-first program built around the five assistants now embedded in every modern workplace: ChatGPT, Gemini, Claude, Microsoft Copilot, and Grok.

Learners practice the same task across multiple assistants to build judgment about which tool fits which job. They build their first custom assistant, configure a low-risk agent, run document and data analysis with multimodal input, and draft an AI acceptable-use policy for their team. Safety, privacy, and ethics are integrated into every module rather than reserved for a final block where they typically get cut for time.

The course is appropriate for any organization rolling out AI to non-technical staff, onboarding new employees to existing AI tools, or upskilling managers who need to direct AI-augmented teams.

Audience Profile

This course is designed for non-technical business professionals with zero to light AI exposure who need to use AI as part of their daily work. Typical roles include:

  • Business managers and team leads
  • Project coordinators and program managers
  • Marketing, sales, and customer service professionals
  • Operations, HR, and finance staff
  • Executives and assistants supporting executives
  • Any knowledge worker whose organization has rolled out Microsoft 365 Copilot, Google Gemini in Workspace, or a similar AI platform

At Course Completion

After completing this course, participants will be able to:

  • Explain in plain language what a large language model is, what it can and cannot do, and why it sometimes hallucinates.
  • Select the right assistant (ChatGPT, Gemini, Claude, Copilot, or Grok) for a given business task based on capability, data sensitivity, and licensing.
  • Write prompts that produce usable first drafts for six common business artifacts: email, summary, outline, analysis, policy, and presentation.
  • Use multimodal features — voice, image, document upload, screen sharing — for real work.
  • Build a basic custom assistant (Custom GPT, Gemini Gem, Claude Project, or Copilot Agent) for a repeating task.
  • Describe what an AI agent is, where agents fit in a workflow, and what risks they introduce.
  • Apply their organization’s AI acceptable-use policy, or draft a starter policy if none exists.
  • Recognize and respond to the top five AI risks: data leakage, hallucination, bias, prompt injection, and copyright exposure.

Outline

What AI Actually is Today

Learning Objectives

  • Define generative AI in plain language and distinguish it from traditional automation and machine learning.
  • Identify the three model types every user encounters: fast chat, reasoning, and agentic.
  • Explain why LLMs hallucinate and how context windows affect responses.

Topics

  • Generative AI versus the broader AI umbrella
  • How LLMs work — token prediction, the 90-second version
  • Fast chat models, reasoning models, and agentic models
  • Context windows, knowledge cutoffs, and recency limitations
  • Why your assistant doesn’t know about something that happened last week

 The Five Assistants — Who’s Who and When to Use Which

Learning Objectives

  • Compare the five major assistants on capability, ecosystem, and data handling.
  • Apply a decision framework for selecting the right assistant for a given task.
  • Run the same prompt across two assistants and evaluate the differences.

Topics

  • ChatGPT (OpenAI) — Custom GPTs, voice mode, Deep Research, operator features
  • Gemini (Google) — Workspace integration, large context window, Gems
  • Claude (Anthropic) — writing and reasoning, Projects, Artifacts, Computer Use, MCP
  • Microsoft Copilot — embedded in Word, Excel, Outlook, Teams; tenant-grounded
  • Grok (xAI) — real-time X data, fewer guardrails, niche use
  • Decision framework: data sensitivity, tenant grounding, capability, cost

Lab

  • Lab 1: Run the same four-prompt exercise against two assistants of your choice. Compare outputs and discuss with a partner.

Prompting in 2026 — It’s Simpler Than You’ve Been Told

Learning Objectives

  • Apply the four-part Role-Task-Context-Format prompting pattern.
  • Choose between pasting, uploading, and linking content.
  • Iteratively refine a prompt to improve output quality.

Topics

  • Why traditional “prompt engineering” matters less than it did
  • The Role, Task, Context, Format pattern
  • When to paste, when to upload, when to link
  • Iterative refinement and follow-up prompts
  • System prompts, custom instructions, and memory features

Lab

  • Lab 2: Rewrite three of your real work emails using each assistant’s tone and format controls.

Multimodal — Voice, Images, Documents, Video, Screens

Learning Objectives

  • Use voice mode for thinking and drafting.
  • Upload an image or document and extract structured information.
  • Use screen-sharing or vision features to get help with on-screen tasks.

Topics

  • Voice mode as a thinking partner
  • Image understanding — screenshots, whiteboards, receipts, charts
  • Document upload — PDFs, spreadsheets, slide decks
  • Screen sharing and vision features in ChatGPT, Gemini Live, and Copilot Vision

Lab

  • Lab 3: Dictate a meeting prep via voice. Upload the resulting document. Ask the assistant for a one-page executive summary.

 Productivity Inside the Tools You Already Own

Learning Objectives

  • Use Microsoft 365 Copilot or Google Gemini inside Outlook, Word, Excel, and Teams.
  • Decide when to use the embedded assistant versus the standalone chat app.
  • Apply the “draft here, polish there” workflow.

Topics

  • Microsoft 365 Copilot in Outlook, Word, Excel, Teams, PowerPoint
  • Google Gemini in Gmail, Docs, Sheets, Meet
  • Embedded versus standalone — when to use each
  • The draft-here-polish-there workflow

Lab

  • Lab 4: End-of-day email triage using Copilot or Gemini in your live inbox (or a sandboxed account).

Custom Assistants — Your First Reusable AI

Learning Objectives

  • Explain when a repeating task justifies building a custom assistant.
  • Build a working custom assistant on at least one platform.
  • Decide whether to share, restrict, or keep an assistant private.

Topics

  • Custom GPTs, Gemini Gems, Claude Projects, Copilot Agents — same idea, different platforms
  • When to build one — any task you repeat weekly
  • Anatomy: instructions, knowledge files, capabilities
  • Sharing, governance, and audit considerations

Lab

  • Lab 5: Build one working custom assistant for a real repeating task — meeting notes cleaner, proposal reviewer, or client research briefer.

 AI Agents — The 2026 Shift

Learning Objectives

  • Distinguish between chat, copilot, and agent modes.
  • Identify tasks suitable for agent delegation versus tasks requiring human judgment.
  • Configure and supervise a low-risk agent task end to end.

Topics

  • Definitions: chat (pull), copilot (assist), agent (act)
  • What agents can do today — browse, fill forms, run code, send email, schedule, update records
  • What agents still cannot do reliably
  • Platforms: Copilot Studio agents, ChatGPT operator and tasks, Claude Computer Use and Agent SDK, Gemini agentic features
  • Risks: runaway actions, prompt injection, credential exposure, audit trails

Lab

  • Lab 6: Configure one low-risk agent task — calendar-to-email summary or document tagging. Watch it run. Discuss what you would and would not delegate.

Data Analysis and Decision Support

Learning Objectives

  • Upload a spreadsheet and produce a useful analysis through natural-language prompts.
  • Generate structured outputs including tables, charts, and decision matrices.
  • Identify when an AI-generated number requires verification.

Topics

  • Uploading spreadsheets — what works, what doesn’t
  • Natural language to chart, pivot, and summary
  • Structured outputs: tables, comparison matrices, decision frameworks
  • Trust and verification — the “show me your work” prompt

Lab

  • Lab 7: Analyze a provided 2,000-row sales dataset. Produce an executive summary. Spot the planted anomaly.

Safety, Privacy, and What Not to Paste

Learning Objectives

  • Distinguish consumer and enterprise tiers of AI services.
  • Identify the top five risks a business user is likely to encounter.
  • Recognize warning signs that an AI response may be wrong or harmful.

Topics

  • Consumer versus enterprise tiers — the most important distinction
  • Data handling: training opt-outs, retention, region
  • Top five risks: data leakage, hallucinated facts, biased outputs, prompt injection, copyright exposure
  • Red flags — when your assistant is confidently wrong

Ethics, Policy, and Your Organization’s Rules

Learning Objectives

  • Summarize the current AI regulatory landscape relevant to a US business user.
  • Explain disclosure norms for AI-generated work.
  • Draft a one-page AI acceptable-use policy for a small team.

Topics

  • EU AI Act and US state-level AI regulations — 2026 snapshot
  • Copyright, training data, and the practical fallout for business users
  • Disclosure norms: when to tell colleagues, clients, and regulators
  • Writing a one-page acceptable-use policy

Lab

  • Lab 8: Draft your team’s AI do’s and don’ts in 15 minutes. Share two with the group.

Your 30-Day Plan

Learning Objectives

  • Identify three habits that produce compounding returns from daily AI use.
  • Commit to a specific 30-day implementation plan.
  • Define personal success metrics for AI adoption.

Topics

  • The three compounding habits
  • Build one custom assistant. Run one agent task. Replace one meeting with voice-mode synthesis.
  • Measurement: time saved per week, artifacts improved, decisions accelerated
  • Resources for continued learning

Prerequisites

Comfort with a web browser and a work email account. No coding or technical background required. Learners should have access to at least one of the following before class:

  • ChatGPT (free, Plus, or Enterprise)
  • Google Gemini (free or via Google Workspace)
  • Microsoft 365 Copilot (any licensed seat)
  • ai (free or paid)
  • Optional: Grok (X Premium)

Learners should bring a laptop with one supported browser installed. Microphone access is required for the voice-mode lab.