If your team is using Microsoft 365 all day (Outlook, Teams, Word, Excel, PowerPoint), Microsoft Copilot often shines because it can work where the work already lives. If your team needs help with thinking, drafting, explaining, ideating, or solving messy problems across lots of contexts, ChatGPT is usually the better “all-purpose” assistant.
Most workplaces get the best results when they stop treating it as a winner-takes-all choice and instead match the tool to the task.
This guide is written for Australian businesses and teams who want practical clarity, safer usage, and better outputs with less trial-and-error.
The simplest way to choose: where the task happens
Here’s the mental model that prevents 80% of confusion:
Use Copilot when…
• The work is inside Microsoft 365 (emails, meetings, documents, files, calendars)
• You want summaries, rewrites, drafting, or analysis grounded in your tenant’s content (based on your permissions)
• The job is “turn what’s already in M365 into a useful output”
Use ChatGPT when…
• You need reasoning, ideation, first drafts, structure, or explanations
• You’re working across tools and topics (not just M365)
• The job is “create a strong starting point” or “think through complexity”
Quick answer
Copilot is usually best for Microsoft 365 execution (summarising meetings, drafting replies from email threads, creating documents from your files). ChatGPT is usually best for thinking work (planning, writing, brainstorming, explaining, reframing, troubleshooting, producing templates). Many teams use both: create in ChatGPT, then execute and refine in Copilot.
First, clarify what “Copilot” you mean
People often mix these up:
• Microsoft 365 Copilot (Word, Excel, PowerPoint, Outlook, Teams)
• Copilot Chat (often used as a chat-style interface, sometimes with work grounding depending on licensing/config)
• GitHub Copilot (developer-focused coding assistance)
• Copilot Studio (building custom copilots)
This article is about Copilot at work in the Microsoft 365 sense: helping people do everyday business tasks faster and more consistently inside the M365 ecosystem.
Task-by-task: the best tool for common workplace jobs
Below you’ll find practical scenarios Australian teams run into every week, plus which tool tends to handle them best and how to prompt for better results.
Email and inbox management
Best tool: Copilot (most of the time)
Copilot is strong when it can see the email thread and your calendar context (subject to your access). It reduces time spent digging through long chains and helps turn messy threads into crisp replies.
Use Copilot for:
• Summarising a long thread into decisions, open questions, and next steps
• Drafting a reply that reflects the thread’s tone and details
• Turning an email request into a short checklist or plan
Prompt ideas:
• “Summarise this thread. List decisions made, unresolved questions, and who owes what.”
• “Draft a reply that confirms the next step, asks for missing info, and keeps the tone friendly and clear.”
Best tool: ChatGPT (when you need better writing or positioning)
If the email is sensitive (stakeholder management, conflict, negotiation) or you want a higher-quality rewrite with options, ChatGPT often produces stronger language and alternative tones.
Prompt ideas:
• “Rewrite this email in a calm, professional tone. Give me two versions: concise and detailed.”
• “Suggest three subject lines that match the content and reduce back-and-forth.”
Meetings, minutes, and follow-ups
Best tool: Copilot
Copilot is typically the fastest way to convert meetings into outcomes: recap, decisions, actions, and follow-up messages.
Use Copilot for:
• Meeting recap with action items
• Turning a recap into tasks grouped by owner
• Drafting a follow-up email to attendees
Prompt ideas:
• “Create meeting notes with: agenda, discussion summary, decisions, action items, due dates.”
• “Draft a follow-up message to the group with the key decisions and next steps.”
Word documents, SOPs, and internal documentation
Best tool: it depends on what you’re starting with
If you already have internal notes, a rough draft, or existing documents in M365, Copilot can help rewrite, expand, and standardise quickly.
If you’re starting from scratch or need a strong structure, ChatGPT is usually better for:
• Outlining a clean SOP structure
• Creating a first draft from a short brief
• Making templates (checklists, scripts, runbooks)
A useful workflow is:
• Draft the structure and first version in ChatGPT
• Move it into Word and use Copilot to refine wording, consistency, and formatting
Q: Which tool is better for writing SOPs?
If you have existing process notes and want to turn them into a polished SOP inside Word, Copilot is often faster. If you have a messy process and need help designing the SOP structure (roles, steps, exceptions, controls), ChatGPT is often better.
PowerPoint decks and stakeholder updates
Best tool: Copilot for building slides, ChatGPT for story
If your deck is based on internal content (a report, meeting outcomes, or project plan), Copilot can help generate a draft deck and speaker notes.
ChatGPT tends to excel at:
• Clarifying the narrative (problem → options → recommendation)
• Producing multiple versions for different audiences (exec vs delivery team)
• Tightening language to be more persuasive and less “wordy”
Prompt ideas for ChatGPT:
• “Turn these bullet points into a 6-slide executive story. Include key message per slide and speaker notes.”
• “Rewrite this update for a CFO audience: concise, risk-aware, and focused on outcomes.”
Excel analysis, formulas, and reporting
Best tool: Copilot (when the data is in Excel) + ChatGPT (when you need an explanation)
Inside Excel, Copilot can help with quick analysis, summaries, and formula generation.
ChatGPT is great when you need:
• An explanation of why a formula isn’t working
• A suggested approach (model design, assumptions, edge cases)
• A plain-English walkthrough your team can follow
A practical approach:
• Use Copilot to create/adjust formulas and generate insights in the sheet
• Use ChatGPT to sanity-check logic and explain the “why” in human terms
Research, comparisons, and external content drafting
Best tool: ChatGPT
For synthesising ideas, drafting long-form content, or building structured comparisons, ChatGPT is usually stronger.
Use ChatGPT for:
• Drafting policies, onboarding guides, and internal training
• Creating customer-friendly explanations
• Producing checklists and scripts
• Brainstorming offers, naming, positioning, and messaging
Important: when you use any AI tool for research-like tasks, build in verification. Treat outputs as a starting point, not a source of truth.
Customer support and response libraries
Best tool: both, depending on where your support work lives
If your team works from Outlook/Teams and internal knowledge is in Microsoft documents, Copilot can help draft responses grounded in existing material.
ChatGPT is excellent for:
• Building a tone guide and response library
• Creating “reply frameworks” (acknowledge → diagnose → next step)
• Rewriting responses to be clearer and more empathetic
Q: Do we need both Copilot and ChatGPT?
Many teams benefit from both because they solve different problems.
• Copilot helps you do Microsoft 365 work faster, in-context
• ChatGPT helps you think, draft, and structure work across contexts
If budget or change capacity is limited, start with the tool that matches where your highest-volume work happens.
The “best at” list: quick decision cues
Copilot usually wins for
• Summarising long email threads and meetings
• Drafting replies using details from your M365 content
• Creating “first pass” documents from existing internal files
• Generating slide drafts from internal material
• Doing quick, in-sheet Excel insights and formula help (depending on setup)
ChatGPT usually wins for
• Planning, brainstorming, and strategy drafts
• Writing high-quality first drafts from minimal notes
• Creating templates (SOPs, checklists, onboarding, scripts)
• Explaining complex topics to different audiences
• Rewriting content into multiple tones and lengths
• Troubleshooting logic, wording, or structure when things are messy
Prompts that actually work at work
Below are reusable prompt patterns your team can keep.
For clearer outputs (either tool)
• “Ask me any questions you need before you answer.”
• “Give me a short version first, then a detailed version.”
• “Provide a checklist I can follow.”
• “Include assumptions and what you’d need to confirm.”
• “Highlight risks, edge cases, and what could go wrong.”
For turning information into action
• “Turn this into tasks with owners, due dates, and dependencies.”
• “Create a simple plan for the next 2 weeks. Keep it realistic.”
• “Draft a message to stakeholders summarising progress, risks, and next steps.”
For quality control
• “Critique this draft. What’s unclear, risky, or missing?”
• “Rewrite for an Australian business audience: plain English, direct, no jargon.”
• “List the claims that need verification and suggest how to verify them.”
Governance and safe-use: the part most teams skip (and regret)
The biggest workplace risk isn’t that AI is “wrong”. It’s that staff unintentionally share sensitive information, or accept outputs without checking.
A practical baseline for Australian businesses is to create simple guardrails your team can follow, aligned with recognised guidance like the Australian Cyber Security Centre’s recommendations on AI and data security. Here’s a good starting point to reference internally: ACSC guidance on AI data security
A simple, workable set of team rules
• Don’t paste customer PII, employee records, health information, or confidential contract terms into any AI tool unless your organisation has explicitly approved it
• Treat AI drafts as “Version 0.7” — useful, but not final
• Verify numbers, names, dates, quotes, and policy statements before sending externally
• Keep a human accountable for any final decision or customer-facing advice
• Store final outputs in your normal systems (SharePoint, Teams, CRM) with appropriate access controls
Q: Which tool is safer for confidential information?
Safety depends on your organisation’s configuration, licences, and policies, not just the brand name on the tool. The safest approach is to:
• classify information (public/internal/confidential)
• define what can and cannot be entered into AI tools
• limit access via permissions and role-based controls
• train staff on “what good looks like” and require verification for key outputs
A practical rollout plan for teams (without the chaos)
If you want adoption without confusion, run a short, focused pilot.
Week 1: pick 5 high-volume tasks
Choose tasks that are frequent and low-risk, such as:
• meeting summaries
• internal email drafts
• first drafts of internal documentation
• weekly status updates
• basic Excel formula support
Create a shared “prompt pack” and a shared definition of a good output.
Week 2: add verification and workflow
Introduce a lightweight review checklist:
• Is the output grounded in the right source material?
• Are there any unknowns presented as facts?
• Are action items clear, assigned, and realistic?
• Does it match our tone and compliance needs?
Week 3–4: standardise and scale
This is where teams move from “cool tool” to repeatable capability:
• document your best prompts
• create templates (update emails, SOP structures, meeting note formats)
• assign a champion per team to keep usage consistent
If you want to connect these habits to broader operational improvements, it helps to anchor the program to an AI automation strategy rather than chasing random use cases.
Where AI tools fit alongside automation (so you don’t double-handle work)
Copilot and ChatGPT help people produce outputs faster. Automation reduces the need for manual handling in the first place. When you combine them thoughtfully, you get compounding gains.
Examples:
• ChatGPT drafts the SOP and support scripts → you standardise them in your knowledge base
• Copilot turns recurring meeting notes into consistent action lists → you connect actions to your task system
• Standard outputs become repeatable workflows that reduce rework and handoffs
If your team is repeatedly doing the same steps (copy/paste, reformatting, routing approvals, chasing updates), that’s a signal to look at business workflow automation so the process doesn’t rely on individual effort.
Q: How do we know what to automate versus what to “AI-assist”?
AI-assist is great for variable, language-heavy work (drafting, summarising, interpreting). Automation is great for repeatable steps (handoffs, routing, data transfer, notifications, status changes). If a task happens the same way 50 times a week, it’s usually an automation candidate.
Common mistakes (and how to avoid them)
Mistake 1: Asking for too much in one prompt
Fix: break it into steps. Ask for a structure first, then content, then refinement.
Mistake 2: No verification step
Fix: add a “checklist prompt” at the end: “List anything that might be wrong or needs confirmation.”
Mistake 3: Automating chaos
Fix: if the process is unclear, map it first. AI can help draft, but humans must decide the process.
Mistake 4: Ignoring permissions and oversharing
Fix: adopt simple data classification rules and train staff. Keep controls consistent with an AI automation roadmap so usage scales safely.
FAQ
Is Copilot better than ChatGPT for office work?
Copilot is often better for office work that lives inside Microsoft 365 because it can draft and summarise using your files, emails, and meetings (based on access). ChatGPT is often better for planning, writing first drafts from scratch, and solving problems that aren’t confined to M365.
What should I use Copilot for at work?
Use Copilot for: meeting recaps, action items, email thread summaries, drafting replies based on thread context, refining Word documents that already exist, and producing slide drafts from internal material.
What should I use ChatGPT for at work?
Use ChatGPT for: brainstorming, outlining, first drafts, rewriting in different tones, creating templates (SOPs/checklists/scripts), explaining complex topics, and troubleshooting writing or logic issues.
Can we use both without doubling effort?
Yes. A common pattern is “create in ChatGPT, execute in Copilot.” For example: outline a document in ChatGPT, then refine and format it in Word with Copilot; draft messaging in ChatGPT, then tailor replies inside Outlook with Copilot.
How do we stop staff putting sensitive info into AI tools?
Create a short policy with examples of what is never allowed (PII, HR records, confidential commercial terms), train staff on it, and reinforce it with reminders and workflow defaults. Referencing recognised guidance (such as the ACSC) helps make it practical and consistent.
Which tool is better for Excel?
If you’re working directly in Excel, Copilot can be fast for formula creation and quick summaries. ChatGPT is great for explaining why something isn’t working, suggesting modelling approaches, and providing plain-English reasoning your team can validate.
