by The Computing Australia Group | Choosing The Right AI Tool
In the AI-driven workplace, the assistants you deploy can amplify (or undermine) team productivity, customer experience, and risk posture. Two names dominate most shortlists: Microsoft Copilot and ChatGPT. Each is powerful-but they’re optimised for different strengths and deployment patterns.
At Computing Australia, we’ve embedded Microsoft Copilot into our standard tech stack across Microsoft 365 and Azure. We also use ChatGPT in our engineering workflow to validate logic, accelerate code reviews, and stress-test ideas. This article explains what each tool does best, where we’ve seen tangible impact, how to evaluate them against your requirements, and a pragmatic path to adoption-so you can choose (and combine) them with confidence.
Integration That Works Where You Work
Why Copilot feels “invisible” (in a good way)
Copilot sits inside the Microsoft 365 apps you already use. Draft a proposal in Word, transform a meeting transcript into actions in Teams, or ask Excel to build a model from a messy dataset-without leaving the app. The value is less about flashy outputs and more about systematically eliminating context-switching:
- Word & PowerPoint: turn briefs, emails, and notes into structured documents, slide decks, and speaker notes.
- Excel: summarise large worksheets, generate formulas, build pivot analyses, and surface trends.
- Outlook: triage inboxes, propose replies, extract key info, and summarise threads.
- Teams: produce meeting recaps, action lists, and follow-up tasks; query past discussions and shared files.
Because Copilot respects Microsoft 365 permissions, people only see what they’re allowed to see. That’s crucial for governance and audit.
Where ChatGPT fits naturally
ChatGPT lives outside your app ecosystem. That’s a strength when you want an unconstrained assistant for:
- Brainstorming & research: explore unfamiliar topics, collect angles, and shape narratives.
- Content generation: outlines, first drafts, tone explorations, headline variations.
- Coding assistance: suggest test cases, refactor snippets, generate documentation, and explain complex code.
- Prompt prototyping: quickly experiment with prompts and system messages before you operationalise them in tools or automations.
It’s fantastic for thinking work that benefits from stepping away from the “document you’re in.”
Security, Compliance & Risk: What Matters to Leadership
If your business handles sensitive customer, financial, or operational data, security isn’t optional-it’s existential.
- Copilot inherits Microsoft’s enterprise security model, including identity, access controls, logging, DLP, and compliance capabilities aligned to the Microsoft 365 and Azure stack. If you already use Microsoft 365 with well-designed permissions, Copilot slots in with least-privilege by default.
- ChatGPT offers enterprise and business plans with improved privacy options and admin controls. Still, the risk posture depends on how you deploy and govern it: which plan, which data you allow in prompts, and which integration patterns you permit. For sectors like oil & gas, healthcare, financial services, and not-for-profit, we recommend formal policies (what can and can’t be shared), training, and auditability before broad rollout.
Bottom line: If your data estate already sits in Microsoft 365 and Azure-and governance is non-negotiable-Copilot will almost always be the more straightforward path to secure, auditable AI at scale. Use ChatGPT where it shines, with explicit guardrails.
Tailored for Business Use: Context Is King
Copilot-the AI that “knows your day job”
Copilot leverages organisational context: emails, files, meetings, calendars, and SharePoint/OneDrive content. That means it can:
- Summarise your client thread, not “a” client thread.
- Draft proposals using your templates and your previous work.
- Build Excel analyses from your ops data and update your chart styles.
ChatGPT-generalist intelligence, specialist prompts
ChatGPT delivers world-class reasoning for open-ended tasks. With the right prompts, it can emulate tone, structure arguments, test hypotheses, and generate code. It’s unmatched for rapid ideation, creative problem-solving, and technical explanation-especially when your work isn’t confined to Microsoft apps.
Real-World Impact at Computing Australia
We’ve deployed both tools across departments. Here’s what that looks like in practice.
1. Systems Operations & Service Desk
- Copilot: builds meeting summaries and action plans from Teams calls; drafts ticket communications; creates knowledge base entries from change logs; surfaces related documentation fast.
- Impact: Faster ticket resolution, consistent client communication, lower handle time, and better documentation standards.
2. Software Engineering & QA
- Copilot inside M365/Teams: turns requirements notes into clear user stories, acceptance criteria, and test plans.
- ChatGPT: helps with code reasoning, generating test cases, explaining complex regex/SQL, and reviewing logic at speed.
- Impact: Fewer misinterpretations, stronger test coverage, quicker code reviews, accelerated delivery.
3. Marketing & Sales Enablement
- Copilot: turns briefs + past proposals into client-ready decks; drafts outreach emails tailored to the opportunity; summarises market research in Excel.
- ChatGPT: explores campaign angles, generates headline variations, and drafts first-pass content for landing pages and ads.
- Impact: Campaigns produced in hours, not days, with measurable consistency and brand alignment.
4. Finance & Leadership
- Copilot (Excel/Power BI context): quick variance analyses, board-friendly commentary, and “what changed since last month” narratives.
- Impact: Executives spend less time assembling data and more time deciding.
Across these teams, we’ve observed time savings up to ~40% on routine writing and documentation tasks after training and process updates-freeing people to focus on client outcomes and innovation.
Cost vs Efficiency: Understanding ROI
Yes, Copilot requires licensing. But the combination of time saved, higher output quality, and reduced rework adds up quickly:
- Fewer manual hours writing emails, summarising meetings, and compiling reports.
- Faster proposals lead to improved win rates and shorter sales cycles.
- More consistent documentation reduces support escalations and onboarding time.
- Developers move faster on code comprehension, test generation, and documentation.
We’ve seen Copilot pay for itself within weeks in high-communication teams once people are trained to prompt effectively and follow good data hygiene.
Comparison Matrix: Copilot vs ChatGPT
| Dimension | Microsoft | ChatGPT |
|---|---|---|
| Primary Value | Integrated productivity inside M365 with enterprise governance | General-purpose reasoning, ideation, and coding help |
| Context Awareness | High-leverages M365 content & permissions | Medium-context within the chat/session; can be extended via tools |
| Security/Governance | Strong-aligned to Microsoft identity, DLP, audit | Varies by plan/policy; requires explicit guardrails |
| Best For | Knowledge work in Word/Excel/PowerPoint/Outlook/Teams | Brainstorming, research, creative writing, code assistance |
| Learning Curve | Low-works where users already live | Low-to-Medium-benefits from prompt patterns |
| Extensibility | Microsoft Graph, plugins, Azure ecosystem | API, function calling, custom tools, broad ecosystem |
| Change Management | Moderate-policy + training in M365 | Moderate-policy + training around data handling |
| Deployment Speed | Fast in M365 tenants | Fast for teams; enterprise rollout requires governance |
Decision Guide: Which Should You Choose (or Combine)?
Use these quick checks:
- Are you all-in on Microsoft 365? Start with Copilot.
- Do teams need an AI “studio” for ideation and coding support? Add ChatGPT.
- Is compliance non-negotiable (NFP, healthcare, financial services, oil & gas)? Copilot first, then ChatGPT under policy.
- Do you need AI in documents, spreadsheets, email, and meetings today? Copilot.
- Do you need wide exploration, content angles, and code reasoning? ChatGPT.
Most businesses do both-with clear use policies, data handling rules, and training.
Implementation Roadmap (Pragmatic & Low-Risk)
1. Define Business Objectives
Identify 5-7 high-value use cases (e.g., meeting notes → action plans; proposal first drafts; ticket documentation; Excel trend summaries; code explanation; SEO content outlines).
2. Data Hygiene & Permissions
Fix oversharing in SharePoint/OneDrive. Enforce least-privilege. Archive or lock down sensitive libraries.
3. Pilot with Champions
Select a cross-functional group. Measure time savings, quality, and user satisfaction. Capture prompt patterns.
4. Create Guardrails
Draft a 1-page AI Acceptable Use Policy. Specify what can/can’t be pasted into prompts, retention expectations, and escalation paths.
5. Train for Prompts & Review Loops
Teach structured prompting (“Goal → Inputs → Constraints → Style → Review”). Introduce red-team checks (verify facts, cite sources, sanitise client info).
6. Expand & Automate
Roll out to adjacent teams. For ChatGPT, consider API-based automations for content QA and code linting. For Copilot, standardise templates in Word/PowerPoint and Excel analysis playbooks.
7. Measure & Improve
Track baseline vs post-adoption KPIs (resolution time, proposal cycle time, document quality scores, meeting follow-up rate).
Prompt Patterns that Work (Copy/Paste)
For Copilot in Word (Proposal Draft):
“Draft a 2-page proposal for [Client] based on [Brief/Email/Notes]. Include: executive summary, objectives, scope, timeline, assumptions, and next steps. Use our [Template Name] voice and British/Australian spelling. Highlight three differentiators from our [Case Study/Deck].”
For Copilot in Excel (Ops Summary):
“Summarise key trends in this worksheet: revenue variance, top three drivers, and any outliers. Propose two charts and create them. Add a short narrative suitable for a monthly board pack.”
For ChatGPT (Code Review/Testing):
“Review this Python function for edge cases and performance. Propose unit tests with inputs/expected outputs. Explain any potential failure modes, and suggest refactors for readability.”
For ChatGPT (SEO Outline):
“Produce an SEO-optimised outline for a landing page targeting ‘synthetic grass Perth’ and ‘artificial turf installation’. Include H1/H2/H3s, FAQs, and internal link suggestions to pages on maintenance, pet-friendly lawns, and swimming pool areas. Australian English.”
Sector-Specific Notes (Oil & Gas, NFP, Manufacturing)
- Oil & Gas: Prioritise Copilot for governed knowledge work. For ChatGPT, restrict to sanitised prompts and non-confidential ideation.
- Not-for-Profit: Copilot strengthens grant writing, impact reporting, and board communications. ChatGPT improves campaign brainstorming and volunteer comms.
- Manufacturing: Copilot accelerates SOP updates and supplier comms; ChatGPT helps with technical documentation drafts and code for small internal tools.
How We’re Building on This at Computing Australia
We’re training models on ~200,000+ tickets (historic service data) to classify, summarise, and route requests-turning years of operational experience into actionable, real-time assistance. Copilot supports the documentation and collaboration layer; ChatGPT helps our engineers reason through complex logic and generate tests. Together, they reduce friction end-to-end: intake → action → documentation → learning.
Final Thoughts
Choosing Copilot vs ChatGPT isn’t a zero-sum game. Map each tool to the jobs-to-be-done in your organisation. If you’re invested in Microsoft 365 and you care about governance, Copilot is the smarter default for daily work. Keep ChatGPT in your toolkit for exploration, coding, and creative acceleration-with clear policies.
If you’d like help planning your rollout, we can assess your environment, prioritise use cases, run a pilot, and deliver training-so you capture value quickly and safely.
FAQ
Will Copilot or ChatGPT “hallucinate”?
Any generative model can produce errors. Build review loops, prefer summarisation over generation for business-critical outputs, and train staff to verify numbers, names, and claims.
Can we stop data leakage?
You can reduce it dramatically. Use the right enterprise plan, enforce policies, keep sensitive data out of prompts, and monitor usage. In Microsoft tenants, enforce DLP, Conditional Access, and least-privilege file sharing.
Do we need both tools?
Often yes. Copilot for M365 productivity with governance, ChatGPT for ideation and coding. Start where the ROI is clearest, then expand.
