Remote SupportQuick Winners at a Glance
Microsoft 365 Copilot
Best inside Microsoft 365
Native inside Outlook, Teams, Word, Excel, PowerPoint. Pulls value directly from your existing M365 files, mail, and meetings. Easiest adoption path for Microsoft-first businesses.
Strengths
- Native to apps staff already use
- Pulls context from your tenant (SharePoint, Teams, mail)
- Fastest adoption for office staff
- Enterprise data boundary honours M365 security
Trade-offs
- Value drops outside the Microsoft stack
- Requires eligible M365 licensing
- Less capable for open-ended reasoning than standalone models
Best for
Businesses running Microsoft 365 as their primary productivity stack.
ChatGPT Business / Enterprise
Best all-round standalone
Strongest general-purpose AI for most roles. Ops, sales, marketing, leadership, support. Not tied to any vendor stack.
Strengths
- Broadest usefulness across departments
- Strong at writing, summarising, planning, analysis
- Custom GPTs and Projects for team workflows
- No lock-in to a single ecosystem
Trade-offs
- No deep native integration with one platform
- Outputs can feel generic without good prompting
- Requires teams to build prompting habits
Best for
Businesses wanting one flexible AI across many roles.
Claude Team / Enterprise
Best deep thinking and writing
Preferred when the output must feel smart, measured, and careful. Board papers, policy, strategy, legal-adjacent writing.
Strengths
- Very strong long-form writing
- Excellent at large-document analysis
- More deliberate tone than ChatGPT
- Class-leading for policy and governance work
Trade-offs
- Slower than ChatGPT for quick daily tasks
- Smaller ecosystem of integrations
- Less of an all-rounder for general team use
Best for
Leadership, consulting, governance, and policy-heavy teams.
Google Gemini
Best inside Google Workspace
Native to Gmail, Docs, Sheets, Slides, Meet. Strongest when you are already all-in on Google.
Strengths
- Native to Google Workspace apps
- Tight integration with Drive, Calendar, Meet
- Usually wrapped into Workspace pricing
- Collaboration-heavy teams
Trade-offs
- Standalone value outside Google is limited
- Not compelling for Microsoft-first businesses
- Less mature as a general-purpose assistant
Best for
Businesses standardised on Google Workspace.
Perplexity Enterprise
Best research tool
Web-backed answers with source citations. Fast fact-finding, market scans, competitor research.
Strengths
- Source-cited answers reduce hallucination risk
- Fast competitive scans and market research
- Strong for presales, consulting, strategy
- Good for due diligence
Trade-offs
- Not a full daily productivity assistant
- Less suited to writing or team-wide deployment
- Specialist tool, not an all-rounder
Best for
Research-heavy teams alongside a broader AI suite.
Ollama / Local LLMs
Best for privacy and control
Run models locally. No data leaves the environment. Full control over models, prompts, and retention.
Strengths
- Data never leaves your infrastructure
- Full model and customisation control
- Strong for developer and dev-secops teams
- Good for privacy-sensitive industries
Trade-offs
- Not a polished suite for non-technical staff
- Requires engineering time and hardware
- Limited to smaller open-weight models
Best for
Technical teams, privacy-sensitive workloads, or environments where cloud AI is restricted.
How to Choose
Start with where your staff already live, then layer specialists on top.
Primarily Microsoft 365?
Answer: M365 Copilot as the default. Fastest adoption, native integration.
Want one AI across roles without lock-in?
Answer: ChatGPT Business. Strongest all-rounder.
Board papers, policy, and governance matter?
Answer: Claude Team alongside your main suite.
Standardised on Google Workspace?
Answer: Gemini. Value comes from native integration.
Research-heavy roles (presales, consulting, strategy)?
Answer: Perplexity as a specialist on top of a generalist.
Cannot send data to cloud AI?
Answer: Ollama or a local hosted model. Budget for hardware and engineering.
AI Governance: The Part Most Businesses Skip
Before rolling out AI to staff, get the governance right. The rushed deployments are the ones that leak data, breach privacy obligations, or end up in front of the board.
Acceptable Use Policy
What AI tools are approved, what data can and cannot be entered, who is responsible for output accuracy.
Data classification
Never paste client PII, financial records, or confidential contracts into public AI.
Tenant-level protections
Use enterprise / team licences with data boundary, not personal accounts. Disable model training.
Human-in-the-loop
Staff are accountable for AI output. No auto-send of AI-written emails to customers without review.
Record-keeping
Know which system of record is authoritative. AI summaries are not the source of truth.
Training and champions
One champion per team. Shared prompt library. Monthly lunch-and-learn sessions.
Common Mistakes
Letting staff use personal ChatGPT accounts
No enterprise data protection. Prompts train the model. Data leakage waiting to happen.
Deploying Copilot without data hygiene
Copilot surfaces whatever SharePoint oversharing already exists. Fix permissions before rollout.
Measuring adoption, not outcomes
Usage metrics do not equal value. Measure time saved and decision quality.
No acceptable use policy
Staff do not know what is okay. Policy is the cheapest control available.
Treating AI as deterministic
Output varies. Sensitive workflows need verification. Never send AI output to customers unreviewed.
Common questions
Which AI tool is best for an Australian business running Microsoft 365?
Is ChatGPT safe for business use?
What is the difference between Claude and ChatGPT for business?
Can we run AI tools locally without sending data to the cloud?
Do we need an AI acceptable use policy before rolling out AI tools?
How much does Microsoft 365 Copilot cost per user in Australia?
Deploy AI Safely
We help Australian businesses evaluate, deploy, and govern AI tools including M365 Copilot, ChatGPT, and local models. Vendor-neutral, outcome-focused.