Picking an AI can feel like walking into a supermarket where every box says “BEST” in huge letters, and somehow none of them tell you what’s inside. One tool is excellent at brainstorming but fumbles citations. Another writes decent code but panics when you paste a spreadsheet. Another makes gorgeous images but (depending on the tool + settings) can be very “community gallery by default”… oops. [5]
So yeah, Which AI? is a fair question. Also a slightly exhausting one. Let’s make it simpler, with a few human-ish rules of thumb, a comparison table, and some practical “try this prompt” tests you can run in a few minutes. ☕🙂
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🔗 Is text-to-speech AI?
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“Which AI?”😅
Here’s what actually matters:
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Your task type: writing, coding, research, images, data, meetings, admin busywork
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Your risk level: is this playful, or “if this leaks I get fired” 😬
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Your workflow: do you live in Docs, Office apps, GitHub, Slack, Notion, spreadsheets?
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Your tolerance for hallucinations: some AIs will confidently “fill gaps” like a friend who swears they saw a celebrity at Tesco
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Your privacy expectations: retention, training opt-outs, enterprise controls, and what “private” amounts to (spoiler: it varies)
If you only remember one thing: choose the AI that matches the job, not the AI that wins the loudest popularity contest.
The quick decision checklist (steal this) ✅
Before you pick anything, answer these in plain language:
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What do I want the AI to produce?
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Text draft, summary, code, image, slides, spreadsheet insights, research answer, etc.
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How wrong can it be before it hurts?
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Low stakes: party invite copy 🎉
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Medium: customer email, blog outline
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High: legal, medical, financial, security, compliance
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Will I paste sensitive data?
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If yes, you want clear business/enterprise terms, retention controls, and admin settings you can enforce.
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Do I need citations or sources?
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If yes, use a tool designed for search + citations, and still verify.
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Do I need it inside my existing apps?
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If your work is 90% in Google Workspace or Microsoft 365, integrated AI can be ridiculously convenient.
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I know, it’s not romantic. But it works.
Comparison table: top options for “Which AI?” 🧭
Prices change, plans change, the universe is turbulent - so think “shape of the tool,” not “receipt.”
| Tool | Best for | When it’s a great fit | What to double-check |
|---|---|---|---|
| ChatGPT | General help, drafting, ideation, analysis | Wide range of tasks; strong “talk it out” partner | If you’re using it for work, read the business/enterprise data commitments and retention controls tied to your plan. [1] |
| Claude | Writing, long docs, tone, reasoning | Long-form editing and calmer prose workflows | Data controls + what your org plan does by default |
| Gemini (Workspace) | Gmail/Docs/Sheets help, meeting notes, doc workflows | You live inside Google Workspace all day | Admin settings, permissions model, and how org data is handled in your Workspace setup. [2] |
| Microsoft 365 Copilot | Word/Excel/Outlook workflows | You live inside Office; want AI “inside the doc” | Org boundaries, Graph permissions, and how prompts/responses are handled under your tenant’s rules. [3] |
| Perplexity (and other research-first tools) | Research-style answers | You want “answers with receipts” fast | Citation quality: can it show what the source actually said? |
| GitHub Copilot (and IDE assistants) | Coding in-editor | Autocomplete + refactors where you work | Policy, telemetry, and what’s allowed on your repos |
| Midjourney | Stylish image generation | “Make it look cool” is the brief | Visibility defaults and privacy modes (especially if the content is sensitive). [5] |
| Stable Diffusion ecosystem | Customizable image pipelines | Control, repeatability, tunable workflows | Model/license terms per model (they’re not all the same) |
Formatting quirk confession: “price-ish” is still a scientific unit in my heart. 😌
A closer look: general-purpose chat assistants (the “talk it out” AIs) 🗣️
If your daily work is a mix of everything - writing a memo, thinking through strategy, planning a trip, summarizing a doc, drafting a reply - a general assistant is the easiest starting point.
What to look for:
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Instruction-following: does it stick to your format, or freestyle?
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Context handling: can it manage long chats, big documents, lots of constraints?
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Tooling: file upload, browsing/search, connectors, workflows
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Data controls: retention options, admin controls, training preferences (and whether those differ by plan)
A tiny test prompt:
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“Summarize this text in 5 bullets, then give 3 counterarguments, then rewrite it as a friendly email.”
If it can do that without getting unhelpfully smug, you’re in decent shape 🙂.
Also, keep one slightly paranoid habit: ask it to label assumptions. It’s like making it show its working, except it still sometimes… doesn’t.
A closer look: research and “answers with receipts” 🔎📚
When you want sources, use a tool that’s designed for it. Research-y AIs tend to:
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Search the web
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Provide citations/links
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Summarize multiple sources
But, and I say this with love: citations can still be misleading. An AI can cite a page that doesn’t support the claim, kind of like citing “a cookbook” to prove you’re a trained chef.
Try this verification prompt:
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“Give me the exact sentence in the source that supports each claim, and tell me if any claim is inference.”
If it struggles, that’s a signal: treat output as a lead, not a conclusion.
A closer look: writing, marketing, and the tone game ✍️🙂
Most “writing AIs” are capable. The difference is usually:
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Tone control (warm vs crisp vs persuasive vs formal)
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Consistency (does it drift halfway through?)
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Editing instincts (does it remove excess, or pad like it’s paid by the word?)
General tools get way better when you give:
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a sample
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a target audience
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“do/don’t” rules
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a hard word limit
Micro-prompt that saves time:
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“Write 3 versions: (1) blunt, (2) friendly, (3) executive. Keep each under 120 words.”
Most people only read the first two lines anyway… 😬
A closer look: coding and dev workflows 👩💻⚙️
For coding, integration matters almost more than raw intelligence.
IDE-first tools shine because they sit right where you work and nudge you in context. When choosing a coding AI, check:
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Language support: your stack, not the internet’s favorite stack
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Refactoring discipline: does it make the minimal safe change?
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Security posture: does it warn about secrets, injection risks, unsafe patterns?
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Org controls: policy, telemetry, what’s allowed on proprietary code
A good test:
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“Here’s a function and 3 failing tests. Fix it. Explain the minimal change.”
If it proposes rewriting everything, it might be clever… but exhausting.
A closer look: images, design, and “make it look real” 🎨🖼️
Image tools split into two vibes:
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Stylized art and creative visuals
Great when you want a mood, a vibe, an album-cover-ish thing that makes your brain go “ooh.” 😌 -
Flexible pipelines and customization
Great when you want control, repeatability, or a workflow you can tune. The tradeoff is usually setup complexity and more responsibility around rights/licensing.
Tiny creative test:
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“Create 4 variations of a minimalist icon set: cat, book, rocket, leaf. Keep consistent line weight.”
If it can keep consistency, that’s a win. If it makes the rocket furry… well. Artistic, I guess.
A closer look: privacy, security, and the stuff people ignore until it bites 🧯🔒
Here’s the awkward truth: your best AI choice might be the one with the clearest data controls, even if it’s not the flashiest.
Practical takeaways:
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If you’re handling sensitive business info, look for clear enterprise commitments, retention controls, and admin settings you can enforce. (This is exactly why the “business vs consumer” distinction matters.) [1][2][3]
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If you’re using tools that can browse or act on websites, be wary of prompt injection: instructions hiding in content that try to hijack what the AI does. Even “grounded” setups (like pulling in documents) don’t magically make that risk disappear. [4]
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If you’re using image tools, assume you must actively choose privacy, not just vibe your way into it. [5]
My imperfect metaphor of the day: using AI without checking privacy settings is like borrowing a stranger’s phone to message your boss. It might work! It might also be… a whole situation.
How to run a fast “Which AI?” bake-off at home 🍳
Instead of debating forever, test 3 tools with the same prompts.
Test 1: clarity and instruction-following
Prompt:
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“Make a 7-step plan. Each step must start with a verb. Add a risk note per step.”
Test 2: accuracy discipline
Prompt:
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“List what you know, what you’re unsure about, and what you would need to verify.”
Test 3: your real workflow
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Paste a real, dull task: a tangled email thread, a spec, a rough outline.
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Ask: “Summarize, decide next steps, draft my reply in my tone.”
Score each tool on:
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Output quality
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Editing needed
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Confidence vs correctness
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Ease of use in your daily tools
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Privacy comfort level
And yes, you can literally give it a score out of 10. Humans love numbers, even fake ones. 🙂
Quick wrap: Which AI? 🧠✅
If you’re still asking Which AI?, here’s the simplest way to land it:
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Need an all-purpose helper: start with a strong general assistant, then specialize later. If you’ll paste sensitive info, read the exact data terms for the plan you’re on. [1]
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Need research with sources: use a research-first tool and verify claims (ask it to prove each one from the source).
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Need Office or Google-doc superpowers: pick the AI built into the suite you already live in - and sanity-check permissions + admin controls. [2][3]
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Need coding help in your editor: use an IDE-integrated tool and apply the same rules you use for any dependency: policy, access, and review discipline.
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Need stunning images: pick the style you want, then read the visibility/privacy rules before you upload anything sensitive. [5]
The “best” AI is the one that fits your job, your risk level, and your patience. If a tool saves you an hour but costs you trust, that’s not a bargain… it’s a peculiar loan with interest 😬.
References
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OpenAI’s outline of enterprise privacy commitments, including data handling and retention controls. read more
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Google Workspace Admin Help page covering generative AI privacy guidance for Workspace, including admin considerations. read more
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Microsoft Learn documentation on data, privacy, and security practices for Microsoft 365 Copilot. read more
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OWASP GenAI Security Project entry on prompt injection risks and mitigations (LLM01). read more
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Midjourney documentation explaining how to keep creations private and manage visibility settings. read more