Which AI Platform Should You Use?
TLDR:Most people pick AI tools like they’re choosing toothpaste — whatever’s trending or looks shiny. Then they complain when it doesn’t “get” them or makes a confident mess of their work.The problem isn’t AI. It’s fit. Each platform has a different purpose, strength, and ceiling. Once you know what each one actually does well, you stop forcing the wrong tool into the wrong job and start getting real value.
If you’ve tried ChatGPT, you’ve probably also tried one of its cousins and wondered why they all give slightly different answers. Each AI system was built for a specific type of interaction, from creative brainstorming to legal analysis. Understanding that saves hours of trial, error, and subscription regret.
ChatGPT – The All-Rounder That Does (Almost) Everything
ChatGPT, developed by OpenAI, is the most versatile of the bunch. It handles writing, coding, research, and analysis with surprising coherence. You can feed it text, images, or even audio, and it’ll respond in kind. Its plugin ecosystem and memory features mean it can recall context over time, automate tasks, and even simulate a personalised assistant.
When to use it:
Use ChatGPT when you need multimodal capabilities — text, images, code, or voice — and when you want to automate thinking-heavy but repeatable work. It’s built for brainstorming, content creation, research, data analysis, and light coding.
Practical use cases:
- Writing reports, blog posts, or marketing material.
- Summarising research or drafting complex proposals.
- Automating customer emails or internal updates.
- Debugging or generating code snippets.
Strengths:
- Industry-leading support for text, image, and voice inputs.
- Expanding plugin ecosystem with thousands of third-party integrations.
- Adaptive tone, capable of handling creative or technical work equally well.
- Memory (on premium plans) that lets it remember your style or context.
Weaknesses:
- Key features like memory, plugins, and GPT customisation are paywalled.
- Accuracy dips in niche or highly technical domains.
- Overconfidence: it will answer every question, even when it shouldn’t.
Best practice tip:
Create a custom GPT for your business or workflow with explicit instructions and a private knowledge base. It’s the difference between a one-size-fits-all assistant and one that actually understands your work.
Gemini – The Workspace Native
If you live in Gmail, Docs, or Sheets all day, Gemini is the AI that sits quietly inside your browser and finishes your sentences before you do. Developed by Google, it’s less about creativity and more about productivity. Its strength lies in real-time collaboration, document handling, and integration with everything in Google’s ecosystem.
When to use it:
When you need live access to files, data, and shared documents. It shines during group projects, report writing, and data prep, where multiple people need context at once.
Practical use cases:
- Drafting and editing Docs collaboratively.
- Summarising Gmail threads or attachments.
- Building data-driven Sheets or presentations.
- Managing projects or tasks across Workspace tools.
Strengths:
- Tight integration with Drive, Calendar, and Gmail.
- Real-time internet access and fact updates via Google Search.
- Handles text, images, and data tables in one interface.
- Excellent for asynchronous collaboration and version control.
Weaknesses:
- Limited usefulness outside the Google ecosystem.
- Some features remain experimental or inconsistently reliable.
- Slower performance with large or complex documents.
Best practice tip:
Use Gemini directly inside Docs or Sheets. Avoid switching tabs to external tools, it’s built to make Google users faster, not to replace standalone LLMs.
Claude – The Long-Form Thinker
Claude, from Anthropic, focuses on reasoning, clarity, and safety. It’s less about personality and more about precision. Claude can read, process, and summarise extremely long documents — entire policy drafts, legal contracts, or academic papers — while maintaining factual consistency.
When to use it:
Use Claude when you need an AI that can digest complexity without cutting corners. It’s built for research, policy, and compliance — anywhere you need your words to stand up to scrutiny.
Practical use cases:
- Analysing 100-page reports or tender documents.
- Drafting defensible policy papers or governance reviews.
- Extracting key insights from academic or technical research.
- Simplifying dense material for public or internal audiences.
Strengths:
- Can handle 200k+ tokens of context (far longer than most AIs).
- Excellent reasoning, logic, and ethical restraint.
- Consistent tone — calm, structured, and clear.
- Reliable for high-stakes content that needs accuracy.
Weaknesses:
- No visual or audio capability.
- Tone can feel formal or overly cautious.
- Less useful for creative or fast-moving content.
Best practice tip:
Use Claude to review or simplify complex material. It’s ideal when accuracy matters more than speed or personality.
Grok – The Real-Time Commentator
Built by X (Twitter), Grok’s superpower is immediacy. It’s tuned for live data, trending topics, and cultural moments. Instead of perfect paragraphs, it produces fast, conversational takes that sound human — because it’s drawing from the same real-time feeds people are reacting to.
When to use it:
When you need quick commentary, summaries of live events, or trend-based content that sounds current. It’s the tool for social-first brands, journalists, and community managers.
Practical use cases:
- Monitoring brand mentions or industry chatter.
- Creating on-brand posts for social media.
- Writing witty replies or summaries of breaking news.
- Tracking sentiment and emerging public conversations.
Strengths:
- Direct access to X’s live data.
- Engaging, informal writing style that fits social tone.
- Fast and context-aware in real time.
- Great for audience engagement and reactive content.
Weaknesses:
- Limited to the X ecosystem.
- Not built for structured or analytical tasks.
- Early-stage toolset compared to other major platforms.
Best practice tip:
Use Grok to track or respond to conversations as they happen. It’s a tone tool, not a research engine.
Perplexity – The Verified Researcher
Perplexity feels like the adult in the room and is hands down our favourite at AI Strategy Consulting. Every claim it makes comes with a source. It combines real-time web results with concise synthesis, so you get short, citation-linked answers you can trust.
When to use it:
When accuracy and traceability are non-negotiable — compliance reports, academic writing, or any work that will be externally reviewed.
Practical use cases:
- Fact-checking or summarising across multiple sources.
- Creating annotated bibliographies or research briefs.
- Replacing traditional search with verified synthesis.
- Reviewing competing claims or policy arguments.
Strengths:
- Every output links to its sources.
- Combines live search with structured summarisation.
- Reduces hallucination risk through evidence retrieval.
- Balanced tone suitable for professional outputs.
Weaknesses:
- Limited creative or narrative flexibility.
- Dependent on web data quality.
- Not suitable for marketing or tone-based writing.
Best practice tip:
Use Perplexity when you need credible evidence, not personality. It’s your best option for research, due diligence, or compliance tasks.
DeepSeek – The Efficient Workhorse
DeepSeek, developed in China, is the quiet performer. It’s optimised for technical workloads and efficiency at scale. While Western tools chase creativity and UX, DeepSeek focuses on speed, cost, and multilingual capabilities, particularly for enterprises handling large data volumes or coding tasks (security concerns pending).
When to use it:
When you need reliable, affordable compute power for technical work, or when your project involves multiple languages or heavy data processing.
Practical use cases:
- Generating or debugging code in various languages.
- Running large AI workloads or analytical tasks.
- Translating or localising content efficiently.
- Supporting internal technical teams at scale.
Strengths:
- High performance for coding and data tasks.
- Significantly cheaper than Western models.
- Lightweight, fast, and scalable for enterprise use.
- Effective for multilingual workloads.
Weaknesses:
- Limited ecosystem and developer support outside Asia.
- Less capable in creative or conversational tasks.
- Lower visibility globally, so fewer integrations.
Best practice tip:
Use DeepSeek when you need scale without breaking the budget. It’s best suited to technical teams, not content creators.
If you look closely, these six tools represent different layers of the AI stack:
- ChatGPT covers breadth and creativity.
- Gemini handles collaboration and productivity.
- Claude ensures accuracy and reasoning.
- Grok captures live social context.
- Perplexity manages verification and sourcing.
- DeepSeek delivers scalable technical execution.
Together, they map the full range of what LLMs can do today from imagination to implementation. The key is matching capability to context.
FAQ
Q: Which one should I start with?
A: ChatGPT. It’s the most accessible and has the broadest capability for general use.
Q: Which is safest for work that could go public or legal?
A: Claude. It prioritises accuracy, ethics, and reasoning depth.
Q: Which integrates best with existing tools?
A: Gemini, if you’re deep in Google Workspace. Otherwise, ChatGPT for custom workflows.
Q: Which one can actually cite its sources?
A: Perplexity. It’s built to show where information comes from, not just summarise it.
Q: Which tool handles multilingual or technical data best?
A: DeepSeek. It’s designed for performance and scalability.
Q: What’s the best combo to use together?
A: ChatGPT for creation, Perplexity for verification, and Claude for analysis. That trio covers 90% of business use cases.