The Use Cases of
Artificial Intelligence
A deep dive into language models and their applications in research, productivity, and brainstorming techniques — with scored comparisons of five leading AI tools.
From the Internet Era to AI
The internet democratized access to information. With a few clicks, researchers could access global databases, peer-reviewed papers, and expert forums. But it came with challenges — information overload, irrelevant results, and hours spent sorting through content.
AI is transforming how we gather, filter, and analyze information. Tools like ChatGPT, Perplexity, and Claude don’t just retrieve data — they synthesize it, spot patterns, and adapt answers to your specific question or context.
What Is AI?
Artificial Intelligence (AI) refers to the simulation of human intelligence by machines. It allows computers to understand language, solve problems, and generate creative content. By processing large amounts of data with speed and precision, AI enhances human capabilities across research, design, and communication.
AI systems are built using a combination of models, data, and algorithms. A Large Language Model (LLM) is trained on vast amounts of text — books, websites, and documents — and uses Machine Learning to recognise patterns in how humans write and speak. It’s powered by Neural Networks which simulate how the brain processes information.
Key AI Terms Explained
GPT — Generative Pre-trained Transformer
A type of AI model that learns language by reading huge amounts of text. It predicts what comes next in a sentence — this is how it generates responses.
Large Language Model (LLM)
A model trained on billions of words from books, websites, and articles. It understands grammar, context, and meaning in natural language.
Neural Network
A computer system inspired by the human brain. Processes data in layers, with each layer extracting features to make decisions.
Machine Learning
A field of AI focused on developing systems that improve their performance over time as they are given more data.
How Large Language Models Work
Every time you prompt an AI, four things happen in sequence — from your raw text all the way to a coherent, contextually aware response.
Break Text Into Tokens
Text is segmented into smaller units like words or subwords, enabling the model to handle language in manageable pieces.
Convert to Numerical Vectors
Segments are transformed into numerical vectors for mathematical operations and pattern recognition.
Use Attention to Understand Context
Attention mechanisms evaluate the relevance of each segment, helping the model focus on what matters.
Train on Massive Text Data
The model learns from vast text sources, absorbing linguistic patterns to generate coherent responses.
Key Players in the AI Hardware Market
AI models don’t run on thin air. The hardware layer underpins everything — three companies dominate this space right now.
NVIDIA
The undisputed leader. Their GPUs are the industry standard for training complex AI models, backed by powerful performance and a mature software ecosystem.
Develops Tensor Processing Units (TPUs), custom accelerators highly optimised for neural network tasks and Google’s own cloud platform.
AMD
A major competitor in the GPU market offering powerful alternatives for AI and high-performance computing workloads.
The AI Ecosystem
The AI landscape spans foundation models, consumer apps, developer tools, enterprise solutions, and infrastructure companies.
Why These 5 AI Tools?
Each tool was selected for a distinct strength. Together they represent the current accessible AI landscape — from research-first to creativity-first, workflow-embedded to standalone.
Flexible idea generator with custom GPTs. Great for structured brainstorming and creative flows. GPT-3.5 free; GPT-4o on premium.
Search-focused AI with built-in citations and deep context. Ideal for fast, verifiable research summaries.
Strong at long-document reasoning and ethical writing. Known for long context windows, safer replies, and Constitutional AI.
Integrated with Google Workspace. Best for brainstorming from Docs, Gmail, or Slides. Formerly known as Bard.
Embedded into Microsoft 365 — Word, Excel, PowerPoint, Outlook, Teams. Drafts documents, analyses data, summarises meetings.
Founded 2021. Uses Constitutional AI. Backed by Google and Amazon. Designed for trustworthy AI in sensitive fields like research and law.
AI for Research
“AI tools summarise complex papers and cross-reference sources in seconds — no more keyword guessing.”
AI tools bring significant capability improvements to research workflows — whether you’re tracking competitors, analysing policy documents, or synthesising customer feedback at scale.
Key Research Applications
Trend Analysis: Track customer behaviour, industry changes, and competitor moves in real time.
Customer Insights: Summarise reviews, surveys, and social sentiment at scale.
Competitor Analysis: Use AI to compare pricing, features, and positioning across competitors.
Policy & Document Analysis: Text comparison, context awareness, and clear summaries of complex legislative or contractual documents.
Opportunity Detection: Spot market gaps and receive AI-generated suggestions for new offerings.
Research Scoring
Each tool scored 1–10 across five research dimensions. 10 = best in class.
| Criteria | Perplexity | ChatGPT | Claude | Gemini | Copilot |
|---|---|---|---|---|---|
| Source Transparency | 10 | 7 | 7 | 5 | 7 |
| Live Web Access | ✓ Full | Limited | Limited | ✓ Full | ✓ Full |
| Export & Usability | 10 | 8 | 6 | 6 | 6 |
| Depth of Response | 9 | 8 | 8 | 7 | 7 |
| Format & Structure | 9 | 8 | 8 | 7 | 8 |
AI for Brainstorming
For B2B applications, AI brainstorming tools can generate product concepts, content campaigns, customer personas, and brand naming — all tailored to your specific industry and tone.
What to Look for in a Brainstorming AI
Idea Diversity: Can it generate a wide range of creative, original, and unexpected ideas?
Follow-up & Refinement: Does it build on earlier responses and adjust based on feedback?
Creativity & Tone Control: Can you request playful, formal, edgy, or niche styles?
Context Awareness: Does it remember what you’ve discussed earlier in the session?
Clarity & Structure: Are suggestions organised in lists, themes, or actionable frameworks?
Brainstorming Scoring
Scored 1–10 across five dimensions. 10 = best in class.
| Criteria | Perplexity | ChatGPT | Claude | Gemini | Copilot |
|---|---|---|---|---|---|
| Idea Diversity | 8 | 9 | 8 | 7 | 7 |
| Creativity | 6 | 9 | 8 | 6 | 7 |
| Follow-Up Suggestions | 10 | 8 | 6 | 6 | 8 |
| Conversational Memory | 6 | 9 | 9 | 7 | 8 |
| Clarity of Output | 9 | 8 | 8 | 8 | 8 |
AI for Image Generation
For B2B organisations, AI image generation unlocks a faster path from concept to visual — cutting design dependencies for common internal and marketing assets.
B2B Applications
- Product mockups — visualise designs before committing to production
- Marketing content — create banners, ads, and landing page visuals
- Brand assets — generate icons and illustrations on demand
- Technical visuals — simplify complex concepts for presentations
- Training materials — enhance onboarding and client education
- Localisation — adapt images for different regions quickly
Must-Know Limitations
Not all AIs generate images. Claude, Perplexity, and free ChatGPT only understand images — they don’t create them.
Free tools are limited. Only Gemini and Microsoft Copilot (Bing) offer usable free image generation. ChatGPT requires a Plus subscription for DALL·E 3.
Editing is a premium feature. Only ChatGPT Plus with DALL·E 3 supports inpainting — editing specific regions of an image.
Prompt crafting matters. Quality depends heavily on how well you describe colours, lighting, angles, and mood.
Check commercial licences. Not all AI-generated images are cleared for commercial branding use — verify each tool’s terms.
AI for Coding
AI coding tools can dramatically accelerate development cycles, automate repetitive workflows, and make technical capabilities more accessible to teams without deep engineering resources.
Accelerate product development with AI-assisted coding and debugging
Automate internal workflows — reporting, inventory, task tracking
Generate personalised sales content and automate CRM actions
Build custom dashboards or client-facing web portals
Modernise legacy systems with AI-driven code translation
Auto-generate technical documentation and onboarding materials
Recommended Tools for AI Code Generation
Strong autocomplete and natural language coding in VS Code and JetBrains. The most widely adopted AI coding assistant.
Exceptional reasoning — best for long, complex coding tasks requiring deep analysis and multi-file understanding.
Deep integration with privacy-first design. Built from the ground up for AI-assisted development workflows.
Collaborative AI coding environment that runs in the browser — ideal for teams without local dev setups.
AI Use Cases at a Glance
Four categories. Two clear winners. One consistent takeaway: the right AI tool depends entirely on the job.
R Research
- Track competitors & industry moves in real time
- Summarise reviews & social sentiment
- Spot market gaps & new opportunities
- Analyse policy documents & contracts
B Brainstorming
- Generate tailored product & service ideas
- Auto-generate customer personas
- Draft industry-specific blogs, emails, ads
- Product names, taglines & brand stories
I Image Gen
- Visualise product mockups before production
- Generate brand assets on demand
- Create marketing visuals in minutes
- Adapt images for different regions
C Coding
- AI-assisted development & debugging
- Automate internal workflows
- Build client-facing portals & dashboards
- Generate technical documentation