Welcome to the forefront of conversational AI as we explore the fascinating world of AI chatbots in our dedicated blog series. Discover the latest advancements, applications, and strategies that propel the evolution of chatbot technology. From enhancing customer interactions to streamlining business processes, these articles delve into the innovative ways artificial intelligence is shaping the landscape of automated conversational agents. Whether you’re a business owner, developer, or simply intrigued by the future of interactive technology, join us on this journey to unravel the transformative power and endless possibilities of AI chatbots.
ChatGPT can support diverse commercial tasks involving text, images or data. Though It is a powerful data processor, it typically requires human supervision due to its hallucinations.
ChatGPT hit 900 million weekly active users in early 2026, roughly 10% of the world’s population. OpenAI reached $10 billion in annual recurring revenue by mid-2025.
But what are those 900 million people doing with it?
OpenAI and Harvard economist David Deming analyzed 1.5 million conversations to find out. This is the largest study of actual consumer AI usage ever released. Combined with real company examples and usage data through January 2026, here’s what ChatGPT actually gets used for.
30% of usage is work-related, 70% is personal. Both categories keep growing.1
ChatGPT has various applications that are useful to consumers and businesses. We explain the top 50 ChatGPT use cases. If you want to use your own company’s data for generative AI, you can look into training or fine-tuning LLMs.
ChatGPT can effectively assist in handling structured tasks that require consistent formatting, predefined outputs, or repetitive workflows. This capability is particularly beneficial when accuracy, clarity, and adherence to a set structure are critical.
ChatGPT, as a language model, can be used for a wide range of text-based use cases. Some of the most common use cases of ChatGPT include:
ChatGPT generates drafts, outlines, and complete articles. Most people don’t publish AI output directly; they use it as a starting point, then heavily edit for voice and accuracy.
Reality check: The generated content is generic. You’ll spend as much time editing as you would writing from scratch unless you’re very specific with prompts.
Figure 1. Example of a content creation using ChatGPT with the prompt “Once upon a time”
E-commerce teams use ChatGPT to write product descriptions at scale. Feed it product specs, get descriptions back.
Where it works: Standardized products with clear specifications (electronics, appliances, basic apparel)
Where it fails: Products requiring nuance, emotion, brand voice (luxury goods, artisanal items, complex B2B solutions)
ChatGPT drafts tweets, LinkedIn updates, and Instagram captions. Companies like Koo integrate it directly into their platforms.
Most common use: Repurposing long-form content into social snippets.
“Give me 10 business ideas for [industry/problem]” is one of the most common prompts.
Useful for: Brainstorming, getting unstuck
Not useful for: Actual business viability (it can’t assess market dynamics, competition, or your specific capabilities)
ChatGPT helps writers brainstorm plots, develop characters, write scenes.
Runway (creative AI platform) uses GPT models to generate video scripts for social media marketers who need engaging content quickly.
The creative limitation: AI writing is competent but forgettable. It doesn’t take creative risks, make surprising connections, or develop unique voice.
ChatGPT translates text between languages with reasonable accuracy for common language pairs.
Real examples:
Spotify uses ChatGPT to provide customer support in 60+ languages. Customers ask about playlists, features, and account issues. ChatGPT translates and responds in their preferred language.2 .
Duolingo leverages ChatGPT to answer customer inquiries in 30+ languages. Users worldwide communicate about courses and app settings without language barriers.
Where it works: Customer support, basic communication, informal translation.
Where it fails: Legal documents, medical information, literary translation (nuance gets lost).
ChatGPT powers chatbots for customer service, sales, and support with human-like responses.
Octopus Energy uses GPT-powered chatbots to handle 44% of customer inquiries. This automation replaced approximately 250 support staff. The system handles billing to account management.
The limitation: Chatbots fall apart when empathy, judgment, or nuanced understanding is required. “I understand you’re frustrated,” from a bot rings hollow.
Businesses feed company data to ChatGPT using retrieval-augmented generation (RAG). Employees can then query private company information using natural language.
Example: “What was our Q3 revenue in EMEA?” pulls from internal databases.
The complexity: RAG systems require significant setup. You need properly structured data, vector databases, and integration work. This isn’t plug-and-play.
For further details, see our article: How to Use ChatGPT for Business
ChatGPT writes code for simple or repetitive tasks, such as file I/O, data manipulation, and database queries.
The reality: It’s helpful for boilerplate and common patterns. For complex logic, the generated code often contains subtle bugs or fails to handle edge cases.
Figure 2. ChatGPT writing code for a comment
ChatGPT proposes possible causes of errors and suggests solutions.
Where it helps: Syntax errors, common mistakes, and suggesting debugging approaches
Where it doesn’t: Complex logical errors, performance issues, architecture problems
Figure 3. ChatGPT helps with debugging code
ChatGPT suggests the next lines of code, recommends structural improvements, generates documentation templates, and produces code snippets.
Developer adoption: By the end of 2025, roughly 85% of developers regularly use AI tools for coding. However, 79% still review and modify AI-generated code before using it.
Figure 4. ChatGPT refactors the code it provides as an example
Figure 5. ChatGPT provides example code documentation for a Python function that sorts a list of numbers in ascending order
Figure 6. ChatGPT provides an example code snippet
ChatGPT explains syntax, functions, and programming concepts particularly useful for beginners learning new languages.
The advantage over Google: Interactive follow-up questions. You can ask “why” repeatedly until you understand.
Figure 7. ChatGPT explains the question, “What is object-oriented programming, and how does it work?”
OpenAI rolled out multimodal capabilities in September 2023. ChatGPT can now process images, audio, and video.3
ChatGPT classifies images into categories: landscapes, animals, and objects.
Applications: Medical imaging (classifying X-rays), e-commerce (categorizing product images), and content moderation
Recognizes specific objects in images: faces, cars, and everyday objects.
Used in: Security (facial recognition), autonomous vehicles (recognizing pedestrians), retail (analyzing shelf inventory)
ChatGPT converts:
Limitation: Accuracy drops with accents, technical jargon, and cross-talk.
ChatGPT translates customer messages and generates responses in different languages, enabling effective communication across language barriers.
Real performance:
ChatGPT trains on customer data (past purchases, chat history, feedback) to create personalized profiles.
Where this works: Recommending relevant products, referencing past interactions, tailoring communication style
Where this fails: Complex situations requiring human judgment about what the customer actually needs vs. what they’re asking for
ChatGPT detects and replies to common complaints: product quality issues, shipping delays, billing errors.
Reality: Handles ~70-80% of routine complaints. The other 20-30% require human intervention for complexity or emotional intelligence.
ChatGPT designs custom email templates using customer data, creating emails personalized to specific interests and requirements.
ChatGPT identifies emotions in customer messages: happiness, sadness, anger, and frustration. Responses are tailored to the emotional state.
Application: Identifying unhappy customers before complaints escalate.
For more information on sentiment analysis comparison on AI-tools, read Sentiment Analysis Benchmark Testing: ChatGPT, Claude & DeepSeek.
ChatGPT generates responses to customer reviews and addresses frequent inquiries by training on FAQ pages and knowledge bases.
Best practice: Human review before posting, especially for negative reviews.
Web contains the largest dataset, and ChatGPT facilitates web data collection. Use cases include:
ChatGPT writes Python code for scraping websites using BeautifulSoup, Scrapy, or Selenium. Makes it easier for non-developers to gather web data.
ChatGPT handles data cleaning and processing tasks.
Where it helps: Standardizing formats, removing duplicates, basic transformations
Where it doesn’t: Complex data validation, understanding domain-specific data quality issues
ChatGPT develops lesson plans, activities, and projects aligned with curriculum guidelines. Creates presentations, worksheets, and quizzes.
The concern: Teachers worry about over-reliance. ChatGPT should supplement, not replace, pedagogical expertise.
ChatGPT proofreads, edits, and provides feedback on written work.
Limitation: It catches grammar and structure issues, but doesn’t understand sophisticated argumentation or subject-specific writing conventions.
ChatGPT evaluates essay content, structure, and coherence. Offers feedback on grammar, spelling, and syntax.
Critical caveat: Should NEVER be the sole grading mechanism. Use it to create rubrics or provide initial feedback, not final grades.
ChatGPT aids in course content creation, organization, and structure:
ChatGPT answers questions, helps with problem-solving, reinforces concepts, and improves writing skills.
Academic integrity concern: Schools are split on ChatGPT use. Some ban it, others teach responsible usage.
Student adoption: 60% of college students use ChatGPT as of 2025.
ChatGPT supports research by:
Important: Always verify information. ChatGPT sometimes fabricates citations that look real but don’t exist.
ChatGPT offers translations, grammar explanations, vocabulary practice, and conversation simulations.
Advantage over traditional tools: Interactive practice with instant feedback.
Figure: ChatGPT creates a weekly schedule for language learning practices
AI-generated texts for content marketing: emails, social posts, blog articles, scripts for advertising.
Effectiveness: Content marketers report 2-3x output increase but note that AI content requires significant editing for brand voice.
ChatGPT generates personalized content considering customer preferences, past behavior, and demographics.
Result: Higher engagement and conversion rates when properly implemented.
ChatGPT analyzes customer data (search queries, social media interactions, past purchases) to identify patterns and trends.
Use case: Understanding customer segments before launching campaigns.
ChatGPT crafts engaging product descriptions aligned with the target audience’s interests.
E-commerce adoption: Widespread for products with clear specifications. Less effective for products requiring emotional selling.
ChatGPT incorporated into chatbots delivers prompt, personalized support. Addresses inquiries, offers technical support, troubleshoots issues.
ChatGPT helps with:
Topic Ideas: Generates relevant keywords, analyzes competitor content, suggests topics based on trends
Keyword Research: Generates keywords, identifies trends
Titles: Creates SEO-friendly titles (60-70 characters, incorporating keywords, attention-grabbing)
Search Intent Grouping: Analyzes search queries and categorizes by user intent
Content Structure: Produces outlines and organization methods
Meta Descriptions: Generates concise page summaries for search results
Sitemap Codes: Generates XML files listing website pages
Reality check: SEO professionals report that 86% integrate AI into their strategy, but they emphasize that AI-generated content still requires human editing for quality and originality.
HR departments use ChatGPT to generate interview questions pertaining to job positions, evaluating qualifications, skills, and experience.
Where it helps: Creating diverse question sets, avoiding repetitive questions
Where it doesn’t: Nuanced behavioral questions requiring a deep understanding of company culture
ChatGPT generates onboarding materials: training videos, scripts, handbook content, and documentation.
ChatGPT generates job descriptions that reflect required skills and qualifications.
Common use: Drafting initial JD, then HR refines for company-specific needs.
Fine-tune ChatGPT with company policies, and it can answer employees’ HR policy questions.
Implementation note: Requires careful setup to ensure accuracy. Wrong answers to policy questions can create legal issues.
Despite reaching millions of users, ChatGPT has clear limitations:
ChatGPT offers businesses a versatile tool for enhancing operations in customer service, content creation, internal communication, and more. However, when adopting AI tools like ChatGPT, organizations must consider potential challenges, such as data privacy, accuracy, and integration requirements.
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Cem Thank you for the ideas. I retired from software QA and now mentor young people in software and IT. I am new to ChatGPT and was casting about for ways to integrate it into my work. Somehow I never thought of using ChatGPT to suggest debugging. I am teaching a jr. high student Python and will work it into our sessions. Another person was laid off from a management position in manufacturing and is looking at career changes. I have been funneling ideas and information to him, encouraging him to get on board with ChatGPT. Best wishes. Joel
Sounds great Joel!
