Begin with the Right Use Cases

Generative AI can be applied to a wide range of use cases across various industries. Here are 12 key areas where GenAI can be particularly helpful.

Ideation

Generate new ideas or suggestions based on a simple request, helping to spark creativity and innovation. 

Example: A marketing team uses GenAI to brainstorm new product names, slogans, or campaign themes based on their target audience and brand identity.

Summation

Summarize lengthy information by providing long-form text, enabling quick comprehension of key points. 

Example: A legal professional uses GenAI to summarize a complex legal document, highlighting the most important clauses and provisions.

Revision

Revise and improve written content by providing suggestions and feedback, streamlining the editing process.

Example: A student uses GenAI to proofread and refine their essay, receiving suggestions for grammar, structure, and clarity improvements.

Translation

Translate text from one language to another with ease, facilitating global communication and collaboration. 

Example: A multinational company uses GenAI to translate internal documents and communications, enabling seamless collaboration among teams in different countries.

Research

Search for information on the internet and receive relevant results with related sources, saving time and effort in gathering data. 

Example: A journalist uses GenAI to quickly gather background information and sources for an article on a specific topic.

Recommendation

Receive personalized recommendations or suggestions based on prompted preferences, enhancing decision-making and discovery. 

Example: An e-commerce platform uses GenAI to provide personalized product recommendations to customers based on their browsing and purchase history.

Evaluation

Analyze and evaluate the quality of various inputs for better decision-making and assessment. 

Example:  A small marketing agency uses GenAI to evaluate and optimize their clients’ ad copy and landing pages. The AI system analyzes the text, images, and overall design of the ad creative and provides suggestions for improvement based on best practices and historical performance data. The agency’s creative team can then use these insights to refine their work and create more effective marketing materials for their clients.

Sentiment

Analyze the sentiment or emotion expressed in a given text or about a topic of interest, providing valuable insights into public opinion and customer feedback. 

Example: A customer service team uses GenAI to analyze customer reviews and social media mentions, identifying common issues and sentiment trends.

Problem Solving

Solve problems and get step-by-step instructions for any task you need to complete, offering guidance and support. 

Example: A DIY enthusiast uses GenAI to get step-by-step instructions for fixing a leaky faucet or troubleshooting a malfunctioning appliance.

Content Generation

Generate new content for anything you can imagine – text, image, music, and more, enabling rapid content creation and customization. 

Example: A social media manager uses GenAI to generate engaging social media posts for their brand’s social media channels.

Learning Assistance

Get information and explanations to gain an in-depth understanding of any subject matter, facilitating learning and knowledge acquisition. 

Example: A student uses GenAI to get detailed explanations and examples for complex mathematical concepts, enhancing their understanding of the subject.

Q&A / Roleplaying

Engage in conversation to encourage creative thinking, aid decision-making, practice pitches, and even explore and express thoughts & emotions, providing a versatile tool for various applications. 

Example: A sales professional uses GenAI to practice and refine their sales pitch, engaging in simulated conversations with potential customers to improve their persuasion skills.

When Not to Use Generative AI

While Generative AI offers numerous benefits and applications, there are certain use cases where it may not be the ideal solution:

• Analyzing Structured Data: GenAI models are primarily designed to work with unstructured data, such as text and images. For analyzing structured data, such as databases or spreadsheets, traditional data analysis tools and techniques may be more appropriate.
  
  
• Researching Real-Time/Current Events: Generative AI models are trained on datasets with specific cutoff dates, which means they may not have access to the most up-to-date information. When researching current events or real-time data, it’s essential to use platforms that incorporate real-time access to the internet or other live data sources.
  
  
• Use Cases Requiring 100% Accuracy: While Generative AI can produce high-quality outputs, it is not infallible. In situations where 100% accuracy is critical, such as legal documents or medical diagnoses, human expertise and review should always be involved to ensure the highest level of precision and reliability.