Suppose you have successfully established a robust data governance framework, implemented effective data cleaning strategies, and made data quality a priority. Now, you are ready to take the next step in your generative AI (GenAI) journey. The critical step now is to identify your use case.
What is a Use Case?
A use case is a detailed scenario that describes how a user interacts with a system to achieve a specific goal. It is crucial in fields like software engineering, user experience design, and requirements analysis because it:
- Helps teams understand and document what the system must do from the user's perspective.
- Guides developers in creating software that meets user needs.
- Focuses on the interactions between the system and external entities, including users and other systems.
Use cases are also known by other names like user scenarios, user stories, user flows, customer journey maps, business scenarios, workflows, or customer experience maps. These terms are often used interchangeably.
Defining a Use Case for GenAI
To define a use case for GenAI, start by identifying a specific problem or opportunity that can be addressed by generating unique content or data. Here are some steps to guide you:
- Identify a problem or opportunity: Look for tasks that are repetitive, require pattern recognition, or involve content generation where human capacity is limited. This could be a business challenge, like automated claims processing, fraud detection, or risk assessment, or a creative challenge, like redesigning service delivery models.
- Conduct workshops: If unsure where to start, consider conducting workshops or brainstorming sessions with stakeholders to generate ideas around content creation, data augmentation, or automation. Prioritize the most promising use cases and refine your ideas based on stakeholder feedback.
- Determine your desired outcome: Clearly define what you aim to achieve with the use case. Engage stakeholders regularly to gather feedback and ensure the solution meets their needs.
- Explore industry applications: Research how GenAI is being used in your industry or similar sectors. Look for success stories, case studies, and emerging trends to understand better how you might apply these tools in your context.
- Evaluate data availability and quality: GenAI models require significant data for training. Assess the quality, quantity, and relevance of your data. Determine if you have access to necessary datasets, or if you need to collect or create new data.
- Consider the user experience: Think about how users will interact with the GenAI system. Will they provide prompts, upload data, or engage directly with generated content?
- Collaborate with experts: GenAI is a complex and rapidly evolving field. Collaborate with experts, researchers, or specialized companies to ensure you have the appropriate expertise and resources.
High-Level GenAI Themes
Here are some overarching themes that use cases tend to fall into:
- Classifying: Automatically categorizing data into predefined groups or classes based on learned patterns from training data.
- Editing: Automatically revising text to improve clarity, correctness, or adherence to specific style guidelines.
- Summarizing: Condensing large volumes of text, audio, or video into a concise form that captures the essential information or highlights.
- Responding: Interpreting and responding to user queries by generating relevant and accurate answers based on a wide range of data sources.
- Drafting: Automatically generating text or content drafts based on input parameters and training data.
Common Use Cases for Business Executives
There are many potential use cases for GenAI in business, and the specific use cases that are most relevant for business executives will depend on the industry, organization, and goals of the executive.?
- Data Analysis and Decision Support: GenAI excels at analyzing vast amounts of data, identifying patterns, and making predictions, enhancing strategic planning and real-time decision-making.
- Enhanced Content and Communication: Improve content creation for marketing materials, customer communications, and language translation.
- Operational Efficiency and Automation: Automate routine tasks to boost efficiency in operations like manufacturing, invoicing, and onboarding.
- Customer Insights and Support: Gain deeper insights into customer preferences and enhance customer interactions.
- Innovation: Foster innovation by aiding the development of creative concepts, new products, prototypes, services, and business strategies.
- Personalized Learning: Offer personalized learning plans based on performance data to improve employee skills.
By leveraging generative AI, business executives can enhance the efficiency, scalability, and effectiveness of their operations, gaining a competitive edge in their industry.
Final Thoughts
Establishing a well-defined use case is a pivotal next step in your generative AI roadmap. By focusing on specific goals such as classification, editing, summarization, answering questions, or drafting, you can harness the power of GenAI to address real-world problems and optimize operations within your organization. Your use case adds a layer of strategic value, driving towards more innovative, efficient, and personalized solutions. As you continue to explore and implement these use cases, keep in mind the importance of continuous engagement with stakeholders and regular assessment of data quality and system performance to ensure your GenAI initiatives deliver tangible benefits.
Build a GenAI Roadmap for Your Organization
At Blue Orange Digital, we’ve created a roadmap to help organizations adopt GenAI. I’ll build on this article over several weeks with an overview of that roadmap.
If you’d like to help in creating your bespoke GenAI roadmap, please reach out to schedule a free 30-minute workshop.
