Applications by domain, technique and complexity level, including practical examples
Generative AI (GenAI) is no longer future music; it is a game-changer for organizations in every sector. From content creation to customer interaction, from internal analytics to autonomous processes, the applications are growing rapidly.
In this blog you will discover the most promising GenAI use cases, structured by technique, by complexity level and by domain. Including concrete practical examples of how we at Data Science Lab see how other organizations create value with GenAI.
GenAI use cases based on different techniques
In addition to applications by domain or complexity, it is also excellent to categorize GenAI by technology or functionality. Within organizations, we increasingly see specific GenAI techniques being used to speed up internal processes, increase the quality of analyses or streamline communication. Below we explain the most important techniques, with concrete applications that we implement at Data Science Lab.
Smart analysis and classification
One of the most powerful applications of GenAI lies in processing and interpreting unstructured data, such as customer feedback, complaint forms or internal memos. Thanks to automatic categorization, large amounts of text are grouped by topic, while sentiment analysis provides insight into the tone or emotion of messages. This helps organizations respond faster to signals from the market or internal bottlenecks. Where before you had to manually read, sort and interpret, GenAI can now deliver actionable insights in seconds.
Applications:
- Automatically categorize feedback by theme or topic.
- Sentiment analysis on customer or employee data.
- Prioritize complaints by urgency or content.
- Tone-of-voice checker for internal and external communications.
Impact:
Consistent, scalable analysis of large amounts of text without manual work.
Chatbots (internal & external)
Chatbots are perhaps the best-known GenAI application. Both internally and externally, they provide immediate support to employees and customers 24/7. Internal chatbots can give employees quick answers to questions about HR policies, IT systems, legal guidelines or onboarding processes, for example. Instead of searching through manuals or waiting for colleagues, employees get fast, accurate and contextual answers.
Externally, chatbots provide efficient customer service, personalized recommendations and proactive follow-up. In both cases, it not only increases customer or employee satisfaction, but also greatly reduces pressure on support departments.
Internal chatbots:
- HR support chatbot
- IT support chatbot
- Legal and policy chatbot
- Onboarding and training assistant
- Internal knowledge base chatbot (for searching documents, minutes or policies)
External chatbots:
- FAQ and customer service chatbot
- Chatbot for booking appointments
- Technical support chatbot
- Review collection and customer feedback chatbot
- Chat-driven advisor or recommendation bot
Impact: Higher customer and employee satisfaction, good accessibility, lower workload and faster response times.
Summarize and analyze information
GenAI excels at processing long or complex documents and files. Customer files, reports and compliance documents are reviewed and summarized in seconds. This allows you to make faster decisions, identify risks and eliminate time-consuming manual steps. You instantly have the core information, you can compare and detect discrepancies and risks.
Applications:
- Summarize and analyze customer or patient records
- Filtering resumes and cover letters
- Compliance and regulatory checks
- Gain insights from customer feedback or open field surveys
- Extraction of key information (amounts, dates, parties involved)
- Generating management summaries
- Structuring reports
- Trend analysis based on unstructured text
Impact: Make complex information understandable quickly, with precision and consistency.
Generative text: from idea to publication
The name says it all: generative AI generates. For text in particular, this offers tremendous opportunities. From marketing content to legal documents: GenAI helps create faster and more consistently. But think also about filling in standard documents, such as contract templates, which is a lot more efficient. All fully in line with your own tone-of-voice and other style guidelines.
Applications:
- Generate blogs, articles and SEO texts
- Set up social media posts by target audience
- Personalized newsletter emails or customer offers
- Auto-fill reports, quotes or contract templates
- Standardize legal or financial documents
- Generating internal communication messages
Impact: Efficient content creation at scale, while maintaining quality and recognizable tone-of-voice.
Data analysis: interactive and accessible
GenAI makes data analysis smarter and more accessible. Not only structured data (e.g. from dashboards or CRM systems) is analyzed, but also unstructured data such as customer reviews, minutes or emails are included. Combining both data types creates deeper and contextual insights. This allows organizations to predict trends, detect risks and better understand customer behavior. Where previously much expertise and tooling was required, especially with quantitative analysis, it can now be done through conversation. This makes data analysis a lot more accessible.
Applications:
- Trend analysis on structured data
- Combining different sources (e.g., sales data with customer reviews)
- Detecting anomalies or risks (e.g., churn signals)
- Analysis of behavior or preferences based on multiple touchpoints
Impact: More accessible and interactive data analysis, faster decision-making and better predictions.
These techniques can provide value separately, but often deliver the most impact when combined; within a smart workflow or integrated environment. Our experience at DSL shows that even relatively simple applications quickly provide marked improvements in efficiency, quality, customer experience and deliver impressive ROI.
GenAI at three levels of complexity
Not every GenAI solution is equally complex. Depending on your purpose, infrastructure and maturity, you can deploy GenAI at different levels. From simple text generation to having it act autonomously within your systems. At DSL, we distinguish three levels of complexity. Below we explain the levels for LLMs with examples and applications.
1. Basic LLM – Text-level efficiency (without data enrichment).
This is the most accessible way to apply GenAI. That’s because you use it without links to external systems or data. The LLM works purely on the basis of prompt input and training data. The applications are broad and immediately applicable.
Applications:
- Generate texts (e.g., blogs, emails)
- Summarize (e.g., of documents and minutes)
- Translate
- Sentiment Analysis
- Writing or reviewing code
- FAQ chatbots based on general knowledge
For whom. Ideal for organizations that want to get started with GenAI in a low-threshold way without large IT investments or data links.
2. Intermediate LLM – Smart interaction with external sources.
At this level, GenAI is enriched with external or internal sources. Using techniques such as Retrieval-Augmented Generation (RAG) or access to databases, systems or individual documents, the AI provides context-specific answers. The output becomes more accurate, reliable and relevant.
Techniques:
- Memory (remember context)
- Retrieval-Augmented Generation (RAG) (retrieving and passing along relevant pieces of context)
- Generate and execute SQL queries
- Web search integration for up-to-date information
- Linking to CRMs, ERPs or data warehouses
Applications:
- Customer support based on internal knowledge
- Generating insights from internal documents
- Automatic reporting with data from BI tools
- Access personalized dashboards or analytics via natural language
For whom. For organizations that want to use GenAI to optimize internal processes or enable personalized interaction with customers.
3. Advanced LLM – Autonomous and agentic action.
This is where GenAI goes a step further. The model independently performs actions in systems based on context and instructions. This is the rise of agent-based AI, in which tasks are automated with minimal human intervention.
Applications:
- Automatically classify, forward and resolve complaints
- Database autonomous updating
- Schedule appointments in systems (such as calendars or scheduling systems)
- Fill out forms or submit applications based on context
- Combine multiple tools into one automated workflow (e.g., read > interpret > report > send)
For whom. For forward-thinking organizations looking to automate routine tasks with minimal human intervention. Seeking operational efficiencies and making room for strategic work.
Each level brings its own requirements in terms of security, governance and integration. Our experience at DSL is that it pays to start small (e.g. basic or intermediate), learn what works, and then scale up to more advanced applications in a controlled manner.
GenAI in practice: applications by domain
GenAI is impacting virtually every domain. From faster customer responses to automated analytics or personalized content creation. The technology is not only smart, but also scalable. Below is an overview of common applications by domain, including concrete use cases we are realizing at DSL.
Customer Service
The use of GenAI in customer contact is making a world of difference. Think of chatbots that are available 24/7, can communicate multilingually and have direct access to internal knowledge sources. Customer questions are answered within seconds, complaints automatically analyzed for urgency, sentiments automatically detected and urgent issues immediately forwarded to the right employee. Customer satisfaction increases while pressure on service departments decreases.
Applications:
- 24/7 multilingual chatbots
- Sentiment analysis on customer feedback
- Automatic prioritization and routing of complaints
Impact: Shorter wait times, quick response, reduced pressure on support teams and higher customer satisfaction.
E-commerce
E-commerce is all about speed and personalization. GenAI automatically generates product descriptions, personalizes recommendations based on behavior, prices are dynamically adjusted to supply and demand. These are all examples where customers feel that the webshop really understands them.
Applications:
- Personalized product recommendations
- Automatically generated product descriptions
- Virtual fitting rooms (try-ons) or chatbot stylists
Impact: Higher conversion rates, increased customer loyalty and a smoother customer experience.
Healthcare
GenAI helps healthcare professionals spend more time with patients by easing administrative tasks. Consultation reports are automatically summarized, medical reports are generated, and patients are supported via AI-driven chatbots that guide through frequently asked questions or medication instructions.
Applications:
- Summarizing consultations or records
- Generate medical reports
- Diagnostic AI support
- Chatbots for patient communication
Impact: More efficient care, less administration, better patient experience.
Education & E-learning
GenAI makes education more accessible, efficient and personal. Teaching materials are tailored to the student’s knowledge level and learning style. Quizzes are automatically generated and chatbots act as personal tutors. This technology also offers tremendous opportunities for onboarding and internal training.
Applications:
- Personalized learning materials
- Onboarding and training assistant
- Quizzes and test generation
- Study help chatbots
Impact: Education that grows with user learning needs, efficient knowledge transfer and scalable training programs.
Legal Services
Legal departments and offices process large volumes of documents. GenAI accelerates document analysis, supports legal investigations and helps with compliance issues.
Applications:
- Automatic contract generationSummarization of legal documents
- Faster legal research
- Automating compliance checks
Impact: Time savings, fewer errors, faster decision making and better informed legal services.
Human Resources
In HR, GenAI helps with recruitment, onboarding and diversity. It screens resumes, writes job postings and helps reduce bias in recruitment. Onboarding materials can also be personalized.
Applications:
- CV analysis and bias detection
- Generating job postings
- Personalized onboarding materials
Impact: More efficient recruitment, more inclusive HR policies and better employee experience.
Marketing & advertising
GenAI accelerates content creation and makes personalization scalable. A/B test variations are generated in minutes, SEO blogs are written, ads are visually designed and emails are automatically personalized at the audience level with their own unique message.
Applications:
- Personalized ads
- Content creation (textual and visual)
- A/B testing variations
- SEO-optimized blogs
Impact: GenAI helps marketers focus on strategy and creativity, while execution is largely automated.
Real Estate
In real estate, GenAI is making the work of brokers, asset managers and leasing organizations more efficient and customer-focused. Think of property descriptions automatically generated from property data, and virtual assistants that simulate tours or answer questions from interested buyers or tenants.
Applications:
- Property text generation
- Virtual tours or AI chat for questions
- Market analysis based on trends
Impact: Improves customer engagement and operational efficiency.
Fashion & Design
Fashion companies can use GenAI to detect trends based on social media, customer data and sales statistics. Those insights can lead to new collections that better reflect market needs. They can also create visual designs, such as for online previews or customized garments, and generate campaign materials and product photos for your online store. It’s all possible with AI image generation.
Applications:
- Trend forecasts
- Visual design generation
- Generation of campaign materials and product photos
- Virtual previews or styling assistants
Impact: Faster response to trends, less waste, strong customer loyalty.
Insurance
In the insurance industry, GenAI speeds up repetitive processes, from claim processing to policy recommendations. GenAI offers huge efficiency gains here. By intelligently automating these processes, insurers can work faster and more consistently, while customers benefit from faster service and clearer communication.
Applications:
- Automatically review and process claims
- Personalized product and policy recommendations.
- Summarizing policies or claims reports
Impact: Lower costs, faster service, accelerated workflows and improved user-experience.
Ready to deploy GenAI?
The applications are there. The technology is mature. And the opportunities are at hand. Whether you want to work more efficiently, communicate more customer-focused, or innovate strategically in a data-driven way. GenAI offers proven value at every level of complexity and in every domain.
At DSL, we help you go from idea to AI implementation. Whether you are just starting out or already have concrete ambitions. We help organizations from orientation to realization: with concrete use cases, scalable solutions and guidance from experienced AI consultants.
Curious what GenAI can do specifically for your organization?
Schedule a no-obligation consultation tailored to your domain/sector/industry, techniques and ambitions.
