Generative AI in Business – Practical Use Cases and Value for Companies

Why Generative AI is Becoming a Key Business Topic

What Makes Generative AI So Valuable for Businesses

For businesses, this means:

1. Faster Processes: Routine tasks can be massively accelerated.
2. Scalability: Content or service volumes can grow without proportional increases in staff.
3. New Business Models: AI enables products or services that were previously too expensive or complex to develop.

Practical Applications: From Marketing to Product Development

• Marketing & Communication
• Sales & Customer Service
• Human Resources (HR)
• IT & Software Development
• Research & Innovation

Use Case 1: Marketing & Communication – Rethinking Content Production

Before AI:

With Generative AI:

• Text Creation: AI models write articles, optimize SEO texts, and generate ad variations.
• Image & Video Creation: Creative assets are produced in minutes instead of days.
• Personalization: Content can be tailored to specific target groups or even individual users.

Example:
A mid-sized e-commerce company in Germany uses generative AI to automatically create product descriptions. Instead of manually writing 3,000 texts, the AI generated drafts within two weeks – requiring only minor editorial adjustments. The result: 80% time savings, faster SEO indexing, and increased revenue in the long-tail segment.

👉 Further reading: The Benefits and Challenges of Generative AI – A Look Beyond the Hype.

Use Case 2: Sales & Customer Service – AI as a Digital Sales and Service Assistant

In sales, speed is critical. Delayed lead follow-ups mean lost deals. The same applies to customer service: long wait times lead to dissatisfied customers.

Generative AI can address these challenges in three key ways:

1. Lead Qualification: AI analyzes CRM data, identifies patterns, and recommends the most promising contacts.
2. Proposal Creation: Complex proposals can be automatically drafted and tailored to customer needs.
3. Customer Communication: AI generates personalized emails, chat messages, or service FAQs in real-time.

Example:
An insurance company implemented a multi-agent workflow powered by generative AI:

🟣 Agent 1 analyzed incoming inquiries.
🟠 Agent 2 reviewed contract data.
🔵 Agent 3 created tailored proposals.

This reduced processing time by 60% while increasing conversion rates.

Use Case 3: Human Resources – Streamlining Recruitment & Employee Development

How Generative AI Helps:

1. Applicant Management: AI reads resumes, matches skills with job profiles, and creates shortlists.
2. Interview Scheduling: Automated scheduling saves time.
3. Employee Development: Personalized learning paths and training content are generated automatically.

Example:
A global tech company uses generative AI to create employee training programs based on individual career goals. Instead of standardized e-learning, each employee receives a curated learning plan. This increased internal training participation by 45%.

👉 Further reading: The Future of Generative AI – Trends, Predictions, and the Role of nuwacom.ai.

Interim Conclusion

These three examples already show that generative AI is not a future topic – it’s transforming business reality today. Whether it’s faster marketing, more efficient sales, or smarter HR, measurable benefits are emerging everywhere:

1. 30–80% time savings in content and document creation.
2. Higher conversion rates in sales.
3. Improved employee experience through personalized training.

Use Case 4: IT & Software Development – From Code to Test Automation

Typical Applications:

1. Code Generation: AI writes boilerplate code or suggests optimizations.
2. Test Automation: Unit and integration tests are automatically created and executed.
3. Documentation: Complex code logic is documented automatically.
4. Debugging: AI analyzes error messages and suggests fixes.

Example:
A German SaaS company reports that developers using generative AI can implement features up to 30% faster. Instead of spending time on standard code, they focus on architecture and innovation.

Use Case 5: Research & Innovation – Accelerating Discovery

Examples:

1. Literature Review: AI scans thousands of papers and summarizes key insights.
2. Simulations: AI generates scenarios that would otherwise require costly physical tests.
3. Product Design: From initial concepts to prototypes, designs are created automatically.

A pharmaceutical company uses generative AI to identify potential drug candidates. Instead of manually reviewing millions of molecules, the AI generates promising suggestions. The result: development cycles shortened by years.

The Business Value: ROI and Strategic Impact

💡 Key Benefits:

• Productivity: Routine tasks shrink, freeing employees for value-added work.
• Innovation: New products, services, and business models emerge.
• Scalability: Content, services, and processes can scale without proportional staff increases.
• Cost Savings: Studies show 20–40% savings in areas like support or content production.
• Employee Satisfaction: Teams can focus on creative projects instead of repetitive tasks.

McKinsey estimates that generative AI could create $1.4 trillion in additional annual value in marketing and sales alone.

Risks and Challenges: What Companies Need to Consider

• Data Quality & Bias: Poor or biased data leads to flawed results.
• Security & Compliance: Especially in Europe, GDPR compliance is crucial.
• Transparency & Governance: Clear governance strategies are needed to build trust.
• Change Management: Employees must be trained and involved to avoid resistance.
• Dependency on Models: Proprietary LLMs can create lock-in effects. Companies should opt for model-agnostic platforms to remain flexible.

👉 Learn more: How to Implement AI Agents Securely and GDPR-Compliantly.

Outlook: The Future of Generative AI

Key Trends:

• Multi-Agent Systems: Specialized AI agents working in coordination.
• Domain-Specific Models: Tailored AI systems for industries like healthcare, law, or finance.
• Edge & On-Premises AI: Growing demand for local or sovereign solutions, especially in Europe.
• Generative AI + RPA: Combining traditional automation with creative AI for new workflows.
• Human-Machine Collaboration: AI complements rather than replaces, reshaping employee roles.

Conclusion

Generative AI is here to stay. Whether in marketing, sales, HR, IT, or research, measurable benefits are emerging everywhere. Companies that act now will gain not only a productivity advantage but also strategic market differentiation.
The key question is no longer if generative AI will be used – but how quickly and effectively.

Book a Demo Now and see live how generative AI automates processes and accelerates innovation.
Download Whitepaper “Successfully Implementing Generative AI in Companies”.

FAQ

Follow us on LinkedIn