AI use cases

Definition

What are AI use cases?

An AI use case describes a concrete application in which artificial intelligence solves a business problem – faster, cheaper or more precisely than previous methods.

Why AI use cases matter

According to Bitkom, 36 percent of companies in Germany already use artificial intelligence – double the previous year. McKinsey puts the average ROI at $3.70 per dollar invested.

Those who use AI strategically gain a measurable competitive advantage.

Typical areas of use at a glance

Most AI use cases fall into six areas: customer service (chatbots, voice bots), marketing and sales (personalisation, lead scoring), production and logistics (predictive maintenance, quality control), finance (fraud detection, document processing), human resources (recruiting, people analytics) and law (contract analysis, due diligence).

Customer service

AI use cases in customer service

Customer service is the most common entry point for AI in companies. The combination of high enquiry volume, recurring questions and round-the-clock expectations makes the area ideal for AI automation.

Chatbots and virtual assistants

Modern AI chatbots understand natural language and resolve standard enquiries on their own. Klarna introduced an AI assistant that does the work of 700 full-time employees – result: $40 million profit improvement.

Vodafone achieves an automation rate of 70 percent with its chatbot TOBi.

Intelligent ticket routing

AI automatically categorises incoming enquiries by topic, urgency and mood. Sentiment analysis detects frustrated customers and escalates their tickets directly to experienced staff – before the situation escalates.

Voice bots and telephony

AI phone assistants answer calls, respond to standard questions and forward complex matters. Especially in mid-sized companies, voice bots ensure round-the-clock availability – without additional staff.

Marketing & sales

AI use cases in marketing and sales

Marketing and sales benefit from AI wherever data on customer behaviour accumulates – and today that is almost everywhere.

Personalisation and recommendations

AI-supported personalisation analyses the behaviour of individual users and delivers matching content, product recommendations and offers. Personalised emails achieve a six times higher transaction rate than generic mass mailings.

93 percent of CMOs surveyed report a measurable ROI from generative AI.

Content creation and SEO

Generative AI creates product descriptions, social media posts and ad copy in seconds. Companies use AI tools for automated A/B tests to systematically optimise headlines, images and calls to action.

Lead scoring and sales forecasting

Predictive models rate leads based on their behaviour and identify contacts ready to buy before sales gets active. That shortens the sales cycle and increases the closing rate.

AI automation takes over data preparation and scoring – sales concentrates on closing.

Production & logistics

AI use cases in production and logistics

In industry, AI delivers the greatest ROI where downtime is expensive and quality requirements are high – which is almost everywhere.

Predictive maintenance

Predictive maintenance analyses sensor data from machines and detects wear before a failure occurs. Siemens uses predictive maintenance in its gas turbine plants.

Across industries, the approach reduces unplanned downtime by up to 34 percent.

Quality control

Computer vision checks products for defects in real time – faster and more consistently than the human eye. BMW uses AI-based image analysis in quality inspection, Bosch relies on AI-supported defect detection in manufacturing.

Faulty parts are detected before they leave the production line.

Warehouse and supply chain optimisation

AI-supported demand forecasts reduce overstocks and shortages. Walmart has cut its out-of-stock rate by 30 percent with AI forecasts.

In logistics, AI route planning shortens delivery times by up to 18 percent. Automated warehouse systems increase throughput by 30 to 50 percent.

Finance

AI use cases in finance and insurance

According to a PwC study, 73 percent of financial companies in Germany already use AI. The sector is among the most advanced industries in AI adoption.

Fraud detection

AI models analyse transaction patterns in real time and raise the alarm immediately on anomalies. Given a 900 percent rise in deepfake fraud, AI-based fraud detection is becoming an obligation – not an option.

Automated document processing

Intelligent document processing automatically extracts data from invoices, contracts and claims. Clerks only check exceptions.

That speeds up processing and reduces errors.

Risk assessment and compliance

AI-based KYC checks (know your customer) shorten the onboarding time for new customers from days to minutes. Automated regulatory checks monitor transactions and report compliance violations before they become a problem.

HR & recruiting

AI use cases in human resources

Human resources uses AI to cope with the skills shortage – from candidate selection to employee retention.

Recruiting and candidate screening

27 percent of companies use AI in recruiting. AI-supported matching compares job profiles with applicant data and finds suitable candidates in seconds instead of days.

Automated CV screening reduces the manual effort in pre-selection by up to 75 percent.

Onboarding and training

AI-generated video avatars guide new employees through onboarding processes. Personalised learning paths adapt training content to individual knowledge levels – every employee learns at their own pace.

Employee retention and people analytics

People analytics models detect patterns that indicate an increased risk of resignation – such as declining activity or changed communication patterns. HR teams can counteract before top performers leave the company.

Other industries

AI use cases in law and healthcare

Even in heavily regulated industries such as law and healthcare, AI accelerates data-intensive routine tasks.

Legal tech

AI-supported contract analysis achieves 94 percent accuracy – and needs 26 seconds instead of 92 minutes to do so. Law firms and legal departments use AI for due diligence, document review and clause extraction.

The legal tech market is growing to an estimated $650 million.

Healthcare

Ambient scribes – AI systems that automatically document doctor-patient conversations – reduce documentation effort by 60 percent. In diagnostics, AI models analyse medical images and detect anomalies that escape the human eye.

The market for AI-based medical documentation has already reached $600 million.

Trend

AI agents: the next generation of use cases

AI agents go beyond classic chatbots. They do not just answer – they act on their own: researching, making decisions and carrying out multi-step tasks without human intervention.

What distinguishes AI agents from chatbots

A chatbot answers questions. An AI agent plans, uses tools and carries out complex task chains on its own.

The decisive difference: multi-step reasoning – the agent breaks a goal into sub-steps and works through them.

Agentic AI use cases

AI agents already take over complex processes today: automated research and reporting, independent code generation and deployment, and customer service agents that solve problems end to end – from understanding the enquiry to executing the solution. AI automation with agents is becoming the standard for companies that want to eliminate repetitive knowledge work.

Implementation

How do companies find the right AI use case?

The biggest challenge is not the technology – it is the right use case. Anyone who starts with the wrong use case burns budget and trust.

Identify problems, do not look for technology

Successful AI projects start with a business problem, not with a technology. The question is not “Where can we use AI?” but “Which process costs us the most time, money or quality?”

Quick wins vs. strategic projects

Quick wins deliver fast results at low risk: automated email sorting, AI-supported meeting minutes or FAQ chatbots. Strategic projects such as predictive analytics or autonomous AI agents need more lead time but deliver the greater leverage in the long run.

Assess ROI realistically

Well-chosen AI use cases achieve an ROI of five to fifteen times the investment. Prerequisite: a realistic assessment of effort, data quality and integration complexity.

AI consulting helps to find the use case with the greatest leverage – before the first model is trained.

FAQ

Frequently asked questions about AI use cases