Generative AI Use Cases for Businesses Across the Industries
Generative AI, with its impressive capabilities of understanding and transforming the context, and creating new content, is no longer a promising tool — it’s a must-have. In many ways, it has already proven to be of great help to business operations.
These days, 82% of organizations considering or currently using generative AI believe it will either significantly change or transform their industry, a recent Google study declares.
It is worth saying that generative AI is changing business vision globally. In short, it will soon enable personalization so that the software will align with customer needs instead of the product designers’ expectations.
This article explores the most popular generative AI use cases for businesses across such industries as:
- Medicine and Healthcare
- Financial Services
- Retail
- Media & Entertainment
Find out how companies can adopt generative AI solutions to solve their business needs.
Why Generative AI for Business?
Generative AI is very popular thanks to its ease of interaction. It doesn’t matter whether it’s being used for personal or business needs since all you have to do is formulate your prompt (question) properly.
Since generative AI is rapidly changing workflows, we’ve highlighted the most important benefits it provides for businesses:
-
Automation:
Generative AI solutions can easily handle routine and repetitive tasks so employees can focus on more creative and complex assignments. It’s estimated that Gen AI, in combination with other technologies, could help save up to 60-70% of working time.
-
Fast content creation:
Generative AI tools, like ChatGPT, simplify and speed up content creation. It also produces diverse content, ranging from marketing emails to automated project task creation.
-
Simplified information search:
Chatbots created on a company’s knowledge base simplify information searches. For example, they can suggest related topics, provide additional context, and guide users to more in-depth information.
-
Better communication:
Generative AI models are widely used due to its user-friendly interfaces and human-like chat interactions. In general, such communication tools improve customer experience and service.
-
Summarization:
Generative AI models understand the semantics and the context of queries to provide suggestions based on context; e.g., they may parse the information and provide insights on a topic afterward.
Learn more about the benefits of generative AI for businesses.
Generative AI Use Cases Across Industries
Now let’s find out which industries generative AI impacts the most.
About 75% of the value that generative AI use cases could deliver falls across four areas (according to McKinsey):
- Customer operations
- Marketing and sales
- Software engineering
- Research and development (R&D)
Banking, high-tech, and life sciences are among the primary industries that can significantly increase revenue by fully implementing generative AI technology.
Further, we will examine the most popular generative AI business cases across all industries.
A Knowledge Base Chatbot Solution That Fits Every Business
One of the most popular and requested generative AI use cases for business nowadays is a knowledge base chatbot. In brief, it’s a chatbot that uses a company’s knowledge base to respond to customer queries accurately, that makes it a must-have tool for customer support.
Knowledge base GenAI chatbots process large amounts of information and data to bring more context to the conversation. In contrast to the older chatbot versions, their responses are more natural and human-like than just dry, robotic answers.
The accuracy of the responses depends on the quality of the connected knowledge base. This knowledge base might include your product catalog, internal and external policies, FAQ page, and even more. Based on the information in the knowledge base, the chatbot quickly transforms the data into clear and sufficient answers.
Generative AI Use Cases in Medicine and Healthcare
How do medical specialists use generative AI capabilities in their work?
Generative AI in healthcare analyzes unstructured data like patient histories and creates new content similar to what it has been trained on.
-
Automating administration procedures:
Doctors can record a patient’s appointment with a generative AI solution, transcribing speech into notes in real-time, allowing them to focus on more important things.
-
Improving drug development:
Developing new pharmaceuticals is a time-consuming and expensive process that takes 12-15 years and costs more than $1 bln. Some companies therefore use generative AI solutions to accelerate drug development. Generative AI helps researchers access, identify, and correlate data, look for connections in huge amounts of research data, and automate tasks.
-
Generating synthetic data:
Generative AI is used in healthcare to generate synthetic data that provides patient privacy. It helps in model training, scenario modeling, and algorithm validation. Synthetic data is also valuable for augmenting limited datasets, modeling clinical trials, and improving anomaly detection in medical applications.
Generative AI Use Cases in Financial Services
Financial institutions incorporate generative AI into their banking services, mainly for financial transaction automation, customer service improvement, and better decision-making. Let’s take a look at some other options below:
-
Make complex data accessible
Gen AI assists bank employees in efficiently finding and interpreting information in contracts and regulatory documents. Gen AI capabilities can speed up report preparation by summarizing large amounts of economic data or other information.
-
Customer support and assistance
Generative AI is great at finding answers in large data sets, summarizing them, assisting customer agents, and supporting existing AI-based chatbots. In addition, Gen AI-based chatbots provide users with conversations that improve their overall customer experience.
-
Know Your Customer (KYC)
Generative AI is transforming KYC processes in the financial sector, such as automating document verification and integrating with facial recognition to improve security. Real-world solutions can be seen in large banks, where generative AI improves identity verification accuracy, promotes personalization of the customer experience, and detects anomalies.
-
Capital markets research
In the capital markets, generative AI tools can assist investment analysts. Such assistants can extract and summarize the key information from complex documents, research papers, and financial reports.
-
Regulatory changes consulting
Finance and banking are known as the most regulated industries. New regulations demand a lot of repetitive work from developers to make necessary adjustments and code changes. Gen AI can improve this process by summarizing required changes and facilitating automated checks. It also can provide the necessary documentation.
Generative AI Use Cases in Retail
Generative AI is not just a technological trend but a strategic asset in the retail industry. Overall, generative AI use cases in retail could improve customer experience by driving a better and time-saving shopping experience.
-
Customer support and shopping experience:
Human-like interactions of chatbots with customers help to resolve issues quickly. Virtual agents reduce contact center workload and create new FAQ content by aggregating conversation and service data.
-
Accelerate product innovation:
Generative AI can make product development more efficient and cost-effective. It accelerates the investigation of various data sources to find relevant ideas, reducing R&D costs and speeding up the search for successful product concepts. In addition, generative AI can quickly create copy and concepts for testing and images for product and packaging design.
-
Virtual stylists:
Virtual stylists can interactively assist clients, offer personalized product recommendations, and help them find their needs.
Every year, retailers worldwide report cumulative losses of more than $2 trillion due to this challenge. Only one in ten shoppers say they find precisely what they are looking for when they use the search function on a retailer’s website.
-
Product catalog management:
Gen AI is helpful for retail catalog management optimization: it quickly creates high-quality images and customer-focused marketing copy based on simple text queries. It solves such problems as sourcing supplier images, categorizing products, and writing product copy.
Previously, these were time-consuming tasks which if not done properly would hinder site search.Generative artificial intelligence is also used to provide efficient catalog management. It drives improved customer service by delivering a better site search experience. This is vital since 92% of consumers are more likely to purchase products that are easy to find. .
Generative AI Use Cases in Media & Entertainment
-
Improved and streamlined content creation and management
Reporters can use generative AI to speed up research by helping them synthesize and analyze large amounts of information or create initial drafts or summaries of editorial content. TV and film producers can speed up post-production editing with AI-enabled interfaces.
-
Personalized customer engagement
Generative AI can help media and streaming companies attract more viewers thanks to personalized recommendations and content searches. For example, Spotify has launched DJ, a gen AI feature that creates customized playlists based on listeners’ habits.
Here is the paradox: despite the diverse content on streaming platforms, it takes time for viewers to find something interesting to watch. In a perfect world, the user could ask the content platform to recommend a specific show based on mood, actor’s choice, similarity to previously watched content, etc. This could all be curated by generative AI .
-
Automatic subtitles and dubbing
Gen AI algorithms can generate subtitles and dubbing for video content in different languages, thereby expanding the global reach of content. This helps reach global markets much faster and is also changing the way media is consumed. Streaming platforms that use generative AI to create multilingual content are targeting more diverse and inclusive audiences.
-
New ways for monetization
Generative AI has the potential to help media companies improve the monetization of the audience experience. Well-tuned personalization can help to retain and increase subscription and advertising revenue. In addition to personalized recommendations, generative AI can generate even more advertising revenue through targeted, contextual, and personalized ads. Gen AI can also significantly lower the time and costs of producing audio ads.
Wrapping Up: Generative AI Business Use Cases
Generative AI capabilities are developing incredibly quickly, and with these changes come new opportunities for businesses to improve current operations.
Many companies already use generative AI or are at least trying to solve routine problems and experiment with a new approach. Its importance and value are beyond question: business leaders are constantly looking for better ways to implement generative AI .
Before adopting generative AI, they must be clear about what they want to accomplish and how this new business driver will impact their employees and customers.
Stay tuned for our following articles to learn how to start with generative AI in your business.
Was this article useful for you?
Get in the know with our publications, including the latest expert blogs
End-to-End Digital Transformation
Reach out to our experts to discuss how we can elevate your business