Top Generative AI Use Cases for Businesses

Generative artificial intelligence (AI) has the potential to transform how businesses work, significantly improving employee's productivity, increasing operational efficiency, and enhancing customers’ experiences.

In this article, we explore selected business use cases of generative AI for various departments and industries to demonstrate how organizations can use this technology in multiple scenarios.

Generative AI Use Cases in Marketing

Generative AI is a great tool for marketers, who can use it to streamline content creation and prepare highly personalized, engaging, and efficient marketing materials and campaigns at scale.

1. Creating personalized content

Traditionally, creating different types of content, such as videos, newsletters, ads, etc., was time-consuming and expensive, requiring businesses to invest in large marketing teams and several tools. However, with the rise of generative AI, preparing engaging marketing materials tailored to customers' preferences and different platforms became much easier.

Creatio AI – content generation example

Generative AI has the ability to automatically analyze vast amounts of customer data to uncover their preferences and needs. Paired with the analysis of the performance of the past marketing materials, customer feedback, consumer sentiment, market trends, etc., these insights serve as the basis for gen AI to prepare engaging content.

From social media posts and short videos to email drafts, ads, graphics, blog posts, and other marketing materials, gen AI can create content that will resonate with the business's customer base. To increase the effectiveness of the marketing initiatives, AI can also tailor these materials to different channels, platforms, and customer segments. Additionally, it can translate the content into multiple languages, helping businesses expand to new markets and engage with customers around the world.

Creatio AI – content generation example

2. Automating marketing campaigns

Marketers can use generative AI to launch multiple marketing campaigns from start to finish, significantly increasing their efficiency. Gen AI tools can suggest campaign ideas, prepare briefs, create marketing materials, roll out the campaign, oversee its performance, and suggest improvements to boost engagement and conversion rates. It can also prepare interactive reports for stakeholders, with key insights regarding the effectiveness of marketing efforts, specific channels, and ads.

According to specialists from McKinsey, gen artificial intelligence has the potential to increase the productivity of marketing teams with a value of 5 to 15% of total marketing spending.

3. A/B testing

Since generative AI can produce new materials in seconds, it’s a perfect tool to use in A/B testing. Marketing professionals can use gen AI tools to create multiple variations of the same ads and content at scale, test it on different audiences and channels, analyze their performance in real-time, and choose the best version to achieve maximum effectiveness.

By analyzing customer feedback and performance insights, generative AI can not only improve the current materials but also learn which approach is the most successful and replicate it in the future.

4. Personalized recommendations

Generative AI systems can quickly analyze vast amounts of customer data and behavioral patterns to deliver personalized product and service recommendations. Whether through email, in-app messages, SMS, or directly on the website, consumers have constant access to the best offers, tailored to their current needs and preferences.

5. Market research

Generative AI can provide marketing professionals with a summary of current market trends that shape customer needs, consumer behavioral patterns, viral marketing trends, and competitor analysis. This information can be used to plan marketing initiatives, design new campaigns, adjust current efforts, or create new audience personas that better reflect modern consumers.

Gen AI can also gather and summarize customer feedback from reviews, social media, and surveys to prepare an overview of a customer sentiment. This information can be used to launch a campaign that will improve or reinforce the brand’s positive image.

Generative AI Use Cases in Sales

Sales agents can use generative AI systems to automate routine tasks and boost their efficiency with actionable insights and personalized offers.

1. Personalized outreach

Generative AI can be used to increase the effectiveness of sales outreach initiatives. Traditionally, sales agents had to manually go through vast amounts of data to find potential clients and prepare personalized messages that would spark their curiosity and encourage them to answer. These tasks used to be very time-consuming and difficult, as not all data is easily accessible. Typically, the success rate for cold outreach was quite low, with around 5% of prospects answering the first message. That changed when generative AI entered the market.

With generative AI, sales representatives can automate nearly the whole outreach process, from initial scouting for high-potential prospects to gathering information about them and preparing tailored messages.

While gen AI takes care of these manually intensive tasks, sales agents can focus on building strong relationships with potential customers. Armed with valuable insights provided by AI, sales representatives can tailor their communication style and offers to align with prospects' needs and preferences, significantly improving their chances of closing a deal.

2. Sales assistant

Generative AI can act as a sales assistant, providing sales representatives suggestions on how to lead a conversation, the next best action, the best time and channel to reach out to a potential customer, etc. Since gen AI constantly analyzes and learns from new data, it can adjust its recommendations based on the prospect’s answers and provide improved suggestions in real-time.

Additionally, after a call, sales representatives can use generative AI to quickly generate transcription, prepare a summary with key insights, and log it into the customer relationship management system. Thanks to this, they have more time to focus on actual selling rather than manually taking care of administrative tasks.

Creatio AI call transcription example

McKinsey estimates that generative AI can increase the productivity of sales departments by around 3 to 5% of global sales spending.

3. Proposal and quote generation

Gen AI can automate the repetitive task of generating proposals and quotes to speed up the sales process. It can prepare a personalized offer based on client requirements, adjust it in real-time if a customer's budget or conditions change, and include all relevant terms, recommendations, and pricing without human involvement.

4. Suggestions for upselling and cross-selling

Personalized offers can also be complemented with recommendations for upselling and cross-selling opportunities. By analyzing prospects’ needs, market trends, etc., generative AI agents can suggest to sales representatives which complementary or premium products are worth mentioning during the meeting or call to increase the deal size and value. Armed with this knowledge, sales agents can recommend products and services that are relevant to customers, rather than rely on a hunch, or push generic “products of the month”.

5. Automated content and document generation

To support sales agents' efforts and help them close a deal, generative AI can prepare personalized sales presentations, case studies related to specific industries, extensive product descriptions, market statistics, etc. Typically, these types of materials take a long time and effort to prepare and personalize to specific clients. They can be a real headache, especially if needed ASAP. With the use of generative AI, businesses can automate the creation process and prepare personalized materials at scale.

Generative AI can also assist sales representatives with creating contracts and agreements by auto-filling required data. By pulling information from CRM systems, structured, and unstructured data such as scans of forms, websites, photos, and emails, AI speeds up the document preparation process and reduces errors.

6. Sales training materials

Generative AI can also be used to produce training materials to help employees improve their selling skills. AI can analyze insights from past sales interactions to identify improvement areas and tailor training programs to each sales representative's strengths and weaknesses.

Additionally, generative AI can prepare onboarding materials using the company’s internal knowledge base, ensuring new employees have a seamless transition into their roles while quickly adapting to the company’s standards and processes.

Generative AI Use Cases in Customer Service

Customer support agents can use generative AI to increase their productivity and speed up the case resolution processes. Gen AI can answer typical customer inquiries, create FAQ sections, and help human agents resolve cases more efficiently.

1. Chatbots

Chatbots can understand, process, and answer natural language queries using machine learning and Large Language Models (LLMs), which ensures human-like interactions. Chatbots can assist customers 24/7 in multiple languages, answering queries related to products, services, payment methods, shipping status, etc. If necessary, chatbots can escalate more complicated cases that require a human touch to customer support agents. Chatbots help businesses provide positive customer experience with timely and relevant support, which increases clients’ satisfaction and loyalty.

For example, many airlines use chatbots as the first-line support for customers requiring help with purchasing tickets, finding information about their flight, filling out check-in forms, filing complaints, etc. However, if customers need help to rebook a canceled flight, find a new flight after they missed their connection, or request special help, chatbots can redirect them to human agents. This way, they can help reduce customer support agents' burden and unblock telephone lines that are only used to resolve the most pressing and complicated matters, rather than routine queries.

According to McKinsey’s report, using generative AI in customer care can significantly boost productivity, saving 30–45% of current function costs.

2. Agent's support

Generative AI not only assists customers but can also help customer support agents provide better service. By analyzing customers’ tone and language, it can determine their emotional state and help agents respond more accurately. By determining whether a customer is angry, frustrated, happy, or natural, generative AI can help human agents prioritize the most pressing issues and help them answer accordingly.

Generative AI can also help human agents personalize their responses based on customers’ history, preferences, and emotional state. It can quickly provide necessary information, guidebooks, relevant content, etc., to speed up case resolution. Additionally, gen AI tools can summarize customer interactions and log them into the system, so if customers reopen the case, support agents have easy access to the most important information and previous resolutions.

Creatio AI Case sentiment analysis and response generation

3. Knowledge management

Generative AI tooewls can help create helpful materials to answer typical customer queries. By analyzing the most frequent questions, Gen AI can update FAQ pages and create guidebooks and instructions to help customers find answers on their own. This way, businesses' knowledge base is always up to date, providing useful information to customers and support agents.

4. Feedback summary

Generative AI for customer support can collect, analyze, and summarize key insights from all customer service interactions. By analyzing customer complaints and feedback, it can find common issues and help businesses improve their products and services.

5. Post-support communication

Businesses can use gen AI tools to automate their post-support communication with customers. To ensure the case was resolved positively, AI can send follow-up messages and analyze customers’ answers. Based on the information provided by the customer it can offer additional support, reopen the case, or close it. By following up on customer cases businesses can collect valuable feedback and use it to improve their support services.

Generative AI Use Cases in FinServ

Businesses from the finance sector can use generative AI to automate tasks such as detecting fraud, providing personalized financial advice, and preparing documents and financial reports.

1. Personalized financial advice

FinServ businesses can use generative AI to analyze customer’s data to automatically generate financial advice tailored to individual needs, preferences, goals, and risk tolerance. Advisers can use AI tools to obtain insights into the performance of their clients’ portfolios in real-time with suggestions on how to achieve better results.

Additionally, this technology can be used by customers who can create personalized savings and budgeting plans adapted to their spending habits, without contacting human agents.

2. Fraud detection and prevention

Financial service businesses can use generative AI to track and analyze transactions in real-time to detect suspicious transactions, flag anomalies, and spot fraudulent behavior much faster than traditional methods. By comparing current information with historical data and market trends, AI can efficiently detect even the most complex money-laundering and fraud methods and prepare a report.

3. Document and report generation

Generative AI can help FinServ organizations’ employees prepare documents and compliance reports that typically take a lot of time and effort. Gen AI can quickly analyze vast amounts of data and autonomously prepare various documents, such as contracts, insurance policies, loan agreements, and performance reports for stakeholders and customers.

Generative AI can also generate compliance reports that are up to date with the most recent requirements, helping FinServ businesses stay compliant with industry regulations.

Generative AI Use Cases in Healthcare

Businesses from the healthcare industry can benefit from generative AI capabilities to automatically create and update medical documentation, prepare personalized healthcare materials, and support new drug development.

1. Medical documentation

Thanks to generative AI, healthcare professionals can focus on providing care to their patients without worrying about administrative tasks. With gen AI tools, healthcare professionals can easily create and update medical documentation, since these tools can pull information from the history of communication with a client, images, emails, calls, scanned hand-written notes, etc.

2. Personalized healthcare advice

Healthcare professionals can use generative AI technology to quickly create personalized healthcare advice tailored to individual patients based on their records. For example, dietitians can use gen AI tools to analyze patient information such as weight, height, blood sugar levels, eating habits, physical activity, etc., to streamline the preparation of personalized diet plans that will help their patients manage their weight. This is especially beneficial for healthcare providers who have many patients or need to regularly update their healthcare plans.

3. Drug discovery and development

Pharma companies can use generative AI in drug development to speed up the discovery of new medication and treatments. Gen AI model can analyze and summarize medical literature, generate potential molecular structures for new medications, and create synthetic data to test drug efficiency.

According to Gartner, this year (2025) more than 30% of new drugs will be developed using generative AI innovation technology.

Once the new drug is developed, gen AI can also help streamline clinical trial processes. Traditionally, finding the right candidates and summarizing trial results was a long and complicated process that required a lot of manual work. Nowadays, clinical trial specialists can use gen AI tools to quickly comb through patient records and identify the best candidates for both control and experimental groups. It can also generate personalized communication, so the organization stays in touch with clinical trial candidates. Healthcare professionals can also use AI to summarize the trial results to generate necessary documentation and reports.

4. Diagnostic tests

According to a Google Cloud article, generative AI tools can also be used to create diagnostic tests that can help detect various conditions in the early stages. Gen AI has the ability to discover even the smallest changes and connect the dots to diagnose illnesses that are difficult to detect faster and more efficiently.

Generative AI Use Cases in Manufacturing

Manufacturing industry can use generative AI technology to improve their product design processes, expedite product development, and boost operational efficiency.

1. Product design and development

Generative AI can help manufacturing businesses expedite and expand the product development processes by generating multiple variations of products. Gen AI can iterate the same products based on various parameters such as material, costs, market trends, customer preferences, etc., and generate prototypes using 3D models and CAD. For example, generative AI can design different versions of a chair made with different materials and aesthetics in mind to appeal to different customer segments.

According to Gartner, gen AI technology in manufacturing has the ability to create designs optimized to specific constraints and goals, including manufacturing methods, performance, and materials, accelerating the design processes.

2. Quality control

Generative AI can be used to ensure the highest quality of manufactured products. AI-empowered tools can instantly spot even the smallest product defects and alert production teams about possible issues. This helps businesses increase the quality of their products, reduce returns, and build a positive brand image.

3. Product personalization

Manufacturing businesses can use generative AI to help them personalize their product offers, without engaging human designers. Gen AI can autonomously tailor the design of products and packaging solutions to fit specific customer requirements.

4. Product innovation

Introducing new products always comes with a risk for a company. It might become a huge success and sell-out in minutes or turn out to be a complete flap and clutter the warehouse for years. However, with the analytical capabilities of generative AI, businesses can be more confident their offering will find its customer base. Generative AI can analyze market data to identify emerging trends, customer needs, and competitors’ offering to generate ideas for new products and features based on industry demand, rather than guesswork.

How Can Creatio AI Empower Your Business

Generative AI offers businesses amazing capabilities; however, the true power of AI lies in the combination of generative, agentic, and predictive AI, which has the potential to truly transform business operations.

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Creatio brings together generative, agentic, and predictive AI into a unified no-code platform to empower businesses across all industries to enhance productivity, support informed decision-making, and boost customer experiences.

Generative AI is designed to support personalized content creation at scale from customized emails and marketing campaigns to financial advice, AML reports, medical documentation, and many more. Thanks to the access to customer data and market trends, Creatio AI can autonomously prepare messages and content tailored to specific customer segments, increasing customer engagement and satisfaction.

Predictive AI analyzes vast amounts of current and historical data to predict trends, anticipate risks, and find growth opportunities, supporting data-driven decisions. For example, Creatio AI can suggest the next best step for a sales opportunity to increase the likelihood of conversion.

Agentic AI acts as an intelligent agent that automates workflows and autonomously performs repetitive tasks such as scheduling meetings, task reminders, and updating CRM data based on chats, meetings, and calls. It can also provide actionable recommendations on the best course of action by analyzing knowledge bases, previous cases, and external sources such as community forums.

This powerful combination of AI capabilities ensures that businesses can work more efficiently, proactively respond to changing customers’ needs and market trends, and provide personalized customer experiences at scale.