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10 Generative AI Use Cases for Enterprises

10 Generative AI Use Cases for Enterprises
10 Generative AI Use Cases for Enterprises

In today’s tech world, there’s this cool thing called Generative AI, or GenAI. Enterprises are super interested in it, unlike smaller ones or startups. They see it as a chance to do special stuff.

Generative AI isn’t just a big deal in 2024’s tech scene. Believe it or not, 50% and 60% of all organizations have already adopted this game-changing technology.

Enterprises like making their own AI models without sharing their secret data with other companies. But there’s a catch. This GenAI stuff is new, and it brings its own set of problems.

But there’s a silver lining. GenAI could be a game-changer, helping companies develop new services and solutions. It’s like opening doors to new markets and stealing customers from the old guys.

Along with the good stuff, there’s some bad. GenAI promises to make things easy with automation, making customers happier and saving money. But there’s a risk, too; the AI might play favorites or see things that aren’t there.

So, big bosses are scratching their heads and wondering how to use GenAI without getting burned. Well, in this blog, we’ll have a look at the top 10 Generative AI use cases. So, let’s get started!

Key Takeaways:

  • Generative AI, or GenAI, is rapidly adopted by 50% to 60% of organizations, promising transformative capabilities in various industries
  • Enterprises are intrigued by GenAI’s potential for custom innovation while safeguarding proprietary data
  • Despite its benefits in automation and cost-saving, GenAI presents challenges such as bias and misinterpretation
  • Generative AI use cases span across sectors like e-commerce, software development, healthcare, and entertainment
  • Notable examples include Shopify’s Magic for product descriptions and Expedia’s ChatGPT for personalized travel recommendations
  • Enterprises rely on AI companies like AI21 Labs and Stability AI for developing tailored solutions due to resource limitations
  • Generative AI enhances content creation, marketing, customer service, medical diagnostics, business intelligence, manufacturing, fraud detection, and entertainment
  • Enterprises should strategize AI adoption considering their unique goals, impacts on employees and customers, and alignment with company plans
  • Business leaders need to ensure thorough understanding, alignment, and acceptance of AI implementation across the organization
  • FiveRivers Technologies offers customized AI solutions using Generative AI and Machine Learning for enterprises to tackle complex challenges and ensure operational efficiency

What is Generative AI in Enterprises?

While Generative AI is a beacon of innovation, its utilization across enterprises paints a diverse canvas. The technology, uniform in its essence, is harnessed in various forms and capacities within different organizational landscapes.

In certain enterprises, Generative AI assumes the role of a conventional subscription-based tool, a mere cog in the machinery of operational enhancement. Here, its potential is merely grazed, its capabilities tapped to a limited extent, and it serves as but a fragment of the greater technological mosaic.

Some organizations choose to develop customized AI models to enhance their technological capabilities. These models go beyond their pre-defined functions and are tailored to the organization’s specific needs and goals. This approach, called Generative AI, allows for custom innovation unique to each organization.

Use of Generative AI Across Industries

Industries worldwide are tapping into the potential of generative AI to revolutionize their operations. Let’s have a look into how various sectors are harnessing this transformative technology:

E-commerce and Retail

According to Statista, almost six out of every ten industry leaders worldwide started using generative AI to suggest products for store employees in 2023, and about 39% considered trying it out.

In online retail, Shopify is a notable player embracing generative AI. Through its innovative feature, Shopify Magic, retailers can effortlessly generate product descriptions tailored to their needs. Users activate Shopify’s magic tool by inputting desired tones and key phrases, which utilizes generative AI to craft descriptions that resonate with their brand. While still in its infancy, Shopify Magic showcases the burgeoning potential of generative AI in the retail landscape.

Software Development and FinTech

AI adoption rates are soaring in the fast-paced realms of software development and financial technology (FinTech). Stripe, a leading provider of financial services SaaS, leverages OpenAI’s GPT-4 to optimize its operations. Through this partnership, Stripe enhances query management, documentation, and more, streamlining user experiences. Also, Stripe Docs empowers users to submit natural language queries, receiving human-like responses that summarize essential information. Collaborations with OpenAI and other generative AI firms further augment subscription and checkout processes, exemplifying the symbiotic relationship between technology and finance.

Travel and Hospitality

The travel and hospitality industry, synonymous with customer-centric experiences, has embraced generative AI to elevate service standards. Expedia, a prominent player in this sector, integrates ChatGPT, a popular generative AI tool, into its travel planner. This integration enables Expedia users to seek personalized travel accommodations and recreational activity recommendations. Moreover, an AI-based feature retains previous recommendations, facilitating seamless booking experiences. Expedia’s AI-driven solutions streamline travel logistics for enterprises, such as companies with frequent travelers, affording employees more time for core responsibilities.

10 Generative AI Use Cases

Some businesses, like those focused on marketing and sales, have swiftly embraced generative AI due to its ability to rapidly produce content and enhance customer relationships. However, industries with stricter legal and compliance requirements, such as healthcare, insurance, and education, have been more cautious. They’re wary of the rapid growth of generative AI without clear rules or oversight.

Enterprises across various sectors are turning to leading AI companies for help. Many companies lack the internal resources to develop or maintain AI systems independently. Let’s explore how these AI companies meet enterprise needs by leveraging the full potential of generative AI.

10 Generative AI Use Cases for Enterprises

Product Development and Management

Generative AI is now crucial in coding apps, crafting product documentation, and enhancing user experience throughout the product lifecycle. Moreover, it’s increasingly utilized for generative design, enabling product designers to explore numerous design concepts efficiently.

Developers and product managers leverage generative AI tools to streamline various tasks. For example, developers may use these tools to brainstorm innovative code and designs. Meanwhile, product managers rely on generative AI to aggregate and summarize user feedback from diverse sources, aiding in product improvement.

Generative AI foundation models and APIs are widely employed to create and refine new generative AI models and products. Many enterprises have developed customer service and chatbot solutions based on OpenAI foundation models, showcasing the versatility and potential of generative AI in product development and management.

Some AI tools that are available for use are AI21 Labs, Stability AI, Viable Generative Analysis, and GPT-4.

Writing Blog and Social Media Content

Large language models (LLMs) wield immense power in writing engaging content for blogs, social media, product pages, and business websites. With the right guidance, they can generate tailored and imaginative content that resonates with audiences.

Generative AI tools offer the flexibility to modify existing content or generate entirely new pieces based on user prompts and contextual cues. Users can specify the desired tone of voice and input past brand content to ensure consistency and relevance.

However, it’s essential to approach generated content with caution. While AI-generated content can mimic human writing, it may also contain inaccuracies or unsupported claims. Human oversight is crucial, especially for journalistic or fact-driven content. Writers, editors, and quality assurance analysts should meticulously fact-check AI outputs before publication to maintain credibility and accuracy.

Some available AI tools are HubSpot Content Assistant, Phrasee, Notion AI, and Jasper.

Inbound and Outbound Marketing Communication

Other than managing blog and social media content, marketing teams must also elevate their inbound and outbound marketing efforts. Traditionally, employees manually craft personalized emails and chats tailored to current and potential customers. However, generative AI solutions are revolutionizing this process by automating the creation and delivery of emails.

Generative AI goes beyond just sending emails; it can also access and qualify contacts for further engagement within the enterprise’s customer relationship management (CRM) platform.

Examples of AI solutions enhancing enterprise project management capabilities include Salesforce Einstein GPT, HubSpot AI, and Twain.

Customer Service Operations

AI has emerged as a vital tool for customer service operations, aiding organizations in providing timely customer support while lightening the load on service representatives and call centers. When the COVID-19 pandemic disrupted Lufthansa Group’s business, its call centers were inundated with customers seeking assistance with canceled and rescheduled flights. This crisis accelerated the company’s shift towards digital transformation in customer service.

For many companies, adopting AI in customer service is driven by evolving consumer expectations. According to McKinsey, approximately 67% of millennials now anticipate real-time customer service, while 75% of customers expect a consistent service experience across multiple channels.

Unilever, a company at the forefront of leveraging AI technology, utilizes the GPT API to develop AI tools to reduce food waste and automate product listings. Additionally, Unilever employs the API to create a platform that filters incoming emails to customer service, distinguishing between spam and legitimate inquiries.

Chatbots such as Forethought SupportGPT, UltimateGPT, Gridspace, and IBM Watsonx Assistant are being implemented in enterprises to improve customer experience.

Medical Diagnostics and Pharmaceutical Drug Discovery

Generative AI is gradually gaining traction in medicine and pharmaceuticals, promising transformative advancements. In medical diagnostics, image generation and editing tools are increasingly utilized to enhance medical imaging, allowing professionals to scrutinize specific areas of the human body with greater clarity and realism. Some tools even offer basic diagnostic capabilities, although medical professionals should verify the results for accuracy and quality assurance.

Generative AI technology is revolutionizing drug discovery and design processes on the pharmaceutical front, making them more efficient and effective. Scientists can now generate novel molecules, identify disordered proteins more accurately, and predict clinical trial outcomes more precisely.

Prominent tools such as ChatGPT and GPT-4 are being explored in pathology applications, with ChatGPT even demonstrating proficiency in passing the U.S. Medical Licensing Exam. Nonetheless, medical professionals must cross-check results to ensure accuracy and identify any anomalies. Other notable AI solutions in the medical field include Paige.ai, Google Med-PaLM 2, Insilico Medicine, and Iambic Therapeutics, showcasing the diverse applications of generative AI in advancing healthcare and pharmaceutical research.

Business Performance Reporting and Data Analytics

Generative AI is increasingly becoming a valuable tool for business intelligence and performance reporting due to its ability to quickly sift through vast amounts of text and data to extract key insights. This technology is particularly effective for analyzing unstructured and qualitative data, which require extensive processing to derive meaningful insights.

Generative AI data analytics tools can either exist as standalone products or be integrated within established data analytics platforms such as Power BI. By using generative AI, these platforms enhance traditional data analytics workflows by providing suggestions for improved visuals, clearer reports, and refined data interpretation.

An intriguing application of generative AI in this domain is the creation of data narratives, which provide highly contextualized explanations of datasets. Notable examples of such AI solutions include Narrative BI, Dremio, and SparkBeyond Discovery.

Smart Manufacturing and Predictive Maintenance

Generative AI is revolutionizing the manufacturing industry, empowering enterprises to innovate and meet their production goals more efficiently. In predictive maintenance, generative AI models play a crucial role in streamlining workflows by generating actionable to-do lists and timelines. These models identify areas for improvement and simplify the data collection process from various parts of the production line.

Also, generative AI facilitates inverse design, which analyzes deficiencies in manufacturing processes. Tools like Tulip Frontline Copilot, Clarifai, and C3 Generative AI Product Suite are adept at identifying missing materials and generating suitable replacements to fulfill production requirements.

Fraud Detection and Risk Management

AI-powered fraud detection and risk management technology is crucial in analyzing large volumes of transaction or claims data swiftly identifying patterns or anomalies. Generative AI is a valuable tool for enhancing fraud detection, underwriting, and risk management processes in the finance and insurance sectors.

In insurance, generative AI offers significant benefits for both insurers and customers. Underwriters and claims adjusters leverage generative AI tools to analyze past policies and claims, optimizing coverage and claim outcomes.

However, this solution has a downside. Bad actors may exploit generative AI tools to more effectively commit fraud and other crimes. Companies must invest in fraud and threat detection solutions to counter this risk. Examples include Simplifai InsuranceGPT, ChatGPT, and Docugami, which specialize in mitigating fraud risks through advanced AI-driven detection mechanisms.

Entertainment Media Generation

Generative AI is poised to transform the entertainment media industry by delivering high-quality and realistic AI-generated images. Its applications span moviemaking, video games, virtual storytelling, VR experiences, and even podcast generation.

AI tools offer a convenient alternative to traditional content creation methods in the entertainment industry. Producers can leverage generative AI to streamline the production process rather than setting up cameras, editing footage, or recording audio. Experts predict generative AI will revolutionize film content creation, script writing, and video production soon.

Leading AI tools such as Stability AI’s Stable Diffusion, Plask, Charisma, and Latitude Unchained are already making waves in the industry.

Graphic Design and Video Marketing

Generative AI has revolutionized graphic design and video marketing by generating realistic images, animations, and audio suitable for various projects. Some generative AI vendors even provide voice synthesis and AI avatars, eliminating the need for actors, video equipment, or advanced video editing skills in marketing videos.

Generative AI video marketing tools are at the forefront of creating multilingual content using artificial intelligence. Although video avatars may require further refinement to replace human speakers convincingly, this advancement is particularly promising for global enterprises needing to convey messages in languages they may not speak.

Generative AI also significantly reduces the barriers to accessing costly technologies and products. For example, it can edit headshots and create compelling background imagery without needing professional photography services. Several emerging generative AI tools generate social media graphics or images based on user input, enhancing accessibility and creativity.

While current avatar and voice technologies may still require some manual adjustments to seamlessly replace human speakers, they represent a significant step forward. Examples of AI solutions offering graphic design and video marketing services include Rephrase.ai, Diagram, Synthesia, and Lightricks.

Leading Examples: Generative AI Use Cases for Enterprise

Generative AI has become integral to numerous enterprise operations and creative endeavors, with organizations adopting various models and tools to enhance their processes. Let’s have a look at some prominent examples of how major enterprises are integrating generative AI into their workflows:

Accenture Use Case (Professional Services and Business Operations)

Accenture leverages generative AI to assist clients in devising smarter business strategies and operations across diverse sectors like banking, sales, and customer service. Specific applications include implementing tools from Microsoft Azure and OpenAI for a major oil and gas company, designing an AI-powered search engine for Spain’s Ministry of Justice, and automating email review and triage for a multinational bank.

Nvidia Use Case (Life Sciences)

Nvidia’s BioNeMo Drug Discovery Cloud Service employs large language modeling to accelerate drug discovery, protein engineering, and research in various scientific domains. Researchers can utilize BioNeMo with Nvidia cloud APIs to develop customized biomolecular AI models, leveraging scalable supercomputing infrastructure.

Expedia Use Case (Travel and Hospitality)

Expedia’s ChatGPT-powered travel planner enables users to receive travel recommendations and save preferred accommodations effortlessly. While primarily catering to individual consumers, Expedia’s solution can also streamline travel planning for business users, enhancing efficiency and saving time.

Shopify Use Case (E-commerce and Retail)

Shopify’s Magic feature uses artificial intelligence to generate product descriptions and other content based on user input. This innovative tool empowers retailers to enhance product development and sales processes through AI assistance.

Stripe Use Case (Fintech and Software Development)

Stripe uses OpenAI’s GPT-4 to enhance documentation, summarization, and query management for developers using Stripe Docs. Also, Stripe facilitates smoother subscription and checkout processes for various generative AI companies, streamlining compliance and financial management.

Conclusion

It’s amazing to see how AI continuously improves and how businesses find innovative ways to leverage its power. From writing ads to discovering new medicines, AI is transforming how we operate and interact with the world around us. It’s fascinating to see how this technology is revolutionizing our lives!

The trick for business leaders who want to use AI is to think about what’s best for their company and what they want to achieve. They also need to consider how it will affect their employees and customers.

When it comes to using AI, it’s not just about choosing a fancy tool. It’s important to understand how AI fits into the company’s plans and make sure everyone is on board with the changes it brings.

FiveRivers Technologies is an enterprise software development company specializing in AI solutions. We offer customized services using Generative AI and Machine Learning to address complex business challenges and ensure high availability for your operations.

FAQs

What is a Real Use Case of Generative AI?

One real-world use case of generative AI is in content creation. Generative models can efficiently produce text, images, music, and videos for various purposes such as writing articles, generating artwork, composing music, and creating game content. This technology saves time and resources while offering new avenues for creativity and innovation.

What are the Uses of Generative Artificial Intelligence?

Generative artificial intelligence is used for content creation, including generating text, images, music, and videos. It’s also applied in creating realistic simulations, enhancing data augmentation techniques, and powering creative tools in various industries like entertainment, design, and marketing.

What Problems Can Generative AI Solve?

  • Creative Content Generation: Creating art, music, and writing
  • Data Augmentation: Generating synthetic data to enhance training datasets
  • Personalized Recommendations: Tailoring suggestions based on user preferences
  • Product Design: Iterative design exploration and optimization
  • Language Translation: Improving translation quality and efficiency
  • Drug Discovery: Generating novel molecular structures for pharmaceutical research
  • Video Game Development: Procedural content generation for games
  • Virtual Reality Environments: Generating immersive virtual worlds
  • Financial Modeling: Scenario analysis and risk assessment
  • Natural Language Understanding: Enhancing chatbots and virtual assistants

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