Future-Oriented Generative AI Applications For Your Business! 

“According to a McKinsey study, about 75% of generative AI applications fall under customer services, marketing, sales, and R&D. The same study also found that using Generative AI can increase productivity by 0.1% to 0.6% annually through 2040. When combined with other automation technologies, the technology can add an extra 0.5% to 3.4% to productivity.” 

From chatbots to maintaining spreadsheets and analyzing client data to verifying information credibility, there are generative AI apps for all your problem statements. 

With its advanced functionalities and smart assistance, generative AI has penetrated every nook and corner of our day-to-day operations. Today, almost every industry can find scope for generative AI integration in both internal operational and external customer-related functionality. 

Today’s blog focuses on these applications of generative AI. We will delve into everything from how it operates to industry-specific use cases. But first!! What is generative AI? It is a new technological advancement in the field of artificial intelligence; it can produce output in multiple data formats, including audio, video, and textual content. 

Generative AI models are trained on vast volumes of data, followed by regular testing, training, and optimization to ensure optimal functionality and productivity. Powered by machine learning, NLP, and NLU, generative AI applications include predictive maintenance, quality control, improved customer interactions, and effective management. 

Related Read – A Brief Overview Of Generative AI

How Does Generative AI Function? 

Every generative AI architecture, though complicated, comprises these crucial layers: 

• Data  Processing Layer – To collect, prepare, and process the data 

• Generative Model Layer – To generate unique content using machine learning 

• Optimization Layer – To regularly improve the AI model based on feedback and new data

• Deployment Layer – To seamlessly deploy the generative model into the system 

There are many generative AI models, but the most prominent are VAE and GAN.

VAE, or Variational Autoencoder model, works with an encoder-decoder architecture. The encoder compresses the data to extract the key information and send it to latent space, which generates relevant samples from a cluster of data. This is then sent to the decoder, which restores the original form in output. 

GAN, or Generative Adversarial Networks, model also comprises two components: generator and discriminator. The generator produces images inspired by training sets that are still unique. The discriminator’s role is to continually improve the AI model by finding similar and fake images produced by the generator. 

These generative AI models are trained on huge quantities of relevant data so they can determine patterns and generate unique content. The app uses ML algorithms and natural languages to respond to prompts in the form of texts, images, designs, audio, etc.  

This future-ready technology finds its use cases in multiple shapes and forms! We have curated some of the crucial generative AI applications and listed them down for you: 

Some Of The Key Generative AI Applications 

There are many generative AI business applications across a multitude of domains and functionalities. These smart integrations bring more agility, flexibility, and scalability, preparing the business for the ever-evolving business landscape. 

Some of the crucial applications of generative AI in the present day are: 

Content Creation 

This is, without a doubt, the most notable generative AI application of all. AI can develop various types of content, including fascinating art pieces, engaging content, and phenomenal videos.

Some of the key areas that generative AI optimizes in the domain of content creation are: 

• Image Generation

When it comes to images, generative AI can create unique images from textual prompts and modify existing images into finer, higher-quality versions. It can also generate missing portions of an incomplete image, design realistic images, or improve them (in terms of color, resolutions, pixels, etc.).

• Video Content 

The predictive suggestions and video manipulation tools allow users to create exceptional videos. Generative AI predicts the video frames based on existing scenes for a seamless experience. Styling tools help users generate separate videos with similar styles, which is good if you want to achieve a cohesive look and feel. 

• Textual Content 

There are many generative AI applications for textual content, such as blogs, content outlines, social media posts, quotes, etc. In fact, generative AI can be used at all stages of textual content generation, from ideation to content guidelines creation to content refining and proof reading. 

Summarization & Transcription

Generative AI doesn’t only help in content creation but also makes the content more accessible. Whether you want to convert audio and videos to text or you want to convert that text into speech, there’s a generative AI app for that. 

Some of the ways generative AI transcribes and makes content more accessible are: 

• Audio/Video Transcription 

Audios and videos can be transcribed either in a word-to-word manner or as a summary using the speech-to-text feature of generative AI. To add more to that, the opposite functionality is also available as a text-to-speech feature. This makes learning and working accessible for everyone. 

• Text Simplification

Complex datasets and research papers can be easily organized and understood using generative AI apps. So, you can organize it in a tabular format or with pointers in a matter of a few commands. 

• Sentiment Analysis 

Since generative AI models are trained on substantial natural language datasets, they understand and can differentiate between language tonality to provide accurate sentiment analysis. This is especially beneficial in customer service, as it will not only save employees time but will also provide them with clarity on how to deal with the situation. 

If you are looking for a tool to transcribe, summarize, or simplify your data, our latest generative AI solution will pique your interest. Know about it here – DataBarin AI. 

Coding 

Another generative AI application comes in software development at the coding stage. Automating code testing and generation reduces the dependency on developers for updates and code fixing. They can rather focus on developing newer products. 

Some of the common examples of generative AI optimizing codes include: 

• Code Generation 

Since the AI model understands natural language, a textual prompt can be easily converted into code. Users can also use images (such as an image for a website or a code screenshot) to generate corresponding codes, which is good from an SEO and maintenance perspective. 

• Automated Testing 

A generative AI tool can identify errors and bugs in the code faster and more accurately than humans. These models can also test the code functionalities in a virtual environment, saving developers time and fostering faster resolution. 

• Code Completion 

One of the best things about context-driven responses is predictive suggestions. Writing codes in an integrated development environment allows generative AI apps to suggest code lines (based on previous code structure) before developers write them, thus reducing errors and improving efficiency. 

Audio Generation 

Content generation is not limited to images, videos, or texts; generative AI’s capabilities can also be leveraged to create high-quality audio, whether in a text-to-speech model, to make music, or to do voiceovers. 

Here are some of the generative AI applications in the category of audio generation: 

• Text-To-Speech 

Users can generate realistic audio from text-based prompts, and this is possible because of the extensive AI model training on speech and textual datasets. These tools are highly beneficial for making these digital assets accessible to people with disabilities. 

• Music Creation 

When trained in music audios, these generative AI models can easily analyze patterns, beats, and styles to generate new and unique music. These models can also replicate the singer’s voice to recreate that audio in the latest music. 

• Speech-To-Speech Conversion 

In this model, a generative AI model can convert audio files into new speech (such as speech translation, voice change, etc.). This one is popular in the entertainment industry, where AI can seamlessly translate the audio for voiceovers in videos and games. 

Industry-Based Generative AI Applications

Generative AI business applications differ between industries, which is also why the shift towards custom solutions was and still is a massive success. While the above-mentioned generative AI applications generally remain the same, their impact varies across industries.

We have selected some of the industries from the vast spectrum to understand a variety of applications of generative AI across multiple domains, so let us have a look at them: 

Financial Sector

Fintech, which witnessed massive growth after the global financial crisis 2008, has since continually transformed the financial industry in unimaginable ways. What started as digital banking systems evolved into secure and transparent transactions with Blockchain. 

Then, with the introduction of cryptocurrencies, digital wallets, and the easily accessible Internet, it has become the lifeline for any financial institution to sustain itself. The introduction of artificial intelligence is no different, and it is ready to evolve with generative AI.  

Some of the areas of generative AI applications in the financial sector are: 

• Real-Time Fraud Detection 

Generative AI is trained on larger data volumes, which makes it easier for it to analyze user patterns, detect anomalies, and report to the authorities immediately. This makes financial institutions secure and reduces risks. 

• AI-Driven Credit Scoring 

One key generative AI application in finances is improved user credit scoring. It will derive effective, more accurate credit scores based on users’ income and employment history, not just their transaction patterns and credit history. 

• Pricing Optimization 

Generative AI can also analyze market trends and users’ purchasing power in the current scenario. This will help institutions determine their pricing strategy for products like loans and insurance policies. 

Healthcare 

Digital advancements in healthcare have transformed everything from primary operations to administration and management. Many areas, including patient data collection, diagnosis, and R&D, have witnessed a positive shift. 

Process streamlining, efficient operations, and data accuracy are some of the many benefits of digital integration in the healthcare sector. With the advent of generative AI, healthcare can further improve its operations. 

Some of the generative AI applications in healthcare are: 

• AI-Driven Clinical Trial  

Generative AI can accelerate drug development and foster better healthcare by introducing new treatments at regular intervals. This is because it can easily analyze huge amounts of data and help users pinpoint specific details. 

• Personalized Treatment 

Today, everything is customized, including our health and wellness. So why not our health treatments? Using generative AI, doctors can create a personalized treatment plan based on a patient’s genetic makeup, medical history, and lifestyle to ensure accurate diagnosis and treatment. 

• Remote Healthcare 

Accessible healthcare is the most crucial generative AI application in healthcare. It allows people to go beyond the limited neighborhood access. They can access primary medical care remotely and talk with an expert from anywhere.  

We designed a generative AI solution to make healthcare digitally adept. Developed by our industry experts, it can be customized into a single GenAI tool to make your healthcare institution digitally adept with AI. Read more about it here: VedAI. 

eCommerce 

A subfield of retail industries, eCommerce grew exponentially during and after the global pandemic. People realized the loopholes of traditional systems and started investing in digital solutions. From online payments to online communities, they invested in multiple digital resources. 

With the advent of artificial intelligence, these digital solutions can get much-awaited upgrades. Hassle-free operations and personalized recommendations are some of the many aftermaths of AI integration. But what does generative AI have in store for eCommerce? 

There are so many generative AI applications in eCommerce yet to be fully explored, some of which are: 

• Demand Forecasting 

Generative AI tools can effectively analyze the demand graph based on previous sales data and existing trends. This will help retailers understand their target audience and stock up on inventory accordingly. 

• Dynamic Pricing 

The current business landscape is highly competitive and filled with tonnes of options for consumers. Generative AI can analyze current trends, competitor pricing, and influencing factors to auto-adjust prices and maximize revenue. 

• Visual Search 

Retailers can leverage generative AI’s ability to analyze visual content to give their customers a seamless shopping experience. Allow visual search so users can search relevant products based on a specific image or textual description. 

Logistics 

If there is one highly complex industry when it comes to digital integration, it is logistics, but AI has also optimized it as well. In the logistics industry, AI’s automation capabilities can be leveraged to unlock your business’s full potential. 

AI in logistics can optimize almost all operations, from data automation to warehouse management, and reduce operational costs with improved efficiency. With generative AI, this shift will accelerate further. 

Here are some generative AI applications in the logistics industry: 

• Automated Warehouse

Generative AI can easily mechanize warehouse management, in which robots can handle the sorting, organizing, and packing of goods while humans foresee the operations. It can also help curate the perfect warehouse layout based on product demand for optimal functionality. 

• Autonomous Things 

Autonomous vehicles are a rage right now, and when applied on the commercial level, they can transform logistics operations. Generative AI-powered solutions such as self-driven automobiles and drones can significantly reduce delivery time periods.  

• Route Optimization 

AI can create a whole route map from satellite images to find the perfect passage and efficient goods transportation. Smart algorithms can analyze things like road conditions, traffic patterns, etc., and maximize deliveries while minimizing disruptions and time. 

Education

The last industry on our list is education. The industry that prepares the young for the world beyond classrooms should be the first to get digitalized. However, it certainly lags behind when it comes to digital integration.  

While educators are adopting digital means in their systems, there’s still a lot of scope for digitalization, especially for AI. Generative AI integration can benefit everyone, including teaching, non-teaching staff, and students. 

Here are some of the generative AI applications for educators: 

• Intelligent Teaching 

Generative AI in education can truly revolutionize how lessons are delivered. Educators can tailor the lessons, teaching methods, and resources to meet student’s needs. The rise of adaptive teaching methodology can make education accessible and student-oriented.  

• Adaptive Assessments 

Every student is different, and so is their intelligence, yet they are assessed in the same manner. With generative AI, this can change. Assessments can be designed with different difficulty levels and evaluation criteria based on students’ performance and intelligence. 

• Curriculum Design and Lesson Planning 

Curriculum and lesson plans must be regularly updated to ensure learning aligns with the current scenario. Generative AI can identify relevant topics, draw rough lesson outlines, and teach effectively. 

Apart from these, many other industries can benefit from generative AI services. All that is needed is a clear roadmap and a reliable service provider to help you actualize your ideas into results. 

How Are These Generative AI Applications Beneficial? 

Integrating generative AI apps can be a highly beneficial investment for any business. Given its growth trajectory and digital advancements, generative AI is not just a means to streamline operations but also to gain a competitive advantage. 

The main benefits of generative AI are: 

• Increased Revenue 

Leveraging generative AI’s automation and data analysis capabilities, businesses can quicken their product development. The solution can be further optimized based on customer-product interaction. As the technology matures, generative AI solutions are bound to open up newer revenue channels that might not exist at present. 

• Better Productivity 

Generative AI understands and can respond in natural language, which is the biggest advantage for many businesses. The tool can effectively summarize, translate, and transcribe data in a simple and organized manner, which saves a lot of manual labor and time.  

• Cost Reduction

The generative AI integration streamlines collaboration and reduces operational costs. Facilitating processes improves resource longevity and reduces employee workload, making the process more cost and business-effective. 

• Enhanced Risk Management 

Generative AI apps record patterns and repetitive actions. They also easily identify any discrepancies in the system, such as sudden out-of-pattern actions, and inform the concerned person. Additionally, they can identify code errors to develop a highly secure system.  

• Sustainable Solution 

Data analysis isn’t limited to gaining insights into customer behavior; it can also be used for integrating sustainable digital solutions. Businesses can leverage these insights to analyze their energy consumption and carbon footprint to design effective AI-driven solutions that benefit both their organization and the environment. 

Some Real-Life Generative AI Examples

Today, you can get off-the-shelf and custom generative AI apps to optimize your workflow. Generative AI app development is complicated, but success stories in the field show that if done right, it can be beneficial.  

Here are four top-notch generative AI examples:

• ChatGPT 

We can’t talk about generative AI applications without including ChatGPT, which was developed by OpenAI in November 2022. The model was trained on vast data and further optimized through feedback. It can converse with the user and generate human-like responses. It can also help write summaries, articles, codes, and much more. 

A free version is available on the OpenAI website for everyone and a paid version, ChatGPT+, for businesses. The latter offers additional functionalities like access to different GPT models, image generation, data analysis, etc.  

• Adobe Firefly   

Adobe Firefly is a generative AI tool for artwork and illustrations. It consists of multiple AI models that analyze text-based prompts to generate phenomenal and unique images. With Adobe Firefly, users can generate different styles of images that best suit their business style. 

Adobe Firefly also offers both free and paid plans that you can choose from at your convenience. 

• Copilot 

Microsoft’s Copilot AI can find use cases in multiple business models, including customer support, lead generation, multilingual communication, and more. Being feature-packed, Copilot can be a beneficial integration across multiple industries. 

It also offers both free and paid plans. GPT-4 Turbo is also accessible to everyone; however, free users only get access during non-peak hours. 

• Vertex AI 

Google took a completely different approach with Vertex AI and gave users a single platform to access all of Google’s cloud services. You can build and deploy ML models and benefit from its autoML feature to train, compare, and store the central model repository. 

Vertex AI is a pay-as-you-go model with no free plan, but it offers a free trial for new users to see if it fits in their system. 

How OpenXcell Can Help You Integrate Generative AI? 

Today’s business landscape poses many challenges, including constantly evolving technologies and market fluctuations. Technology is moving at a fast pace, and it’s about time to match it if you want to sustain. Generative AI applications have also spread across various industries, operations, and functionalities. 

We may not be experts in everything, but we know technology like the backs of our hands. Generative AI offers a plethora of benefits and applications that can help your business move ahead of your competitors. We can help you integrate it into your existing system. 

At OpenXcell, we design custom AI solutions that scale with your business. Our transparent services, ethical methodology, and years of expertise make us your reliable generative AI integration services provider. The only thing you need to do is connect with us and share your requirements. Our team of dedicated professionals will take care of the rest.