Generative AI In Creative Works: Better Productivity In Content Creation For Professionals And Businesses

This post talks about the application of generative AI in creative works and the relative impacts it delivers on the works of businesses and professionals. I have tried my best to make it a brief and quality reading experience for readers wanting to know how AI innovates content generation for businesses and professionals.

Generative AI (also referred to as language and image AI models) is believed to be a boon for individual professionals and businesses in content generation. For example, it helps them generate automated content, enhance content quality, and improve content variety. Besides, the technology helps personalize content in tune with customers’ discretion, thus boosting their productivity in content design and creation.

How Generative AI Is Boosting Productivity In Content Generation

Generating Automated Content

Generative AI models can carry out automated content generation. These tools help create new articles, blog posts, or engaging social media posts. As a result, your brand will have increased value in the long run. That’s why generative AI tools, such as Midjourney are time-saving technologies. Corporate houses and individual professionals use generative AI in creative works to drive productivity in content generation.

Better Content Quality

Applying generative AI in creative works helps professionals and companies create high-quality content whenever needed. AI tools generate content based on prompt engineering done by a user. Moreover, content generated by these tools also sounds great to readers, thanks to the level of quality they exude.

How generative AI models create high-quality content has its scientific reason. They, in fact, go through intense training processes on huge datasets. They are trained to learn and identify contextual nuanced, patterns and semantics. Through years of training, they finally start to learn how to generate high-quality, accurate, and informative content as per the user-given prompts.

More Diversified Content

Businesses and individual professionals can use generative AI models to create a variety of content types, ranging from text to images, videos, and so on. Apparently, these models come in handy for these users in designing and creating more diverse and engaging content for a wider range of audiences. Diversification in content generation of this level was not in sight before. Perhaps due to human cognitive and physical limitations.

Personalized Content

Generative AI models are trained machines. They intuitively help users create personalized content to the tune of their prioritized users/audiences. So, as a businessperson or an individual professional, these tools come in handy for you to generate readers-focused, engaging, authentic, and optimized content. You will give a personalized touch to your target audiences looking for content that resonates with their preferences.

Recommended Read – Top 10 Generative AI Trends In 2024 And Beyond

Generative AI In Creative Works – Exemplifying How AI Models Help Create Content For Businesses And Professionals

OpenAI’s large language model (LLM) GPT-3 can create texts according to a user’s prompts. The generated texts by this tool reflect the strength and proficiency of this technology. These models are sensitive to the user’s prompts and act accordingly in a reasonable way. The texts look grammatically fine and appropriately structured. Conclusively, these tools tell the full significance of their potential values for businesses and professionals.

No doubt, the impacts of generative AI models on content creation are already felt worldwide. Besides, they influence marketing, design, software, entertainment, and interpersonal communication. You can say generative AI models are incredibly diverse. They can be used to create content such as images, video recordings, longer text formats, social media posts, and so on. They can do sentiment analysis, answer questions, and whatnot. Here is the breakdown of generative AI best use cases.

Generative AI Use Cases In Creative Works

Using Generative AI For Marketing

The efficiency of generative AI models finds their respective applications in diverse business functions. If we talk about the marketing application of the models, they are very common. For example, based on GPT-3 architecture, the models can help businesses create blogs, social media posts, sales copies, and other marketing-related and customer-focused content. Jasper, ChibiAI, and Copysmith are some of the most common and popular GPT-3 generative models contributing their respective efficiency to the marketing needs of businesses and individuals.

List of GPT-3 based Generative Models:

  • Jurassic-1 Jumbo: You can use this generative model to create different text formats, including code, poems, scripts, emails, letters, musical pieces, etc.
  • Megatron-Turing NLG: This generative model can create text, translate languages, and generate various types of creative content.
  • Bard: It is Google’s brainchild AI language model trained on a large dataset of code and text. It can generate various types of creative text formats and answer users’ questions. It is now rebranded as Gemini.
  • BLOOM: This generative model can create text and translate languages.

Generative models based on GPT-3 models can help you create content optimized for search engine placement consequently leading to significant improvements in your business.

Note Generative Pre-Trained Transformer 3 (GPT-3) is a consortium of large language models, not a single model. Created by OpenAI, the model leverages Deep Neural Network that utilizes an attention mechanism to make out and process text. As a result, GPT-3 architecture analyzes the relationships between words and predicts the next word in sequence. That’s why it can generate texts, translate languages, and create different types of content, as well as answer a user’s prompts.

Using Generative AI to Generate Code

Saying that the generative AI model has become way too advanced to generate code effectively would be an overstatement, considering the models are still in their developing phase. However, there is no doubt in admitting that the AI models have proven their efficiency in generating computer program code, thanks to GPT-3’s exceptional Codex program that can generate code in different languages.

Moreover, Microsoft’s Copilot which is based on a large language model is a coding wizard that can generate code in any programming language one can imagine. Talking about Codex, the AI model can also help developers identify bugs and fix errors in its code, including the fact that the model can explain the behavioral pattern of the code. The purpose here is not to drive human programmers out of the job but to help them improve their efficacy and speed.

It is worth noting that any likelihood of eliminating human programmers is zero, given code generation Large Language Model (LLM) has its limitations. That’s because a larger program can’t accommodate the integration of LLM-based code generation as well as the integration of the program into a specific technical environment unless supported by human programming capabilities.

Using Generative AI as A Conversational Technology

The application of large language models as conversational AI or chatbots is a known fact these days. These generative models are trained to understand conversation and context awareness. Therefore, they can maintain easy conversations with humans without breaking off the context. An example of BERT of Google is worth noting in this context. The technology is applied to understand the search queries of users and is used as a part of Google’s DialogFlow chatbot engine. Though these models are not perfect in conversational behavior, they will be, given they are still learning to mimic human emotions.

Generative AI In Creative Works For Knowledge Management

Generative AI models are said to contribute significantly to educational institutions or organizations in terms of managing knowledge based on texts or videos. Since large companies find it difficult to create (labor-intensive) structured knowledge bases, involving generative models is seen as an effective strategy to solve the problem, especially when the models are well-trained on a specific body of knowledge within a company. As a result, the stored knowledge within the model can be accessed through prompts by the users.

Impacts Of Generative AI In Creative Works For Knowledge Management – At A Glance

  • AI models can automatically translate raw data into a well-structured, informative article, saving time and resources for human experts.
  • Generative models can create quick summaries of key information according to a user’s specific needs and level of knowledge, thus saving a huge time from surfing through voluminous data.
  • AI-powered chatbots can help users find relevant information or solutions quickly and easily.
  • Advanced generative AI models pioneer intelligence in semantic search, enabling more accurate search results for knowledge-seeking users.
  • These models help knowledge-seeking users get the search results specific to their interests and needs. This helps users not to experience information overload. The models produce personalized recommendations to the users based on the study of their past behaviors, actions, and interactions.
  • Individuals or businesses seeking more relevant and quality information about their current project or task can simplify so by using AI models. Generative AI models can proactively suggest data or information relevant to your project or task.

Generative AI In Creative Works – FAQs

What Is The Application Of Generative AI In The Creative Industry?

Generative AI in creative works of designers, artists, and other creative specialists drives efficiency. For example, generative AI tools such as DALL-E 2 (for images), Jasper (for text), and Mubert (for soundtracks and background music) assist professionals in their creative works. Video-creating AI tools like Synthesia, Runway, Fliki, etc. help creative professionals generate video content.

Is Midjourney A Generative AI Tool To Create Video Content?

No, you can’t create a full-fledged video from scratch using Midjourney. Just like DALL-E of OpenAI and Stable Diffusion of Stability AI, Midjourney can be used to create images based on prompts. It is primarily an image generation tool, though it has some functionalities to create short video snippets. To say otherwise, with Midjourney, you can see a short video clip that gives you a visual demo of how it creates a collection of images arranged in a tabulated or square grid format.

Is There Any Difference Between Generative AI And AI Tools? Or Both Are Same?

Generative AI is not the same as any AI tool. While generative AI focuses on specific functionalities, like creating new content, AI tools involve a broader range of functionalities. They can perform tasks, such as data analysis, automation, identifying patterns, make predictions. Note that AI tools don’t generally involve new content creation. That’s not their primary function. You can see them being used in facial recognition in security systems, chatbots for customer service, and filtering spammy emails.

With Generative AI Fully Capable Of Creating New Content Quickly, Will It Replace Human Creativity?

Generative AI requires human intervention for prompts and guidance to create new content. These tools are not to replace human creativity but to assist it with new ideas to boost creative imagination. So, you can use generative AI tools to enhance your creativity or explore new ideas for your blogs, images, or video content.

Does A Person Have To Be Creative To Use Generative AI In Creative Works?

While generative AI tools are programmed to be user-friendly, I think at least a certain degree of creativity is needed. To say differently, you must know how to do prompt engineering, at least at a basic level. These tools are just machines that depend on your instructions to generate output. If you don’t know anything about how to use a generative AI tool, you will not maximize its creative potential. However, even if you don’t know anything in the first place, with experience, you will get a hang of it. And then using the tool will be a delightful experience.

How Will Generative AI Impact The Future Of Creative Industries?

The most obvious change will be the increased pace of innovation in generating new content. It will pioneer new creative forms. Besides, access to creative tools will likely be democratized in creative industries.


The use of generative AI models in creative works can undoubtedly bring numerous advantages for businesses and individuals. From automating content creation to generating diverse and multi-format content for marketing purposes and knowledge management, generative AI models excel.

However, there are certain challenges in the application of generative AI models as well. For example, Deepfake AI has already earned notoriety worldwide for being used to create blackmail materials to wrongly frame victims.

Moreover, the reports of fraudsters and scammers tricking people into fake investment schemes using deepfakes are already making headlines in global news sites. In India, deep-faked images of celebrities shocked the netizens. Moreover, the identities of many celebrates were compromised as their deep-faked images were shown doing fake endorsements.

Bottom line: There are serious ethical concerns behind the application of AI models. OpenAI’s latest brainchild invention Sara has now intensified the ethical concerns of artificial intelligence. In fact, questions are rising about what is fake and what is original today. Though Sara is not yet officially green-lit for public use, the uniqueness of its creativity in generating lifelike videos poses grave concerns as to the safe use of AI in the future.

With all is said and done, Generative AI in creative works is undoubtedly helpful in innovating our content generation. Though they may influence content ownership and intellectual property somehow, we can’t rule out the capabilities of AI models excelling our knowledge and creative work. As far as the ethical application of artificial intelligence is concerned, it requires careful monitoring and government-backed regulations.

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