AI generated text can be a problem solver for businesses.

Generative AI is becoming a problem solver for businesses. (Image – Shuttertock)

How businesses can leverage AI-generated text

The AI-generated text has been a game changer for those who struggle with ideas and creating content. While AI-generated text programs have been around for some time, generative AI capabilities have given them a much-needed boost, especially in generating content that is more acceptable today.

Today, AI-generated text is based on AI models that are trained on vast amounts of data to understand the structure, context, and patterns of human language. They can then generate coherent and contextually relevant text based on the input they receive.

The most famous AI-generated text tool right now is OpenAI’s ChatGPT. The models of the Generative Pre-trained Transformer series have demonstrated the ability to produce human-like text across a wide range of tasks, such as writing articles, answering questions, creating stories, generating code, and more.

The success of ChatGPT has led to a huge uptake in AI research by other companies as well. For example, Google is working on Bard, its own generative AI while Apple and Meta are also looking to develop their own versions. Several Chinese tech companies are also developing their own versions of AI-generated text.

For businesses, AI-generated text can help them increase productivity and efficiency in many ways. Apart from saving time it takes for teams to come up with ideas and content, AI-generated text also helps business better plan their business strategy, especially when it comes to increasing productivity and improving the customer experience.

Three ways how businesses can leverage AI-generated text.

1) Content creation

AI-generated text can be used to produce high-quality content, such as blog posts, articles, product descriptions, and social media posts. It can save time and resources for businesses, especially those that need to produce large volumes of content regularly.

Some of the programs available for this can even generate content that is SEO focused and be tailored to individual users based on their preferences and browsing history. This allows businesses to create personalized product recommendations, email campaigns, and advertisements, leading to improved customer engagement and conversions. In sectors like gaming and entertainment, AI-generated text can be utilized to create interactive and dynamic storytelling experiences for users, enhancing engagement and immersion.

Examples include:

  • SE Ranking –  offers an AI writing tool that can help businesses quickly generate a raw draft of an SEO-friendly copy on any suggested topic/
  • Word AI – uses natural language technologies to create content that appears more unique and professional. WordAi is also available in a range of languages, making it a useful tool for companies looking to do business in international markets.
  • Copy.AI – an AI writing tool that is popular for generating content for emails, social media and marketing. It’s built on top of GPT-3 and is designed to help businesses with copywriting.
AI-generated text can power chatbots and virtual assistants to provide instant and accurate responses to customer inquiries.

AI-generated text solutions can also facilitate real-time language translation to boost customer service. (Image – Shutterstock)

2) Customer support

AI-generated text can power chatbots and virtual assistants to provide instant and accurate responses to customer inquiries. This improves customer service, reduces response times, and enhances overall customer satisfaction. AI-generated text can also facilitate real-time language translation, making it easier for businesses to communicate with global customers and enter new markets.

Examples include:

  • Pand.AI – uses proprietary natural language processing (NLP) to provide text in English, Chinese, Bahasa Malaysia and Bahasa Indonesia, making it a popular choice for businesses in Southeast Asia. Use case examples include diagnosing an existing chatbot of an insurance company in Malaysia, and redesigning the entire conversational experienceusing actual conversation data.
  • Tidio – best suited for customer support for any business and automated sales chat with connected e-commerce stores. It integrates with major website platforms, including WordPress, as well as several popular messaging channels so that businesses can deploy high-level chat solutions where ever their customers are.
  • Wiz.AI – has developed talkbots that are able to communicate with customers in several languages, including English, Mandarin, and Indonesian. They also cover informal forms such as Singlish, a blend of Singaporean slang and English, as well as Manglish, an informal variant of Malaysian English. At present, the company counts over 30 clients from various industries, including healthcare, insurance, banking, telecommunications, e-commerce, and the government.

Writing code can be completed in half the time. (Image – McKinsey)

3) Code generation

When it comes to code generation, AI-generated text can be used to generate code snippets, documentation, and automated testing scripts, streamlining software development processes. For businesses, this simply means anyone with a basic understanding of how coding works could look to use these tools to improve their products and services.

In fact, a Mckinsey study shows that software developers can complete coding tasks up to twice as fast with generative AI. The research also stated that equipping developers to be their most productive significantly improves the developer experience, which in turn can help companies retain and excite their best talent.

“Participant feedback from the study indicates that developers actively iterated with the tools to achieve that quality, signaling that the technology is best used to augment developers rather than replace them. Ultimately, to maintain code quality, developers need to understand the attributes that make up quality code and prompt the tool for the right outputs,” the study mentioned.

The most obvious examples are:

  • GitHub Copilot – Considerably one of the best acquisitions by Microsoft, GitHub Copilot has been designed to be an AI pair programmer. Unlike ChatGPT, Google Bard, and Auto-GPT, it’s not built using a general-purpose LLM. Instead, it uses OpenAI Codex, which was trained on billions of lines of code and explicitly designed to be capable of writing functional code in languages like Python, Javascript, Go, PHP, Ruby, and Swift. And this is where there are some concerns about the origins of the code.
  • Amazon CodeWhisperer – trained on billions of lines of publicly available code, it works with multiple programming languages like Python and Java, integrates with IDE, and suggests complete functions based on prompts, comments, and project code. The key difference is that CodeWhisperer is optimized for AWS APIs, including the popular EC2, Lambda, and S3 infrastructure types.
  • CodeWP – designed and trained explicitly to generate PHP, Javascript, and jQuery that’s compatible with WordPress, its plugins, and its database. Like most AI coding assistants, it’s a relatively new app, so it might not have all the capabilities developers expect, but it is under active development, with new features rolling out regularly.

Now, while AI-generated text can help businesses, organizations using the technology should also be mindful of potential challenges and ethical considerations when using it. Ensuring the generated content is accurate, ethical, and aligns with the brand’s values is crucial to maintain trust with customers and avoiding misinformation. Additionally, staying compliant with data privacy regulations and addressing potential biases in the AI model are important responsibilities for businesses utilizing AI-generated text.