During the last six months the global interest in Generative AI is skyrocketing. Most conversations about Artificial Intelligence (AI) are about ChatGPT, the new Natural Language Processing (NLP) technology that leverages Large Language Models (LLMs) to enable human-like conversations with chatbots. ChatGPT broke the world record in the speed of acquisition of users: It managed to attract a user base of one million users within just five days back in November 2022 when it was first publicly released. This is a much faster pace than the respective acquisition of users from Instagram, the record holder until late 2022, which acquired one million users in about 75 days. It is a pace that seems to bring us closer to an AI-driven technology singularity.
ChatGPT is currently used by millions of users to provide information and generate texts for essays, letters, e-mails, software programs and more. At the same time, many businesses are considering its integration with their existing enterprise systems and processes to offer a human-like chat interface that fetches information timely and conveniently, without tedious web scrapping. In this context, enterprises had better consider how to best integrate ChatGPT in their business and IT strategies. To ensure that this integration is effective, they have better take advantage of best practices and lessons learnt from early adopters. Moreover, they should consider the possible evolution of this technology in the years to come.
Prompt engineering is the process of designing and building prompts for chatbots like ChatGPT. Prompts are interactive elements that allow users to talk with their AI chatbots, and they’re an essential part of any conversation. A proper prompt engineering process is the best way to design and create a chatbot that will be able to understand and effectively respond to the user’s input. Hence, companies had better invest in designing and supporting proper prompts for their applications. Likewise, their users must be trained to appropriately use these prompts. In principle, a prompt consists of the following elements:
When building an application using ChatGPT’s technology, enterprises must understand the prompt options offered by the chatbot. Users must therefore learn the most effective ChatGPT prompts i.e., prompts that lead to high quality results for certain tasks. For instance, they should learn to use prompts like “Draft a social media post”, “Structure an essay about a subject”, “Paraphrase the following text”, “Rewrite this text using a certain tone”, “find popular questions about a subject”, “Suggest articles that rank well” and many more. These prompts can be also useful when designing a new application based on ChatGPT technology, as they provide users with a baseline set of prompts for using the application.
Human oversight is very important when using ChatGPT and other generative AI technologies. This means that a human user must oversee the production and use of results produced by ChatGPT. It is very important given that ChatGPT results are not always accurate and cannot be used as produced. Rather a human user must validate their timeliness, accuracy, and overall quality. Furthermore, humans can also resolve situations where the chatbot system is unable to answer a question with confidence. Human intervention limits automation, yet it minimizes risk and potential damage from limitations of the technology.
Using ChatGPT is nowadays a skill. Contrary to popular belief, it is not trivial to get optimal results out of ChatGPT conversations. While anyone can use it, experts will get way deeper and higher quality results than average or even novice users. Therefore, enterprises must invest in ChatGPT education and skills. Workers must be reskilled or upskilled to use and fully leverage the capabilities of the technology. In this direction, companies can benefit from a very wide range of courses that are currently available in major learning platforms like Coursera and Udemy. Based on such courses, companies can learn from experts who have extensive experience on how to use ChatGPT for various practical tasks. Investing on ChatGPT education will certainly increase the productivity of employees and will improve the overall Return on Investment (ROI) from using the technology in enterprise contexts.
When using ChatGPT for enterprise applications and tasks, it is advised to go beyond the free version. It is much preferred to pay for registered access to the service, as well as for access to some tokens. The price for the registered service is very affordable. At a very small monthly fee, enterprises can enjoy access to the most up to date information, priority access (over users of the free version), much faster response times, and constant availability of the service. The pay-as-you-go plan is generally very cheap and comes with a clear cost-benefit proposition. For instance, access to the latest ChatGPT 3.5 LLM APIs costs $0.002 per 1,000 tokens, where one token is approx. 0.75 words. Based on this price it is possible to execute long queries at a cost of couple of dollars per month. The simple and flexible pricing options of the service can be found at the OpenAI pricing page.
Using ChatGPT to fetch information and generate text based on a user-friendly interface should be the starting point of your generative AI journey. The next step should be to use ChatGPT technology to revolutionize your applications. Nowadays, thousands of software developers all around the world are using OpenAI/ChatGPT technology to build enterprise applications that are faster, more intelligent, ergonomic, and user-friendly than ever before. A significant number of such applications focus on incorporating AI-driven text generation and processing. Some of the most prominent application examples including chatbots, virtual assistants, as well as advanced content analysis and generation tools. The latter applications are built and deployed across many different industries such as marketing, publishing, finance, insurance, and manufacturing. ChatGPT is an enabling technology that serves as a basis for developing a wide range of value-added applications in different areas.
Overall, recent advances in generative AI and ChatGPT based technologies promise numerous benefits for modern enterprises, including enhanced communications, time savings, and multi-lingual support in chat interactions. These benefits can be directly realized by using ChatGPT for content generation in the scope of various business processes. However, additional benefits can be realized through customization of ChatGPT applications in-line with the requirements of specific applications like customer service, content creation, and research assistance. To take advantage of ChatGPT and its customizations, modern enterprises had better follow the earlier outlined best practices. Most of them involve investing time and effort in ChatGPT processes, yet they yield considerable returns in accuracy, efficiency, productivity, and scalability. As such they must not be ignored by enterprises that implement ambitious strategies for the use of ChatGPT and generative AI in their business processes.
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