Generative artificial intelligence is a form of AI that can create original and realistic data, such as text, images, music and video, based on existing data. The technology uses deep-learning techniques and large language models to create diverse and novel outputs.
Generative AI can transform many aspects of business, such as customer service, marketing, new-product development, research and decision-making. However, it also poses challenges and risks, such as data privacy, ethical issues and technical complexity. Therefore, owners of small and medium-sized businesses need to prepare well before using it. Here are some suggestions:
* First, define your business problem and goal. Before using generative AI, have a clear idea what problem you want to solve and what goal you want to achieve. For example, do you want to improve customer satisfaction, increase sales or reduce costs? What kind of data do you need to create, such as text, image, music or video? How will you measure its success?
* Second, choose an appropriate generative AI tool or model. There are many available, such as ChatGPT, Gemini, DALL-E, and Midjourney. Each has strengths and weaknesses depending on the data it was trained on, the architecture it uses and the features it offers. Choose one that suits your business domain, language and task. Also, compare their performance, cost and reliability.
* Third, customize the AI tool or model for how you want to use it. Most can handle a wide range of data-creation tasks. However, they may not work well for your specific needs, especially if your data is different from the data the AI was trained on. So, customize the AI tool by adjusting its parameters or providing specific inputs. This process is called fine-tuning and can help you improve the quality and relevance of the created data. Some tools or platforms can help with the fine-tuning process. There are more than 30,000 plug-ins in OpenAI that provide additional features. Explore some to see which one best meets your needs.
* Fourth, use and monitor the AI tool in a small scale first, such as for a marketing campaign, customer service, a meeting summary, or a data analysis. Then monitor the performance, quality and impact by collecting feedback, metrics and analytics. Also be aware of the potential risks and challenges of using AI, such as data security, ethical dilemmas and legal implications. Always follow the best practices and guidelines for using AI responsibly and safely.
* Finally, as a leader of your organization, personally experiment and learn from generative AI. Play around with it. Maybe start with AI tools for personal use, such as Microsoft365 or Google Gemini, which can help with tasks like writing emails, creating presentations or generating summaries. This will give you a realistic understanding of the capabilities and limitations of generative AI, as well as the opportunities and challenges it presents.
