Managing Teams with AI Generated Summarizations and ChatBots

Introduction:

The era in which we live is experiencing rapid globalization and expanding corporations, the challenges faced by senior management staff in large organizations are becoming increasingly complex. As teams grow, maintaining standardization, implementing effective education initiatives, and navigating transitions to new technologies become daunting tasks. However, the field of generative AI provides a powerful solution to address these challenges. Finance is the field of managing money and how individuals, companies, and government groups intake and spend money. Just by definition, it is apparent how much interactions and information goes into the field of finance. As the world’s economy grows, the amount of data storing and interactions between companies and people will only rise exponentially as well. Therefore, it is important to install some sort of technology to mitigate the troubles of an expanding economy and managing teams, and this revolution has come to fruition with generative AI techniques.

Creating a cheaper, more efficient option to answering every employee’s questions is a way to significantly assist finance professionals, since AI tools can provide quick ways to do a task for the organization. By leveraging generative AI, very large corporations can efficiently manage their teams by providing a cost-effective and streamlined means of summarizing complex concepts for their employees. This paper explores how generative AI can be harnessed to distill large amounts of information for finance professionals, focusing on maximizing understanding, accuracy, and usefulness.

The Problem:

As corporations expand and teams multiply, the need to summarize information effectively becomes crucial. This is particularly true for very large corporations with hundreds of locations and thousands of employees, such as international financial firms. The process of educating employees on specific topics becomes increasingly challenging as the same questions are repeated, requiring senior experts to invest significant time and effort in providing detailed answers. The same is true for employers who have decided to reshape their company by adopting new models in the workplace. For instance, if you have a team of hundreds of developers, it is quite difficult to transition from object-oriented coding (java) to reference coding (python). This situation not only hampers the progress of critical projects but also limits the experts' ability to provide comprehensive responses. Consequently, employees are often directed to reference extensive tutorial guides, resulting in a lack of personalized and efficient information delivery.

Using Summarization as a Means to Educate Teams:

Generative AI presents a viable solution to the problem of concept summarization in large corporations. In the aforementioned example, tutorial guides and instruction pages for various topics can be utilized as training data for generative AI models. By leveraging natural language processing and machine learning techniques, generative AI tools can be employed to develop intelligent chatbots capable of relaying summarized information to employees with questions. Interactive and context-aware chatbots can serve to be useful in the sense that this approach pushes for engagement from employees as well as ensures that employees receive relevant information without wasting anyone’s valuable time. This approach not only saves time, money, and resources but also ensures consistent and standardized knowledge dissemination throughout the organization.

To maximize the effectiveness of generative AI in concept summarization in the workplace, it is essential to focus on understanding, accuracy, and usefulness in the output provided to employees. Therefore, it is important to train on high quality information specific to a corporation's needs. After training the initial generative AI model, a fine-tuning process can be implemented using expert guidance. Finance professionals and subject matter experts can review and validate the generated summaries to enhance accuracy and align the output with domain-specific knowledge. This iterative process helps refine the model's performance and ensures the delivery of accurate and reliable information to employees.

To be given a quick summary about a topic of your choice, try it here. The topic doesn’t need to be technical, but some examples you can try include liquid ratio, cost accounting, zero-based budgeting, mergers and acquisitions, and so on. Experiment! See for yourself how quick summaries can be constructed by using generative AI.

Moreover, leveraging advanced natural language generation techniques, such as abstractive summarization, can enhance the usefulness of the output. Abstractive summarization enables the generative AI model to create concise summaries that capture the key points of complex concepts for employees. By focusing on the most relevant and important information, employees can quickly grasp the core ideas without being overwhelmed by extensive documentation.

Conclusion:

Generative AI offers tremendous potential in providing effective concept summarization for employees in very large corporations, particularly in the finance sector. By leveraging generative AI, organizations can streamline the dissemination of knowledge, save time and resources, and improve the accuracy and usefulness of information provided to finance professionals.

Summarization is just one of many possibilities that professionals in finance and business leaders can use to educate their employees. Generative AI is and will continue to revolutionizing how companies approach educating large teams, especially how businesses approach explaining topics to teams that manage finances. If you are interested in promoting your business to a new level, it is never too late to start testing the waters for your company.