Effectively Integrating AI Into Your Team
Objective
By responding to end-of-module prompts, learners will demonstrate knowledge of methods effective leaders can use to integrate AI into their teams.
Introduction
View the video below for an introduction to this module.
Examples
Read the following exemplars to solidify key points made in the introductory video.
Andrew works at a company of over 5,000 employees. He leads a team of 20. He has noticed a range of sentiments about AI within his team. Some are enthusiastic about its possibilities and others are convinced they will be out of work in the next year. After educating himself on various LLMs and having numerous discussions with engineers at the company, Andrew organizes monthly informal sessions where both members of his team as well as others at the organization can share their techniques and experiences with AI. He also invites more proficient users to come and talk about the importance of using good prompts and ethics. He notices morale of some of the more fearful team members begin to improve.
Natalie works at a medium-sized company. She is an executive in the sales division. She is beginning a sales forecast report for the next quarter, and her director has encouraged her to utilize AI “just to see what it can do.” The outputs she is receiving from the LLM have not been helpful. She realizes that much of what is being returned is not tailored to her company. She decides to feed the LLM specific data points, relevant trends, and crucial internal processes. What she receives is much more relevant information that she then uses to supplement her report.
Susan is a financial analyst at a Fortune 100 company. She feels confident in her ability to make AI work for her. After attending a quarterly meeting the previous day, she asks the LLM to illustrate how the quarterly report might predict growth in the upcoming 2 - 3 years. What she receives is encouraging. However, from the AI-focused trainings she has attended, she has learned to scrutinize the information that she receives from the LLM. After re-checking her work, she realizes that by prioritizing the most recent quarterly report, she has introduced recency bias into the prompt, which has given her inaccurate information. She updates the prompt accordingly.
Comprehension Check
Use what you have learned in this module to answer the following three questions. This is an ungraded comprehension check, designed for you to gauge your own learning.