This accessible, low-code program empowers future managers to understand how to apply AI strategically to innovate and streamline business processes. According to GMAC, the number of candidates who say AI is essential to their GME curricula surged from 29% in 2022 to 40% in 2023—the most year-over-year growth of any curricular option and evidence of the growing demand to learn about the role of AI in a business context.
All Rize MBA Specialization Programs, including AI, are designed to be taken in any order as to create maximum flexibility when it comes to adoption. These courses do not stack. Depending on your MBA program requirements, all students must complete the 3-4 courses below.
Generative AI (GAI) is ushering in a new age of productivity in business, and managers who ineffectively adopt it risk being outpaced by forward-thinking competitors. This course equips students to drive impact in any industry using GAI tools. You’ll learn to engineer effective prompts, integrate AI into workflows, and develop innovative GAI solutions, as well as explore ethical considerations and future trends.
Just like you wouldn’t use a financial model to drive a marketing campaign, different business use cases require different AI tools. In this course, students will explore the potential and limitations of AI technologies, learning to identify business problems suitable for AI solutions and build effective AI implementation strategies. By the end of this course, students will address key challenges and solutions in AI implementation.
Alongside powerful data-driven solutions, AI opens a Pandora's box of ethical issues: data privacy, bias, transparency, and balancing automation with human oversight. AI governance may be the biggest ethical issue of our time, something essential for any manager to understand before implementing this new technology. Students will develop AI policies for ethics and compliance, mitigate AI-related risks, and communicate governance standards to stakeholders.
AI projects can help predict trends and optimize operations, allowing businesses to understand not just what has happened but what will happen—and what should be done about it. By the end of this course, students will be prepared to drive financial and operational impact by managing AI project lifecycles: developing comprehensive project plans, managing data and models, ensuring effective deployment, and communicating progress and outcomes to stakeholders.
