Mini-MBA: Artificial Intelligence Curriculum

Introduction to AI

AI technologies continue to expand their capabilities to perform human tasks, gaining interest from companies that seek to invest and embark on a transformational journey to improve the efficiency and effectiveness of their operations, products, and services. Before adopting these new technologies in their organizations, it is critical for leaders to understand what AI can do, the benefits it provides, and the challenges that might be encountered. Learn how different types of AI can be used for different purposes.

Key Takeaways:

  • Understand the general principles of automation with technology
  • Understand the hype and reality of AI dangers
  • Distinguish the different types of AI and what they are best used for
  • Choose who you need on your team for your AI project
  • See how machine learning and generative AI work

Data Analytics

Data is the fuel of AI. Artificial Intelligence projects do not follow the same precepts as traditional programming projects. While they can use similar agile processes, they are not designed to add features and functions as they mature, but rather to use data to improve accuracy. Learn to identify data readiness for your potential AI project and to optimize the process of using data to solve the problem.

Key Takeaways:

  • Understand how data is used with different AI techniques
  • Identify projects whose data makes them conducive to the use of AI
  • Address problems with your data
  • Explore the AI improvement process using data

Process Optimization

AI and machine learning are general technologies which will impact every aspect of your organization. It will allow for the reimagining of work by leveraging innovative technology and applying it directly to core processes essential to your organization. Its impact is already being felt in manufacturing, distribution, transportation, professional services and healthcare. This change will only accelerate.

This module provides a framework to help you leverage AI in processes you identify as critical to your organization, create AI roadmaps, establish pilot programs and prepare your organization for change.

Key Takeaways:

  • Conduct a “rapid process assessment” to identify key processes most likely to benefit from AI
  • Understand the level of change AI will cause and evaluate its impact on the company
  • Develop an AI roadmap that helps align the organization around change

AI for Customer Service and Customer Experience

Customer service and customer experience are increasingly important ways for brands to differentiate from the competition. The problem is that truly top-notch customer service is frightfully expensive, which is why most customer service is mediocre—or worse. AI can improve customer service and customer experience at a lower cost, which can prove a game-changer in many situations.

Key Takeaways:

  • How data privacy regulations affect customer data collection
  • How chatbots and smarter search answers customer questions
  • How to use social media listening to predict brand health
  • How to improve customer journeys

AI in Marketing and Sales

For the last 25 years, digital technology has quietly revolutionized marketing and sales. But AI might make even bigger changes in the next few years. Marketing and sales have always needed the human touch—and they still do. But AI has the ability to automate some tasks that could be performed only by people in the past.

AI won’t take away the jobs of marketers and salespeople; however, the ones who risk losing their jobs are the ones who won’t use AI themselves.

Key Takeaways:

  • How to analyze data to find your best customers
  • Improving site search to improve conversions
  • Determining the best marketing message for each customer
  • Implementing advanced attribution modeling
  • How to improve lead scoring

AI for Supply Chain

Artificial Intelligence (AI), along with other advancements in data analytics, has been changing how supply chains are managed nowadays. Many executives have reported revenue increases and cost savings from AI adoption in business units. As many businesses are at the turning point of adopting AI in their supply chains, it is critical to study successful applications and key challenges. It is also helpful for business leaders to understand the people factor and risks associated with the transformation.

Key Takeaways:

  • Understanding of supply chain functional areas, and their usage of data
  • AI applications in supply chain functions (procurement, planning, warehousing, logistics, etc.)
  • Challenges and risks of adopting AI, especially for small- and medium-sized businesses

AI in Finance

Recent advances in AI have demonstrated to non-technical people the power of this family of technologies. While AI won’t replace every finance professional, it will eventually change the way all financial professionals perform their day-to-day work.

During this module, we will walk through examples of six use cases within the finance function where AI has the opportunity to transform the way business is conducted.

Key Takeaways:

  • Understanding of the corporate finance role
  • Discussion of the AI technologies that are relevant for finance practitioners
  • A look at how AI technology can be applied to the major processes within finance

Ethics in AI

There is no doubt that AI presents an opportunity for radical advancements in many fields such as agriculture, manufacturing, medicine, computer science and cybersecurity, to name a few. However, with each advancement comes a number of questions and concerns, ranging from business to legal to ethical implications. There is no easy answer to these questions, but they cannot be ignored.

This module will center around the advent of AI and how the business community, and any community for that matter, should view AI from an ethical and legal viewpoint.

Key Takeaways:

  • Consider the ethical and legal implications of using AI systems
  • Be better equipped to evaluate business decisions related to AI
  • Gain a deeper understanding of the impact of bias and computational errors in AI

AI’s Impacts on The Future of Work: New Careers, Coworkers, and Competencies

This module explores the significant ways that AI, Automation, and Robotics are transforming The Future of Work. Specifically, we’ll delve into three overarching impacts: the emerging careers that humans will pursue; the rise of machine coworkers designed to enhance productivity and job satisfaction; and the essential competencies required for future success, which will encompass both technical proficiency and emotional intelligence... along with the strategic imperative to continuously refresh worker skills as AIs evolve and advance.

Key Takeaways:

  • A look at how the nature of human jobs will shift toward problem-solving, strategy, and creativity as machines take on more tasks traditionally performed by humans
  • Reframing our understanding of teamwork in the context of human-to-machine collaboration
  • How to merge human capabilities with machine efficiencies in pursuit of a more productive, creative, and fulfilling professional life
  • The ways in which AI places a premium on skills that machines can’t replicate (such as emotional intelligence, critical thinking, and adaptability) and necessitates a commitment to reskilling over time

AI for All: Roadmap to Success

This module demystifies how AI projects span across the spectrum, from exploration to disruption. Whether you're intrigued by the operationalization of AI use cases, the integration of AI in business strategies, or the future of GenAI, this session is tailored to unveil the layers of AI's impact on various industries and domains.

Through real-world case studies, practical insights, and forward-thinking ideas, we will provide a framework to harness actionable strategies and envision how AI can be your business multiplier in the ever-changing digital arena.

Key Takeaways:

  • Learn how AI projects are planned across the spectrum
  • Explore key approaches to target and identify the right AI problems
  • Determine key metrics to evaluate the success of AI
  • Examine the future of AI: Is GenAI (generative AI) different?

Program Overview

For an overview of our Mini-MBA: Artificial Intelligence program plus program benefits and outcomes, please click here.