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, generative AI, and agentic 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
Artificial Intelligence is set to impact every part of your organization, from optimizing back-end business processes to enhancing customer experiences. AI enables organizations to rethink their core processes and gain a competitive edge in the industry. The impact of AI in how businesses operate is evident in sectors like manufacturing, distribution, transportation, professional services, and healthcare—and this transformation is only accelerating.
This module offers a structured framework to help you effectively leverage AI to optimize your business processes. You will also gain the skills to create AI roadmaps and prepare your organization for change.
Key Takeaways:
- Explore Assessment Methods: Understand the tools and methods for assessing processes to identify areas for improvement.
- Perform Rapid Process Assessments: Conduct assessments to pinpoint key processes that are likely to benefit from AI integration.
- Evaluate Readiness for AI: Assess your organization’s readiness to implement AI-driven process optimization effectively.
- Develop an AI Roadmap: Create a strategic roadmap to align your organization on the overall vision, goals, and milestones for your AI program.
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
This module explores the transformative role of AI in modern supply chain management, offering a discussion on how traditional practices are being reshaped by data-driven technologies and global interconnectivity.
Through interactive scenario-based exercises, strategic proposal development, and ethical reflection, participants will leave with both strategic insight and practical tools for driving AI innovation within their supply chain operations.
Key Takeaways:
- Reflecting on the journey from foundational supply chain concepts to advanced AI-driven applications
- Impact of core AI technologies (natural language processing [NLP], predictive analytics, machine learning and computer vision) on demand forecasting, inventory optimization, logistics, and supplier management
- Emerging trends in areas such as contract automation, smart warehousing, and autonomous vehicle logistics
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
The Future of Work in an AI-Accelerated World
This dynamic module explores how AI is reshaping the world of work: transforming the careers we will pursue, the AI coworkers we will collaborate with, and the competencies we will need to thrive. Structured in three parts—across New Careers, New Coworkers, and New Competencies—this session unpacks the profound shifts in roles, responsibilities, and required skills, and integrates targeted exercises in each section to reinforce applied learning.
In addition to the Future of Work, this module features a special segment on the Future of AI, spotlighting 10 emerging trajectories that will define AI’s evolution over the next five years.
Key Takeaways:
- 8 Forces Shaping the Future of Work
- Common AI Myths & Misconceptions
- How AI Augments Professions
- The 4 Roles AI Will Play in Your Work and Life
- New Employer Expectations in the AI Era
- Mindset Shifts for the New Work Culture
- Essential Skills—Both Digital and Human
- 10 Shifts Driving the Future of AI
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.