How to use Generative AI for Leaders, Executives, and CEOs

Name: How to use Generative AI for Leaders, Executives, and CEOs
Rating: 4.2 (22 reviews)

Drive Growth and Innovation With Artificial Intelligence with ChatGPT, Gemini, Claude, and more

Created byJustin Barnett, Jan A

Last updated 4/2025

English

English [Auto],Korean [Auto],

What you'll learn

This practical course will teach you how to develop a comprehensive AI business strategy to drive growth and innovation in your organization.
You'll learn how to identify specific areas of your business primed for AI disruption, strategically leverage AI for product enhancement
Understand the critical role of data in fueling successful AI initiatives, and master effective data collection and management strategies
Explore AI's transformative impact across various business functions, including marketing, human resources, product development, and more.

Course content

5 sections • 25 lectures • 2h 18m total length

How to make the most of this course2:41
Familiarize yourself with Udemy course interface to maximize learning, explore the homepage, lectures, and downloadable resources such as cheat sheets, note cards, and images, and use Q&A and learning tools.
Definitions and Acronyms used in this course5:25
Define key ai concepts and acronyms such as large language models, generative ai, and transformers. Explore learning terms like prompting, ai agents, multimodal lms, model weights, and inference.
Connect with Me0:53
Connect with fellow classmates and the instructor by joining the Facebook group 'ChatGPT and Gen I for content' for enrolled students to ask questions and discuss gen AI topics.

What is Artificial Intelligence9:51
Explain artificial intelligence, its transformer and GAN foundations, and how leaders package AI as a service, open source self-hosted, workflows, or consumer products, while aligning data and APIs for success.
Why learn about Generative AI?7:51
Learn why generative AI matters for leaders and executives, explore its human language interfaces, productivity benefits, and key use cases across marketing, software, and operations.
What is RAG (Retrieval Augmented Generation)6:41
Enhances llm responses by using retrieval augmented generation to combine internal and external sources. Demonstrates fast implementation, embeddings, vector stores, and practical use cases like medical records and customer support.
What is MCP (Model Context Protocol)8:29
Explore the model context protocol (MCP), an open standard USB-C for AI that enables vendor-neutral AI integration through a hub of tools, resources, and data sources in a client-server architecture.
How do Transformers work10:12
Explore how transformers use attention to power generative ai, explain encoding, n-grams, and inference for llms, and discuss why llms hallucinate and how prompts guide output.
Hands on Activity: Exploring ChatGPT as a end user product4:08
Explore the ChatGPT interface to prompt, tokenize, and route requests to text or image models like DALL-E, illustrating a model-as-a-service workflow for writing, brainstorming, and planning.
Self Hosted Open Sourced LLMs vs Closed Source10:40
Compare closed and open source LLMs, weigh self-hosting against managed hosting, and learn how data control, customization, and cost influence your AI strategy.

Using AI to enhance Marketing5:14
Leverage AI in marketing operations with tools like ChatGPT, Gemini, Copilot, and Adobe to generate content, personalize experiences, localize website copy, and support marketing research and change management.
Generative AI in Human Resources4:22
Leverage generative ai in human resources to automate content and admin tasks, craft bespoke onboarding and recruitment workflows, and guide employee benefits via rag models and chatbots.
Generative AI in Innovation and Product Development2:18
Leverage artificial intelligence to fuel ideation and product development by uncovering unknown unknowns through prompts, and use text-based AI for brainstorming, processing customer data, and software development.
Hands on Activity: Exploring NotebookLM4:29
Explore Notebook LM, a Google tool that builds a custom data-driven LM from your documents, with up to 50 sources including drive docs, slides, YouTube links, and websites, prompting queries.
Case Study: Buzzfeed integrates AI into their product lines3:11
BuzzFeed demonstrates how leaders can harness generative AI by turning quiz responses into prompts and sending them to the ChatGPT API for on-the-fly, staff-curated content ideas for the website.
Case Study: Using Github Copilot for Software Development3:51
Analyze a case study of GitHub Copilot, an AI pair programmer using OpenAI Codex to suggest real-time code. Explore productivity, code quality, and licensing concerns.

Hands on Activity: Exploring ChatGPT for Image Generation10:25
Explore autoregressive image generation in ChatGPT, learn to craft prompts and edit images in a multi-step, context-driven workflow, and compare with diffusion models.
Auto Regressive vs Diffusion Image Generation Models5:28
Compare autoregressive and diffusion image models, noting autoregressive builds images left to right to preserve text and context. Expect slower, compute-heavy generation but potentially more unique, contextually consistent results.
Hands on Activity: Using Google AI for Generating Video and Text to Speech8:20
Explore Google Media Studio within Vertex AI Studio to generate video, images, audio, and music using Vo2, Imagine 3, and Lyra; experiment with text-to-speech for podcasts, voiceovers, and multilingual output.

The role of leaders in driving AI adoption3:16
Lead with a clear AI adoption vision, prioritize high impact use cases, and align with business strategy. Build talent, foster experimentation, and champion data driven insights and ethical AI practice.
Building an AI-ready culture2:55
Promote an ai ready culture from the bottom up by sharing internal ai wins, providing free ai education, and aligning ai with business goals while fostering psychological safety for experimentation.
Developing an AI business strategy5:13
Develop an AI business strategy by identifying vulnerable areas and bolstering them with AI. Integrate AI to enhance product offerings, optimize data collection, and upsell advanced features for customer value.
Identifying opportunities for AI improvement5:24
Identify opportunities for ai improvement by recognizing limitations and data biases to support continuous, ethical development. Implement feedback channels, monitor metrics, and apply explainable ai to improve real-world applications.
The Future of Work: Navigating the AI Revolution3:43
Navigate the AI revolution shaping the future of work by embracing automation, upskilling, and new leadership approaches. Build human machine partnership with remote work, lifelong learning, and empathetic, transparent leadership.
Responsible use of generative AI3:09
Lead with responsible AI by upholding fairness, transparency, accountability, privacy, and security, address biases, and establish policies, audits, and an ethics committee to guide ethical deployment.

Requirements

No programming experience needed
No prior experience with AI needed

Description

● Identify areas within your business that are poised for AI transformation. This involves recognizing both the opportunities AI presents, as well as the areas where AI could potentially disrupt existing business models. For instance, the course examines the case of Shutterstock, whose stock value plummeted due to the emergence of AI-powered image generation tools.

● Develop a data strategy that effectively leverages the wealth of information your business collects. Data is the foundation of AI, and this course will guide you in establishing a comprehensive data strategy, encompassing collection, cleaning, storage, and accessibility. This includes techniques such as gathering customer data through reviews and surveys, collecting website analytics, and ensuring regular data integration from tools like CRM and email management systems.

● Understand the different ways AI can impact various business functions, including marketing, human resources, and product development. For example, in marketing, AI can be utilized for content generation (blog posts, ad copy, website copy), personalization (dynamically generating emails, targeted product recommendations), creative asset generation (images, videos, audio), and market research (analyzing customer sentiment, identifying trends). In human resources, AI can automate tasks like writing job descriptions and onboarding materials, improve talent acquisition through candidate screening and personalized communication, and enhance employee happiness through personalized benefits recommendations and educational chatbots.

● Cultivate an AI-ready culture within your organization. This involves promoting internal awareness of successful AI implementations, providing accessible AI education and training for employees, integrating AI goals into existing business objectives, and fostering a safe environment for experimentation with AI tools.

● Embrace the role of an AI-powered leader. This requires continuous learning about AI advancements, actively advocating for AI adoption across the organization, promoting data literacy, and championing ethical AI development and deployment.

Who this course is for:

Business leaders and executives seeking to integrate AI into their strategic vision and drive organizational growth.
Entrepreneurs looking to leverage AI for competitive advantage and disrupt traditional business models.
Managers and professionals aiming to understand and apply AI in their roles to increase efficiency and impact.
Anyone interested in the future of business and the transformative potential of artificial intelligence.

How to use Generative AI for Leaders, Executives, and CEOs

What you'll learn

Explore related topics

Course content

Introduction to the Course3 lectures • 9min

What is Artificial Intelligence7 lectures • 58min

Integrating AI for Operations6 lectures • 23min

Integrating AI for Generating Creative Assets3 lectures • 24min

Integrating Generative AI into Business Strategy6 lectures • 24min

Requirements

Description

Who this course is for: