Generative AI for executives: A primer
Generative AI is a powerful, multi-purpose tool for the workplace. Executives can use it to boost efficiencies, reduce costs, and empower their workforce, all crucial for maintaining a competitive edge in today's business landscape.
No time to read? Get answers to your generative AI questions using our Generative AI Executive Advisor chatbot.
What is generative AI?
Generative AI (GenAI) refers to a category of AI designed to generate content, data, or other outputs that are similar to human-created content.
GenAI tools have the capability to generate new, original data or content, often in the form of text, images, audio, or even video.
Generative AI can be used for tasks such as creating human-like text, generating artwork, and completing code.
How does generative AI differ from traditional AI?
Generative AI specializes in creating new content, such as text, images, or music, based on patterns it learns from large datasets.
Traditional AI, in contrast, focuses on analyzing data and making decisions based on predefined rules or algorithms.
Generative AI is more adaptable and creative, excelling in tasks that require innovation and a human-like understanding of context.
Traditional AI is often more efficient and reliable for structured tasks, like data processing or logical problem-solving, where clear rules can be applied.
Go deeper
Watch a short video from Gartner covering the opportunities and challenges with generative Ai.
Why does generative AI matter to executives?
Generative AI scales your business
Generative AI has rapidly progressed from a novel concept to a scalable business tool. Businesses are successfully integrating it into various functions, such as customer service and fraud detection. PwC's $1 billion investment in an "AI factory" exemplifies this trend, demonstrating the feasibility and urgency of scaling generative AI in a responsible manner.
Generative AI is already transforming your workforce
Your employees are already using ChatGPT. Generative AI is transforming job roles across organizations. Employees, irrespective of their technical knowledge, will increasingly interact with AI, necessitating new skills and roles like "prompt engineer" and "model mechanic." This transformation underlines the need for a synergistic approach involving strategy, legal, and data teams.
Generative AI is ushering in an innovation and R&D paradigm shift
Generative AI is altering the traditional build-versus-buy debate, particularly in R&D and product development. Companies are reevaluating their innovation strategies, focusing on adapting AI models to their specific needs rather than developing new products from scratch, and recognizing the importance of strategic partnerships and data assets.
Go deeper
Learn how Generative AI is evolving and what leaders need to know about generative AI in their organizations in the McKinsey report, What every CEO should know about generative AI.
What are some generative AI product examples?
ChatGPT
The product that introduced the masses to generative AI. Built by OpenAI, ChatGPT can answer your questions, write copy, draft emails, and more.
MidJourney
Midjourney generates images from text instructions (prompts) Similar products includes DALL-E and Stable Diffusion.
Github Copilot
GitHub Copilot suggests code completions as developers type and turns natural language prompts into coding suggestions.
Writer
An AI-powered writing assistant that can create blog posts, marketing content, and more while adhering to your brand guidelines.
Perplexity
A search chatbot using generative AI that offers exact and complete responses to user inquiries.
Pi
A personal AI, designed to be supportive, smart, and there for you anytime. Ask it for advice and answers.
Runway
Runway is like a new video editor. It's a complete AI-powered video production studio, capible of creating videos from text.
Eleven Labs
Add your pricing strategy. Be sure to include important details like value, length of service, and why it’s unique.
Typeface
An generative AI content workflow platform to create brand stories and campaigns
What are common enterprise generative AI use cases?
Content generation and enhancement
Generative AI is adept at creating high-quality written content, from marketing copy to technical documentation. It can also enhance existing content by making it more engaging or tailored to specific audiences.
Product development and innovation
AI can assist in the design and development of new products by analyzing trends, customer feedback, and performance data. It can also generate creative ideas for product innovation.
Data analysis and insights generation
AI can analyze large volumes of data and generate insights. This can be particularly useful in areas like market research, customer behavior analysis, and financial forecasting.
Personalization at scale
Generative AI can tailor experiences and content to individual users or customer segments in marketing, e-commerce, and content platforms. This personalization can significantly enhance customer engagement and satisfaction
Customer service automation
AI-powered chatbots and virtual assistants can handle customer inquiries, providing instant responses and reducing the workload on human customer service representatives. These systems can also learn from interactions to improve over time.
Process automation and optimization
AI can automate routine tasks and workflows in various enterprise functions like HR, finance, and operations. This not only speeds up processes but also reduces errors, leading to more efficient operations.
Go deeper
Explore over 60 enterprise use cases for generative AI in Deloitte’s interactive Generative AI Dossier.
Leading products integrating generative AI to enhance workplace productivity.
-
Figma is a popular design tool used by enterprise product teams to build digital products and brainstorm. Figma is using generative AI for enhanced visual search, generate designs from text prompts, and more. Learn more here.
-
Canva uses text to image generative capabilities to allow generate images, editing videos, and virtual avatars. Learn more here.
-
Zoom’s AI Companion streamlines work communication by composing email and chat responses, summarizing meetings and chats, and providing actionable summaries with next steps. Learn more here.
-
Microsoft is embedding generative AI in all its products to empower their customers be more productive in Outlook, PowerPoint, search and more. Learn more here.
Go deeper
Explore more enterprise and consumer generative AI use cases with Sequoia Capital’s generative AI market map.
How does generative AI work?
-
It learns from massive amounts of data.
Generative AI starts its journey by learning from a massive library of information. This library includes books, articles, images, videos, and more. It's like a student going through an extensive course of study, absorbing knowledge on a wide array of topics.
-
It looks for patterns as it learns.
As it learns, the model begins to understand how things are related. It uses probabilistic and statistical principles to notice patterns, like how sentences are structured or what makes an image appealing. This stage is akin to the artist practicing and understanding different styles and techniques.
-
It generates new content and adapts to feedback.
After learning and understanding, the model can create new content. It can also adapt to feedback. If you tell it to change a part of what it created, it can do so, learning from your preferences to make something closer to what you want.
Learn more about how generative AI works
If you want to learn about foundation models…
Foundation models are models that are trained on a broad set of unlabeled data that can be used for different tasks. OpenAI, Google, and other companies have all built foundation models. Read this primer from IBM or watch their 8 minute video explainer.
If you’re want to learn about Large Language Models (LLMs)…
Large Language Models power many enterprise generative AI solutions. Watch this video on how large language models work.
If you want to understand the cloud providers who power generative AI products…
Building generative AI products requires more than having a model. Learn about cloud service providers for generative AI in this short overview.
If you want to get really technical on building LLM products…
Microsoft’s offers a comprehensive guide for launching Generative AI products.
More generative AI resources for executives and leaders
Flex your learning muscles and dive into these bite size resources to learn more about generative AI for enterprise.
Explore Gartner’s FAQ for Generative AI.
Listen to HBR’s podcast on how Generative AI changes strategy.
Listen to the Accenture podcast on what to consider when implementing generative AI.
See practical business use cases for generative AI in this Gartner video.
Learn Responsible AI practices for generative AI solutions.
Understand the biases and limitations of generative AI.
Interested in learning more?
Meet our AI chatbot for business leaders and executives
Ask questions, learn AI vocabulary, and demystify generative AI with our chatbot.
Designed to help leaders at all levels of an organization understand and experiment with generative AI.