Generative AI Business Books

Introduction to LLMs for Business Leaders

A leader's guide to Generative AI: how it works, opportunities, risks, use cases, and strategies.

FINALIST: 2023 HARVEY CHUTE AWARDS recognizing emerging talent and outstanding works in Business and Enterprise Non-Fiction.

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Generative AI Transformation Blueprint

This handbook offers an accessible overview of AI-enabled business transformation that can be read in under two hours.

SCENARIO-BASED LEARNING

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Responsible AI
in the Age of Generative Models

Governance, Ethics and Risk Management in the Age of Generative Models.

A RIGHTS-BASED

APPROACH

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Generative AI for Business Leaders: Book Collection

BEST VALUE

Business leaders must understand how to effectively leverage Generative AI within their companies in order to remain competitive. This book collection offers a fresh, timely viewpoint on this critical topic. Readers will gain foundational knowledge about AI and Generative algorithms while exploring both the potential benefits, risks and ethics involved. Guidance is provided on enhancing an organization's offerings, operating model and strategic direction while mitigating biases and negative consequences.

The book collection lays out a comprehensive approach for businesses to successfully adopt and integrate Generative AI technologies. Common errors and challenges that companies face in this relatively new domain are highlighted, along with proven tactics to overcome them and achieve strong results.

A comprehensive playbook to unlock the commercial potential of generative AI for managers, directors, executives, governance specialists, and any professionals interested in the intersection of business and emerging technologies.

Responsible AI in the Age of Generative Models: AI Governance, Ethics and Risk Management

A comprehensive guide to navigating the complex landscape of ethical AI development and deployment. As Generative AI systems become increasingly powerful and ubiquitous, it is crucial to develop governance frameworks that mitigate potential risks while harnessing the technology's transformative potential. This book presents a rights-based approach, grounded in established human rights frameworks, to align AI systems with societal values and expectations.

Divided into ten parts, the book covers a wide range of topics essential for responsible AI governance:

Maps generative AI risks to specific human rights.
Presents a framework for institutionalizing rights-respecting AI practices throughout the development lifecycle.
Delves into responsible data governance practices.
Examines participatory approaches to data stewardship.
Explores the roles and responsibilities of different organizational functions in operationalizing responsible AI, emphasizing the need for cross-functional collaboration.
Focuses on transparency and algorithmic auditing.
Provides guidance on implementing effective multi-layered governance across the AI system lifecycle.
Introduces maturity models for assessing an organization's responsible AI capabilities.
Features an in-depth case study of Anthropic's innovative Constitutional AI approach.
Analyzes emerging regulatory frameworks such as the EU AI Act and discusses the implications for businesses operating in multiple jurisdictions.

"Responsible AI in the Age of Generative Models" equips readers with the knowledge, tools, and strategies needed to unlock the transformative potential of generative models while safeguarding human rights and promoting social justice. It is an essential resource for business leaders, policymakers, researchers, and anyone concerned about the future of AI governance.

By embracing responsible AI as an imperative, we can work together to build a world where AI empowers and uplifts us all. This book is an invitation to engage in that critical conversation and take action towards a more equitable future.

Generative AI Transformation Blueprint

This practical and concise guide provides senior decision-makers with a clear, accessible roadmap for harnessing the power of generative AI, enhancing innovation, and boosting business outcomes.

Drawing on insights from AI-enabled business transformations in diverse sectors, it presents a validated strategic approach. This blueprint not only outlines best practices but also showcases pioneering use cases, integrating them into a cohesive framework for practical implementation. This scenario-based approach helps leaders understand where and how to apply the practices outlined.

Spanning across areas from strategic alignment and talent development to ethical governance and sustaining a competitive edge amid relentless underlying progress, it delivers clarity for charting an optimal Generative AI roadmap.

This book is designed for busy executives and can be read in less than two hours. For a more in-depth exploration of Generative AI for business, check out our book "Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype."

Who this Book is For

The core audience comprises senior executives like CEOs, Transformation advisors, strategic planners, technology heads, product leaders or functional unit heads keen on harnessing generative AI for a competitive edge but needing authoritative counsel consolidating recent lessons into a crisp actionable package to aid planning.

Key Topics Covered

Understanding Generative AI: What it is, key capabilities and applications, strengths and limitations.
Strategic Alignment: Mapping generative AI to business goals, prioritizing high-impact use cases, managing risks.
Talent and Skills: Developing in-house capabilities through upskilling programs, attracting and retaining external AI talent.
Technology Integration: Assessing IT infrastructure readiness, optimizing make vs buy decisions for AI solutions.
Implementation and Scaling: Pilot testing for viability, expanding validated applications through metrics-driven scaling.
Risk Management and Ethics: Governing biases and reliability issues, safeguarding data privacy and security.
Organizational Change: Securing leadership commitment, preparing the workforce to adopt new AI-powered processes.
Continuous Improvement: Quantifying value through KPIs, optimizing models through responsive feedback loops.
Future-Proofing: Investing in R&D for sustained innovation, building agility to adapt to rapid AI progress.

Featuring use studies, business scenarios, practical frameworks, and research insights from top consultancies and AI leaders, this book delivers a visionary yet pragmatic roadmap for AI transformation. A must-read guide for any organization looking to leverage generative AI for competitive advantage.

Introduction to LLMs for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

Finalist for the 2023 HARVEY CHUTE Book Awards recognizing emerging talent and outstanding works in the genre of Business and Enterprise Non-Fiction.

In this comprehensive guide, business leaders will gain a nuanced understanding of large language models (LLMs) and generative AI. The book covers the rapid progress of LLMs, explains technical concepts in non-technical terms, provides business use cases, offers implementation strategies, explores impacts on the workforce, and discusses ethical considerations. Key topics include:

The Evolution of LLMs: From early statistical models to transformer architectures and foundation models.
How LLMS Understand Language: Demystifying key components like self-attention, embeddings, and deep linguistic modeling.
The Art of Inference: Exploring inference parameters for controlling and optimizing LLM outputs.
Appropriate Use Cases: A nuanced look at LLM strengths and limitations across applications like creative writing, conversational agents, search, and coding assistance.
Productivity Gains: Synthesizing the latest research on generative AI's impact on worker efficiency and satisfaction.
The Perils of Automation: Examining risks like automation blindness, deskilling, disrupted teamwork and more if LLMs are deployed without deliberate precautions.
The LLM Value Chain: Analyzing key components, players, trends and strategic considerations.
Computational Power: A deep dive into the staggering compute requirements behind state-of-the-art generative AI.
Open Source vs Big Tech: Exploring the high-stakes battle between open and proprietary approaches to AI development.
The Generative AI Project Lifecycle: A blueprint spanning use case definition, model selection, adaptation, integration and deployment.
Ethical Data Sourcing: Why the training data supply chain proves as crucial as model architecture for responsible development.
Evaluating LLMs: Surveying common benchmarks, their limitations, and holistic alternatives.
Efficient Fine-Tuning: Examining techniques like LoRA and PEFT that adapt LLMs for applications with minimal compute.
Human Feedback: How reinforcement learning incorporating human ratings and demonstrations steers models towards helpfulness.
Ensemble Models and Mixture-of-Experts: Parallels between collaborative intelligence in human teams and AI systems.
Areas of Research and Innovation: Retrieval augmentation, program-aided language models, action-based reasoning and more.
Ethical Deployment: Pragmatic steps for testing, monitoring, seeking feedback, auditing incentives and mitigating risks responsibly.

The book offers an impartial narrative aimed at informing readers for thoughtful adoption, maximizing real-world benefits while proactively addressing risks. With this guide, leaders gain integrated perspectives essential to setting sound strategies amidst generative AI's rapid evolution.

More Than a Book

By purchasing this book, you will also be granted free access to the AI Academy platform. There you can view free course modules, test your knowledge through quizzes, attend webinars, and engage in discussion with other readers. No credit card required.

AI Academy by Now Next Later AI

We are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically.

Featured by Amazon as #1 Hot New Release in Big Data Business.

AI Fundamentals for Business Leaders Book: Up to Date With Generative AI

Introducing "Artificial Intelligence Fundamentals for Business Leaders" - the perfect guide to help non-technical business leaders understand the power of AI. Completely up to date with the latest advancements in generative AI. Part of the Byte-sized Learning AI series by Now Next Later AI, these books break down complex concepts into easily digestible pieces, providing you with a solid foundation in the fundamentals of AI.

Featured by Amazon as #1 Hot New Release in information technology.

More Than a Book

By purchasing this book, you will also be granted access to the AI Academy platform. There you can test your knowledge through end-of-chapter quizzes and engage in discussion with other readers.

You will also receive 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion.

AI Academy by Now Next Later AI

We are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically.

Generative AI for Business Leaders: Book Collection

Geneerative AI for Business Leaders Book Collection

Perfect gifts for someone you love!

About the Author: Inês Almeida

We are the most trusted and effective learning platform dedicated to empowering you with the knowledge and skills you need to harness the power of AI safely and ethically.

Our comprehensive courses, designed by industry experts, get you up to speed fast: no padding, or detours, or thousands spent on outdated content. We give you exactly what you need to adopt AI in your business or to advance your career.

Pedagogic Design

SMART learning goals. Microcredential issued upon successful completion. Lesson quizzes validate understanding. Curriculum updated monthly.

Engaging & Effective Content Delivery

Caters to diverse learning styles. Lessons integrate video, audio, images, and AI avatars. Students receive a free copy of our best-selling book.

Instructor-Guided Business Application

Instructor-guided course assignment kick-starts your AI strategy. Option to apply to your business or industry.

Live Sessions and Ongoing Support

Live, instructor-led sessions weekly. Instructors regularly engage in the discussion forums, providing learning support. Up-to-date AI advancements, applications, and case studies

Long-Lasting Community

Network with other leaders via the course forum and discord site for engagement beyond the course timeline. Stay connected with the latest news and innovations.

No credit card required.

Navigating the Generative AI Landscape

Learn the latest AI technologies, strategies, and practical applications tailored to non-technical professionals.

Our instructor-graded assignments help you kick-start your AI business strategy, or alternatively, you can apply it to your favorite industry.

Navigating the Generative AI Landscape: words by Inês Almeida, spoken by Cy.

No credit card required.

Artificial Intelligence Fundamentals for Business Leaders Course

This self-paced course includes 50 key lessons for non-technical business leaders. It's based on I. Almeida's best-selling book, featured by Amazon as #1 Hot New Release in information technology.

Introduction to Artificial Intelligence [FREE]

Learning Objectives:

Demonstrated comprehension of AI's evolution, definition, applications, and comparison with human intelligence.

Lessons:
Innovate and Adapt, Faster!
AI and the Transformation of the Global Business Landscape
What is Artificial Intelligence?
Human Intelligence Versus Machine Intelligence
Current and Emerging Applications
Computational Power

All About Data

Learning Objectives:

Clear understanding of the significance of data, and strategies for data management.

Lessons:
Big Data
Data Science Versus Machine Learning
Harnessing Data for Machine Learning: Strategies and Challenges
Proprietary Data as a Competitive Advantage
Open Data and Data Sharing
The New Era of Generative AI: Understanding the Data Management Implications

Machine Learning for Business Leaders

Learning Objectives:

Familiarity with machine learning algorithms, and different learning types.

Lessons:
Why Business Leaders Must Understand Machine Learning
Expert Systems
Machine Learning
Supervised Learning
Unsupervised Learning
Self-Supervised Learning - Bridging the Gap
Reinforcement Learning
Reinforcement Learning from Human Feedback (RLHF): Enhancing AI Models with Human Input

Stepping-Stone Models and Concepts - Non-Technical Overview

Learning Objectives:

Demonstrated comprehension of parametric and non-parametric algorithms.

Lessons:
Parametric And Non-Parametric Algorithms
Linear Regression
Logistic Regression
Decision Trees
Ensemble Methods
K-Means Clustering
Key Steps of a Machine Learning Project

Deep Learning for Business Leaders

Learning Objectives:

Understanding of deep learning, its basics, and the structure and types of neural networks, and the key steps involved in a machine learning project.

Lessons:
Introduction to Deep Learning
Neurons
The Perceptron
Training a Neuron
Neural Networks
Basic Types of Neural Networks

Model Selection and Evaluation - Business Decision-Making

Learning Objectives:

Ability to select and evaluate machine learning models and utilize them for decision-making.

Lessons:
Model Selection
The Unreasonable Effectiveness of Quality Data
Model Evaluation
Outputs Versus Outcomes
Enhancing Decision-Making with Machine Learning

Generative AI For Business Leaders

Learning Objectives:

Detailed understanding of generative AI, its value chain, transformer models, diffusion models, and governance challenges.

Lessons:
Introduction to Generative AI
Transformer Models
Transformers: The Near Future
Generative Adversarial Networks
Diffusion Models
Foundation Models
The Generative AI Value Chain
Training GPT Assistants and the Art of Prompting
Prompt Strategies
Regulating and Governing Generative AI: A Case Study of the European Union

Assignment: AI Opportunities and Challenges for Your Business or Industry

Learning Objectives:

To analyze the opportunities and challenges posed by the integration of Generative AI technologies in your business operations, and to design an initial strategic response to these insights. You can work on a real or imagined business.

No credit card required.

Pedagogic Design is Teamwork

We build a curriculum focusing on learning goals, applying best practices and evolving them to find the best methods, activities, and tests to help students meet their goals.

In building a program focused on AI and data, we embed intelligence into everything we do. Our videos may feature AI avatars, but each lesson is carefully designed and curated by our team of expert humans. We work hard to make sure every part of your learning experience is just right for you. Our team is online guiding you at every step along your learning journey.

AI Academy's Pedagogic Design: words by Inês Almeida, spoken by Cy.

No credit card required.

Microcredentials

At the AI Academy, we align with the National Microcredentials Framework. This initiative is aimed at addressing the growing demand for shorter-form courses that enable rapid upskilling and lifelong learning.

We align with each principle in our commitment to a culture of continuous learning and growth, where every member is encouraged and supported to enhance their skills and knowledge, and seek advice from the best in our field.