AI in Business for Dummies.

Format:

Book

Author/Creator:

Allan, Jeffrey.

Language:

English

Subjects (All):

Artificial intelligence--Business applications.

Artificial intelligence.

Business intelligence.

Business.

Industries.

Electronic books.

Physical Description:

1 online resource (338 pages)

Edition:

1st ed.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2026.

Summary:

Create an AI strategy that best fits your business You've heard about how artificial intelligence will revolutionize business, but maybe you're not sure how it will revolutionize your business.

Contents:

Intro

Title Page

Copyright Page

Table of Contents

Introduction

About This Book

Foolish Assumptions

Icons Used in This Book

Beyond the Book

Where to Go from Here

Part 1 Getting Cozy with AI in Business

Chapter 1 Why AI Matters in Your Business

Defining AI in Simple Terms

AI's emergence and relevance

AI's historical context

Why AI is crucial for businesses today

Misconceptions about AI in Business

Myth: AI will replace all jobs

Myth: AI is too expensive for small businesses

Myth: AI is only for tech companies

Introducing Generative AI in a Practical Business Context

Why generative AI is different

Everyday business applications of generative AI

How generative AI complements other types of AI

Small and Midsize Businesses Successfully Using AI

Examples of AI in retail, manufacturing, and services

Retail

Manufacturing

Services

Lessons learned from successful AI implementations

Have a clear goal

Begin small and scale gradually

Engage teams and manage change

Use external expertise and off-the-shelf tools

Customize AI to fit your business

Watch costs and plan integration thoughtfully

Keep humans in control

Common challenges and overcoming them

Immediate Benefits and Competitive Advantages of AI

Cost savings and efficiency gains

Enhanced customer experiences

New revenue opportunities

How AI Can Transform Your Business Operations

Streamlining operations and reducing errors

Enhancing decision-making and strategy

Improving employee productivity and satisfaction

Chapter 2 Grasping AI Essentials

Defining Generative AI Clearly and Simply

How generative AI creates new content

Key differences from traditional AI

Simple analogies to explain generative AI

Generative AI as an autocomplete tool.

Generative AI as a songwriter

Generative AI as a language learner

Essential AI Terms Demystified

Algorithms, models, and training data

Neural networks and deep learning

Overfitting, underfitting, and bias

Supervised, Unsupervised, Reinforcement Learning, and More

How each type works and when to use them

Supervised learning

Unsupervised learning

Reinforcement learning

Real-world examples of each AI type

Choosing the right AI type for your business needs

The Basic Principles of Generative AI

The role of large language models (LLMs)

Training and fine-tuning generative AI models

Understanding prompts and outputs

Data: The Fuel Behind AI

Why data is critical for AI success

Types of data: Structured, unstructured, and semi-structured

Data collection and preparation best practices

Importance of Data Quality and Quantity

Ensuring data accuracy and relevance

Balancing data quantity with quality

Common data quality pitfalls and how to avoid them

Data Privacy and Security Concerns

Protecting sensitive business and customer data

Compliance with data protection regulations

Best practices for secure data handling in AI projects

Chapter 3 Picking the Best AI Tools

Identifying Business Problems AI Can Solve

Recognizing everyday tasks AI can handle

Checking whether your team is ready for AI

Focusing on high-impact areas first

Criteria for Selecting AI Tools

Ease of use for non-tech teams

Ability to grow with your business

Cost and value for the money

Evaluating Generative AI Tools

Comparing user-friendly platforms

Weighing free versus paid options

Learning from other users' experiences

Popular AI Platforms and Their Features

Tools built into software you know.

Simple apps for specific tasks

Solutions tailored for your industry

Deciding When to Build versus Buy AI Tools

Benefits of ready-made tools

When to consider other options

Picking the best fit for your needs

Tips for Piloting and Testing AI Tools

Starting small with a test run

Measuring results and getting feedback

Rolling out to more areas

Matching Tools to Business Needs

Automating customer service in a small business

Boosting marketing in a midsize company

Streamlining supply chains in a large enterprise

Part 2 Putting AI to Work in Your Business

Chapter 4 Automating Daily Business Tasks with AI

Automating Email Responses and Follow-Ups

Email-related AI tools

Preparing AI to handle your emails

Generating reports and summaries

Useful tools and prompts

Visual reports

Creating Personalized Customer Communications

Preparing AI to write personal messages

Looking at Real-World Applications

Personalizing sales emails with AI

Speeding up customer support with AI

Simplifying financial reports with AI

Generating Social Media Content

Exploring AI tools for social media

Creating a content calendar with AI

Measuring engagement and refining strategies

Automating Tasks in Marketing, HR, and Accounting

Marketing: Automating ad copy and campaign analysis

HR: Streamlining recruitment and onboarding

Accounting: Automating invoice processing and forecasting

Tools and Technologies for Automation

Robotic process automation tools

AI-powered workflow automation platforms

Integrating AI with existing business software

Best Practices for Implementing Automation

Starting small and scaling gradually

Ensuring human oversight and intervention

Training employees to work alongside AI

Measuring the Impact of Automation on Productivity.

Key metrics to evaluating automation success

Calculating time and cost savings

Continuous improvement and optimization

Chapter 5 Winning Customers and Growing Sales with AI

Applying Generative AI to Personalized Marketing

Creating personalized email campaigns

Generating tailored product recommendations

A/B testing with AI-generated content

Customer Segmentation and Targeting with AI

Using AI to identify customer segments

Predicting customer behavior and preferences

Dynamic targeting based on real-time data

Predictive Analytics for Sales Forecasting

How predictive analytics works in sales

Tools for sales forecasting

Improving accuracy with AI-driven insights

Customer Support with Chatbots and Virtual Assistants

Deploying conversational AI for customer service

Best practices for chatbot implementation

Integrating chatbots with human support

Testing and measuring performance

Training your chatbot with real language

Maintaining brand voice and personality

Ongoing improvement and team readiness

Measuring customer satisfaction and resolution rates

AI-Driven Content Creation for Sales and Marketing

Generating blog posts, whitepapers, and case studies

Creating video scripts and social media content

Ensuring brand consistency with AI tools

Case Scenarios: Improving Customer Engagement with AI

Retailer using AI for personalized promotions

Service provider enhancing support with chatbots

Manufacturer optimizing sales with predictive analytics

Chapter 6 Sparking Innovation through Generative AI

Generating Ideas and Solutions Using Generative AI

Brainstorming with AI

Using AI to solve complex business problems

Encouraging team collaboration with AI

Basics of Effective Prompt Engineering

Prompt engineering explained.

Crafting prompts for better AI output

Be clear and specific

Provide context

Break down complex tasks

Use examples

Set boundaries

Experiment and iterate

Ask for alternatives

Common mistakes and how to avoid them

Being too vague

Overloading the prompt

Ignoring context

Not reviewing or editing

Asking close-ended questions

Expecting AI to know your business like you do

Not saving good prompts

Real-Life Examples of Product Ideation and Business Innovation

AI-generated product concepts

Innovating business models with AI

Enhancing R&amp

D processes

Using AI for Design and Prototyping

AI tools for design automation

Rapid prototyping with generative design

Testing and iterating designs with AI

AI in Problem-Solving and Decision Support

AI as a decision-making assistant

Scenario planning and risk assessment

Balancing AI insights with human judgment

Encouraging Creativity and Innovation with AI Tools

Fostering a culture of innovation

Training teams to use AI creatively

Measuring the impact of AI on innovation

Part 3 Strategically Integrating AI into Your Business

Chapter 7 Making Smarter Decisions Using AI

Informing Strategic Choices with Generative AI Insights

Using AI for market analysis and trend forecasting

Generating strategic options with AI

Evaluating risks and opportunities

Simplifying Predictive Analytics Using Generative AI

Enhancing predictive models with generative AI

Tools for simplified predictive analytics

Interpreting AI-generated predictions

The importance of explainable AI

Combining predictions with human judgment

Practical Decision-Support Examples

AI in financial planning

Optimizing inventory with AI

Enhancing HR decisions with AI

Integrating AI into Decision-Making Processes.

Embedding AI in business workflows.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-394-37736-3

9781394377367

OCLC:

1564119763