Chasing Profit in the Age of AI

Profit in The Age of ai

Profit in The Age of AI? How entrepreneurs, coders, and creators are cashing in on the machine revolution reshaping work and wealth. In a downtown Manhattan loft with glass walls and espresso machines that hiss like serpents, a 24-year-old founder in Allbirds sneakers leans back in his ergonomic chair. “It’s not just about building the model,” he says, “it’s about knowing how to sell the magic.” The magic, of course, is artificial intelligence.

The gold rush is on.

AI, once the province of graduate students with coffee-stained hoodies, has become Wall Street’s darling and Silicon Valley’s newest gospel. It’s no longer just about research papers and obscure algorithms. Now, it’s about product. Monetization. Building something people will pay for or better, building something that replaces people altogether.

Venture capital has responded accordingly. A single tweet announcing an “AI productivity tool” can still spark a feeding frenzy. The formula is almost too simple. Take an everyday human activity writing, coding, designing logos bolt on a large language model, wrap it in slick UX, and charge a subscription. Voila: startup.

But the real money isn’t just in making tools. It’s in automation quiet, pervasive, ruthless. Across industries, AI is slipping into workflows like a ghost in the machine. In legal firms, clerks are being replaced by language models that parse contracts at hyperspeed. In media, headlines are now often penned by neural nets. In customer service, the human voice is quickly vanishing behind a synthetic mask that never sleeps and never unionizes.

There’s a certain irony here. The same technologists who warn of AI’s existential risk are often the ones selling its capabilities at scale. One founder described his AI startup as “the last job you’ll ever need” he meant it as a flex.

Still, the field has its stratifications. The elite few those building foundation models raise billions and absorb electricity by the megawatt. Then there are the app layer opportunists, the prompt whisperers and micro-SaaS dreamers who live on Twitter and launch on Product Hunt. They flip GPT wrappers like real estate.

For many, making money with AI today means not inventing but remixing using existing APIs and models, building thin layers of interface and branding on top. It’s the age of the “AI co-founder,” a term that now signals not a person but a bot.

Yet the chaos is fertile. Content creators automate production with uncanny efficiency. Niche consultants use AI to draft client reports in minutes. TikTokers push “passive income with ChatGPT” to millions of viewers. Courses and e-books proliferate, promising to turn anyone into an “AI entrepreneur” for $47.

Is it sustainable? Maybe not. Most AI tools are brittle, easily broken by edge cases. Costs rise fast, especially when scale demands compute. But this is a boom, and booms don’t care about sustainability. They care about momentum.

Behind it all is a familiar American story: of opportunity, of hustle, of making a quick dollar before the wave crashes. The machine is here. It doesn’t sleep, it doesn’t eat, and if you play your cards right it might just pay your rent.

For now.

 

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Paperback published on:  July 22, 2024

Paperback ISBN:  9781501522543

Front matter: 20

Main content:  550

Price per unit: £150

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Frontmatter 

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Preface

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xvii
Chapter 1: The Role of AI in Digital Marketing
Chapter 2: Understanding Artificial Intelligence 39
Chapter 3: Harnessing Data and Analytics in AI Digital Marketing 53
Chapter 4: Machine Learning and Deep Learning Foundation 67
Chapter 5: Natural Language Processing in Digital Marketing 77
Chapter 6: Personalization and Customer Segmentation with AI 85
Chapter 7: Predictive Analytics for Targeted Marketing 97
Chapter 8: Behavioral Analysis and Customer Profiling 105
Chapter 9: Content Creation with Artificial Intelligence 119
Chapter 10: Emotional Search Engine 127
Chapter 11: AI in Search Engines 147
Chapter 12: Enhancing Search Engine Optimization 169
Chapter 13: Social Media Listening and Sentiment Analysis 231
Chapter 14: Chatbots and Conversational AI 249
Chapter 15: Influencer Marketing in the Age of AI 261
Chapter 16: The Latest AI Trends in Digital Marketing 279
Chapter 17: Leveraging AI for Email Marketing Campaigns 291
Chapter 18: Marketing Automation and Workflow Optimization 305
Chapter 19: A/B Testing and Optimization with AI 321
Chapter 20: AI in Multichannel and Omnichannel Marketing 333
Chapter 21: Programmatic Advertising and Real-Time Bidding 345
Chapter 22: Creative Ad Design with AI 361
Chapter 23: Ad Campaign Optimization with Machine Learning 379
Chapter 24: AI-Powered Customer Service and Support 397
Chapter 25: Churn Prediction and Customer Retention Strategies 415
Chapter 26: Cross-Selling and Upselling with AI 419
Chapter 27: Privacy and Data Protection in AI Marketing 429
Chapter 28: Ethical AI Practices and Bias Mitigation 437
Chapter 29: Key Performance Indicators for AI Marketing 443
Chapter 30: ROI and Cost-Benefit Analysis 451
Bibliography 515
Appendix A 521
Appendix B 523
Appendix C 525
Glossary 527
About the Author 541
Index 543

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