AI First.

.Picture this. You are sitting across from Sam Altman, the CEO of OpenAI. He tells you, calmly, that within five years his machines will do 95% of all marketing tasks. Instantly. For free. Almost perfectly. Your stomach drops. Your mind races. You feel a jolt — a mix of panic and electric excitement. That is the exact moment Adam Brotman and Andy Sack lived through. They call it the "holy-shit moment."

You may not have been in that room. But the wave they felt is already crashing into your business. And most leaders are freezing. They watch. They wait. They schedule another meeting about "AI strategy" for next quarter. That is the wrong move. The window is closing fast.

This microbook is built to shake you awake. It shows you why artificial intelligence is not just another tool. It is the steam engine of the mind. And it gives you a clear playbook to stop planning for tomorrow and start building with AI today — before your competitors do.

The Steam Engine of the Mind

Reid Hoffman, the co-founder of LinkedIn, recently sat with Vatican officials. His mission was bold. Democratize healthcare across the planet using one device — the smartphone. Powered by AI. That conversation captures the shift. Generative models are not faster typewriters. They are capability multipliers.

Hoffman calls AI a 10X amplifier for knowledge workers. Brotman and Sack go further. They name it the "steam engine of the mind." Just as steam freed muscles from physical labor in the 1800s, machine intelligence now frees your brain from repetitive cognitive work. Drafting, summarizing, researching, analyzing. All of it. Suddenly available, on demand, at near-zero cost.

This changes the game from human-versus-machine to human-plus-machine. Every leader needs two playbooks now. An offensive game, using AI to grab market share and launch new products. And a defensive game, anticipating what your sharpest competitor will do with the same tools. Standing still is the only losing move. The deer-in-headlights pose ends today.

The Jagged Frontier of Productivity

Bill Gates is hard to impress. He has seen every wave of computing since the 1970s. When he first tried ChatGPT, he compared the shock to the day he saw the Xerox Alto graphical interface — the moment that birthed Windows and the Mac. That is the scale of the disruption.

But productivity now means something new. It is not just speed. It is quality. A landmark study by Harvard Business School and the Boston Consulting Group put 758 consultants through real tasks with and without GPT-4. The result? Workers using AI finished 25% faster and delivered work judged 40% higher in quality. Both dials moved at once.

Here is the trap. AI is brilliant at some tasks and surprisingly bad at others. The researchers called this the "jagged technological frontier." It writes a stunning client memo, then botches simple arithmetic. So humans must stay in the loop. The winners adopt one of two styles. The centaur splits work cleanly — humans for judgment, machines for execution. The cyborg fuses with the tool, weaving prompts into every keystroke. Both beat the worker who refuses to touch the keyboard.

The Hyper-Fast Middle Era

Jaime Teevan, Microsoft's Chief Scientist, tested an early version of GPT-4 alone in her car. She started screaming. Not in fear. In recognition. She understood, instantly, that the world had just changed. Mustafa Suleyman, co-founder of DeepMind, now talks openly about "Artificial Competent Intelligence" — AI agents that will run entire social media personas, indistinguishable from humans.

We are in what the authors call the "middle era." A hyper-fast bridge between today's chatbots and full Artificial General Intelligence. Paul Roetzer, founder of the Marketing AI Institute, places AGI between 2028 and 2030. That is not science fiction. That is your next strategic planning cycle.

And yet a dangerous gap is forming. Surveys cited in the book suggest 90% of C-suite executives remain mere observers. They have heard of ChatGPT. They have not built with it. To close this proficiency gap, Brotman and Sack lay out concrete moves. Mandate AI education across all levels. Form an internal AI Council with cross-functional leaders. Write clear guardrails and responsible-use policies. Then launch short pilots — 30 to 60 days — to test real workflows. Education, governance, pilots. In that order. Skip any step and the rollout collapses.

The End of Traditional Brand Building

In 2016, an AI system called AlphaGo played the world champion of Go. On move 37, it placed a stone in a spot no human master would ever choose. Commentators thought it was a glitch. It was genius. AlphaGo won. That move proved machines can do real divergent creativity — not just remix the past.

That same capacity is now in your marketing department. Tools like Suno and Udio generate full original songs in seconds, complete with vocals tuned to your brand. The tedious work — SEO optimization, media planning, sentiment analysis, A/B testing — moves to autonomous agents working through the night. Your marketers stop being content creators. They become managers of AI systems.

And personalization reaches a new ceiling. Forget broad audience segments. Imagine living, interactive ads that generate themselves the moment a specific customer clicks. A video tailored to her city, her last purchase, her current mood. Static targeted media is dying. Real-time, individually generated content is being born.

Rewiring the Corporate Mindset

Technology does not transform a company. Culture does. Brotman and Sack fuse two classic frameworks here. Carol Dweck's growth mindset, which says abilities can be developed through effort. And Eric Ries's lean startup thinking, which says you build, measure, learn, repeat. Together they form the "AI-first" mindset.

Consider the young banking associate cited in the book. She was given a project expected to take a full week. Using ChatGPT to draft analyses, structure spreadsheets, and refine language, she finished in a day and a half. That is not a productivity story. That is a career-redefining story. And it only happens when leadership gives permission to experiment.

Matt Britton, CEO of consumer-insights firm Suzy, lived this principle. He did not delegate AI to his CTO. He sat down and coded the first version of the company's Churn Early Warning System himself. That signal — the CEO with his hands on the keyboard — silenced legal pushback and operational skepticism. The result was a 30% to 40% increase in sales efficiency. Lead by example. Or do not lead at all.

The Power of Showing Over Telling

Sal Khan runs Khan Academy, one of the largest free education platforms on Earth. When OpenAI gave him early access to GPT-4 under strict NDAs, Khan did not commission a study. He did not hire McKinsey. He gathered a small team and built a working prototype of an AI tutor called Khanmigo in just two weeks.

That speed mattered. When a technology is this disruptive, action beats analysis. Khan walks into all-hands meetings and uses AI live in front of staff. He summarizes HR survey results in seconds. He drafts grant proposals out loud. He shows his shortcuts, his prompts, even his mistakes. That vulnerability gives the entire organization cultural permission to try.

The numbers back the bet. Software teams using GitHub Copilot have seen output jump by as much as 300%. You do not need a polished policy first. You need a prototype on the screen. Show the magic. Skepticism evaporates faster than any memo could ever achieve. Telling persuades a few. Showing converts everyone.

Treating Intelligence Like Electricity

Moderna is the gold standard. The biotech firm behind the mRNA Covid vaccine appointed a VP of AI and started not with software, but with conversation. They conducted 270 internal interviews — what they called "listen before you think" sessions — to map exactly where employees were stuck. Only then did they build mChat, a secure internal version of ChatGPT that protected proprietary research data.

Then came the gamification. Moderna launched a company-wide prompt contest. Employees submitted their best uses of mChat across every function. The winners were compiled into an internal playbook titled "180 Things We Learned." Out of that contest emerged the natural super-users, who were organized into the GenAI Champions Team — a grassroots council spreading best practices department by department.

CEO Stéphane Bancel framed the philosophy with one line. He said calculating the ROI of AI is like calculating the ROI of electricity. You do not. You just plug in. Ethan Mollick, the Wharton professor, sharpens the mandate further. Stop renting chatbots from vendors. Build an internal generative AI R&D lab. Now. Treat machine intelligence as the foundational utility powering the entire enterprise.

Your Move, Today

The revolution will not wait for your committee. Stop chasing perfect ROI spreadsheets. Form the council. Write the guardrails. Open the lab. Demand daily use. The leaders who treat AI as the new electricity will compound advantages every quarter. Everyone else becomes the case study in what happened next.