Thinking in AI

Most companies say they use AI. Very few can say what they are becoming — or answer one question: if every AI tool were switched off tomorrow, would the business still run?

Thinking in AI: The Foundations gives every reader — executive, manager, employee or engineer — one shared set of ideas for adopting AI on purpose: the three adoption levels (AI First, AI Embedded, AI Native); the shutdown test that reveals which level you are really at; the difference between an agent (a thing you can count), an autonomy level (a degree you can set) and a multi-agent system (a system you can organize); the five-level autonomy scale; the four-layer model built on a deterministic core; the four work groups; the four-step roadmap and the four conditions no transformation survives without.

Every idea is shown, not lectured, on three fictional companies — Cedar Bank, Oakridge Manufacturing and Harbor Securities — with the same people and numbers that run through all six books.

After this book you will be able to:

• Classify any company, project or tool into one of three adoption levels — and explain, in one sentence, why
• Apply the shutdown test to a business unit and read the answer correctly
• Tell an AI agent from an autonomy level from a multi-agent system, and ask the right test question of each
• Place any piece of software on the five-level autonomy scale and say what the human does at that level
• Put any AI initiative into the four-layer model and name the one thing that must never change
• Explain the four-step roadmap and the four work groups, and why skipping a step is the most common cause of failure
• Check a transformation plan against the four mandatory conditions before money is spent

16 chapters, 16 figures, a self-test with answer keys in every chapter, a 60-term glossary and worksheets. Read it first; the other five books each take one seat in the company.

In this series: 1 The Foundations · 2 Thinking in AI for Leaders · 3 Thinking in AI for Managers · 4 Thinking in AI at Work · 5 Thinking in Agents and AI-Native Systems · 6 The AI-Native Casebook.