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Digital Marketing · PDF · 220 pages

AI for Google Ads at a scale manual work cannot reach

Thirty-eight chapters on the recurring work that decides account performance — search terms, negatives, ad copy at volume, audits and scripts.

  • Classify four thousand search terms consistently in minutes, instead of accurately for three hundred and then rubber-stamping.
  • Generate RSA variants that pass a mechanical character-count check before upload, not after 40% get rejected.
  • Build negative keyword lists with an architecture, so a new negative never quietly kills your best-converting query.
  • Write, review and deploy Google Ads Scripts through a protocol designed to fail safely on a live account.
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Front cover of AI for Google Ads 2026, a 220-page PDF
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Who this is for

Buy it if

  • You run real budgets and have had to explain a cost-per-lead increase to someone who pays you.
  • Search-term mining is the job you know matters most and skip most often because it is tedious.
  • You manage more than one account and the reporting month is the part that hurts.
  • You want the scripts as well as the prompts — ten production scripts, indexed in Appendix B.

Do not buy it if

  • You have never run a Google Ads account. The book assumes you know what a search terms report is and does not stop to explain it.
  • You want AI to run the account for you. Every workflow here has a human validation step, and the book argues that judgement about money is the thing not to automate.
  • You are hoping for a way around Google policy. There is nothing like that here, and Chapter 10 is about staying inside the rules rather than outside them.
  • You only spend a few hundred a month. The workflows are built for a scale where consistency beats attention, and below that scale attention still wins.

After reading it

What you will be able to do

What is inside

Pages
220
Chapters
38
Parts
8
Prompts
120
Appendices
2
PART ONE · THE OPERATING MODEL5
  1. 1

    What AI Actually Changes in a Google Ads Account

  2. 2

    Three Layers: Assistant, Pipeline, Agent

  3. 3

    Picking Your Model, and What Each Is Actually Good At

  4. 4

    The Account Context Pack

  5. 5

    Data Hygiene: What Goes In, What Never Does

PART TWO · AD COPY AT SCALE8
  1. 6

    The 2026 Responsive Search Ad

  2. 7

    Why AI Writes Bad Ad Copy, and the Six Fixes

  3. 8

    The RSA Generation System

  4. 9

    The Validation Layer

  5. 10

    Pinning, Brand Safety and Compliance Copy

  6. 11

    Variant Systems: Testing Copy Without Breaking the Account

  7. 12

    Localisation and Multi-Market Copy

  8. 13

    Performance Max Assets, Text Guidelines and AI Max

PART THREE · SEARCHTERM SAND NEGATIVEKEYWORDS6
  1. 14

    The Search Terms Report Is the Most Valuable Asset in the Account

  2. 15

    Building the Query Taxonomy

  3. 16

    The Classification Pipeline

  4. 17

    Negative Keywords: Extraction, Match Types and List Architecture

  5. 18

    Mining Queries for What to Build Next

  6. 19

    Query Data in PMax, Shopping and AI Max

PART FOUR · STRUCTURE, KEYWORDS AND THE AUDIT5
  1. 20

    Keyword Research Without the Keyword Dump

  2. 21

    The Account Audit Pipeline

  3. 22

    Designing Account Structure That Survives Automation

  4. 23

    Match Types, Bidding and Budget Logic

  5. 24

    Landing Pages and Message Match

PART FIVE · SCRIPTS AND AUTOMATION6
  1. 25

    Scripts: The Honest Primer

  2. 26

    Writing Scripts With AI The Prompt System

  3. 27

    GAQL and the Reporting Layer

  4. 28

    The Safe Deployment Protocol

  5. 29

    The Monitoring Library

  6. 30

    Sheets, Apps Script and the Dashboard Layer

PART SIX · ANALYSIS AND DIAGNOSTICS5
  1. 31

    Diagnosing Performance Changes

  2. 32

    Reporting That Clients Actually Read

  3. 33

    Competitor and Market Analysis

  4. 34

    Lead Quality and Conversion Integrity

  5. 35

    Forecasting and Budget Planning

PART SEVEN · RUNNING THE SYSTEM3
  1. 36

    The Operating Cadence

  2. 37

    Training a Team and Keeping Quality High

  3. 38

    What to Automate Next, and What Never To

PART EIGHT · THE PROMPT LIBRARY2
  1. A

    The 120Prompt Library

  2. B

    The Script Library Index

Straight from the book

Two prompts, printed exactly as they appear inside

G-008 · Vertical primer before a pitchAI for Google Ads 2026
I am pitching a [VERTICAL] business in [MARKET]. Brief me on: how
customers in this vertical actually search, the buying cycle, typical
seasonality, the regulatory constraints on advertising, the claims that
are standard and the claims that are risky, and the three things a
paid search specialist usually gets wrong here. Flag anything you are
inferring rather than confident about.

The last sentence is the one that makes it safe to use. Without it you get a confident brief on an industry the model has half-guessed.

G-012 · Handover documentAI for Google Ads 2026
Write a handover document for this account. Cover: business model and
how a lead becomes revenue, account structure and the logic behind it,
deliberate decisions that look like mistakes and why they are not, live
tests, scheduled scripts and what they do, client communication
preferences, and known risks. Flag anything I have not given you that
the next manager will need.

CONTEXT PACK + DECISION LOG + STRUCTURE: [paste]

Written for the account you are handing over, and quietly the best audit of your own work — "decisions that look like mistakes and why they are not" is the line that finds the ones that actually were.

Sample pages

Three unedited pages from the book.

220

pages in total

38 chapters, all of it written like the three pages beside this one.

Get instant access

The prompt library

120 numbered prompts — G-001 to G-120

Format and delivery

Format
PDF
Pages
220
File size
3.2 MB
Text
Searchable and selectable, not scanned images
Reads on
Phone, tablet, laptop, e-reader — anything that opens a PDF
Printing
Unrestricted
DRM
None. The file is not locked to a device or an account
Delivery
Download link immediately after payment
Access
Permanent — the file is yours once downloaded
Edition
2026, written against the platform in Q3 2026
Structure
38 chapters across 8 parts, then Appendix A (120 prompts) and Appendix B (10 scripts)

Why $24.99

Five dollars more than the rest of the catalogue, for the largest book in it and the only one that ships working code. Two hundred and twenty pages, 38 chapters, 120 numbered prompts and ten production scripts, aimed at someone who spends money in the platform every day. The comparison that makes sense is not against the other guides but against an hour of the work it replaces: a single search-term classification run over four thousand queries is an afternoon by hand, and the book turns it into a pipeline you run monthly. It promises no performance improvement, because no book can honestly promise one.

One payment, no subscription, and the file is yours to keep. The full delivery spec is above, and the refund policy says exactly when the money comes back.

Refunds

Refunds are handled by Payhip, where the payment is taken. Digital downloads are delivered instantly and cannot be returned, so completing checkout waives the statutory 14-day right of withdrawal. Refunds are still given for a file that will not open, a duplicate charge, the wrong product, or a product that materially differs from its description here — within 14 days, by email.

This wording matches the full refund policy exactly. If the two ever disagree, the policy page is the one that governs — and the difference is what causes chargebacks, so they are kept identical.

Before you buy

Questions about this book

Will any of this get my account suspended, or breach Google policy?
No, and it is worth being precise about why. Google Ads Scripts are a first-party feature that Google builds, documents and supports — automating with them is intended use, not a loophole. Using a language model to draft ad copy, classify your own search-term export or summarise your own performance data happens entirely outside Google's systems and is not a policy question at all. What genuinely does get accounts suspended is the content of ads: prohibited claims, misrepresentation, trademark misuse. Chapter 10 covers pinning, brand safety and compliance copy for exactly that reason, and the validation layer in Chapter 9 exists partly to stop a model inventing a claim you would not have made.
Why is this $24.99 when the other guides are $19.99?
It is the largest and most specialised book here: 220 pages, 38 chapters, a 120-prompt library numbered G-001 to G-120, and ten production scripts indexed in their own appendix. The scripts are the difference — they are working code you deploy, not templates you fill in. It is also the only book aimed at people spending money daily, where a single avoided mistake covers the five dollars several times over.
Does it cover Performance Max and AI Max, or only search?
Both. Chapter 13 covers PMax assets, text guidelines and AI Max, and Chapter 19 covers query data in PMax, Shopping and AI Max — which is the part most PMax coverage skips because the data is awkward to get at.
I do not write code. Can I use the scripts chapters?
Chapter 25 is called "Scripts: The Honest Primer" and is written for that. The premise of Part Five is that you direct the writing rather than do it, and the safe deployment protocol in Chapter 28 assumes you cannot read every line — which is exactly why the protocol exists. Appendix B indexes all ten scripts so you can find one without reading the part.
Which model does it assume I am using?
None in particular. It is model-agnostic across Claude, ChatGPT and Gemini, and Chapter 3 is specifically about picking one per task and what each is genuinely good at. The prompts carry no product-specific syntax.
How much of the book is prompts versus method?
Thirty-eight chapters of method and two appendices of assets. The library is substantial but it is the back of the book, not the point of it — the chapters on why AI writes bad ad copy, on validation, and on diagnosing performance changes are where the length goes.
Is there anything about attribution, GA4 or the measurement side?
Partly. Chapter 34 covers lead quality and conversion integrity, and Chapter 31 is about diagnosing performance changes, which necessarily involves the data. There is no dedicated GA4 or attribution-modelling coverage — this is a book about operating the ads account.
How current is it, given how fast the platform moves?
It was written against the platform as it stood in the third quarter of 2026, including asset-level RSA reporting, PMax asset groups and the AI Max layer. The book states that character limits, report names and settings will move, and every prompt and script is written to survive that — but it tells you to verify specifications against the Google Ads Help Centre rather than trusting the page.

Read next

Thirty-eight chapters on the recurring work that decides account performance — search terms, negatives, ad copy at volume, audits and scripts.

Get instant access — $24.99$24.99 · 220-page PDF · instant download