WHITEPAPER
Beyond the prompt:
A practical operating model for using AI in marketing.
AI adoption in marketing is an operating-model challenge.
The difficult part in my experience isn’t getting access to the tools, It’s deciding where an uncertain output is useful, where a defined outcome is safer, where experience still matters most and how those choices fit together inside real work.
This paper maps the journey from scattered experimentation to a practical operating model for AI in marketing.
48 pages • 7 chapters • Free PDF
CONTENTS
What's inside the paper
Two short primers, then seven chapters that build the operating model end to end.
48 pages • 7 chapters
Primer – Executive summary
Primer – How to use this paper
01 Beyond experimentation
02 Where AI adds value, and where it doesn’t
03 Selecting the right approach
04 Designing governed workflows
05 Moving from individual to team adoption
06 Measuring value and scaling responsibly
07 Beyond the prompt
WHO IT’S WRITTEN FOR
Written for the people accountable for the outcome
CMOs & marketing leaders setting the direction for AI and answerable for the results.
Marketing ops & RevOps turning tools and prompts into repeatable, governed workflows.
Teams in regulated sectors where accountability, quality and compliance aren’t optional.
ABOUT THE AUTHOR
Will Tisdall
Will Tisdall is a marketing and digital leader whose work focuses on turning emerging technology into practical, governed ways of working. He has experience applying AI, automation and data-led approaches within marketing environments, with particular attention to commercial value, quality, accountability and adoption in regulated organisations.
This whitepaper reflects his own views at the time of writing. This published content should not be taken as representing the views of any employer, client or organisation.
BEYOND THE PROMPT
Get the operating model your
AI activity has been missing.
48 pages. Seven chapters. A clear route from experimentation to governed, measurable practice.
PUBLICATION NOTE
This paper is provided for general information and does not constitute legal, regulatory, data protection, cyber-security or professional advice. Organisations should apply their own policies, risk appetite and assurance processes and seek specialist advice where appropriate. AI systems, product capabilities and official guidance may change after publication.