Most artificial intelligence (AI) guidance is written for the people who build systems. Far less is written for the people who approve them. Thinking With AI is an illustrated companion that presents the Open Alliance for Cloud Adoption (OACA) position on responsible AI adoption in a format intended for shared reading, discussion, and decision-making among senior leaders.
The storybook covers nineteen short chapters, each one page, organized around the decisions leaders actually face:
- Framing the problem — the AI landscape, a decision maker’s playbook, starting with better questions, and testing claims before proceeding.
- Choosing and measuring — selecting winnable use cases, measuring return across investment, employee, and future horizons, and aligning strategy with structure and capability.
- Operating responsibly — continuous evaluation and education, safe piloting, human oversight proportional to risk, data foundations, guardrails, and build-buy-partner decisions.
- Sustaining it — preparing for failure, scaling only what can be operated and trusted, worked examples, a pre-approval checklist, and the leadership principles that hold over time.
Two sections are designed to be used rather than read. The Responsible AI Leadership Checklist is a one-page conversation guide for senior leaders before scaling AI, organized into strategic fit, operational readiness, human impact, and trust and compliance. The Executive Takeaways page distills the material into six principles, beginning with starting from questions rather than hype and measuring value across more than cost savings.
The storybook is a companion to the OACA AI Guidance white paper, which develops the underlying “Return on X” framework and the four macro-level areas of consideration in full. It also builds on our earlier AI Responsibly position paper from 2023.
A note on how this document was produced
In alignment with responsible AI principles, the format and illustrations in this storybook were generated with AI assistance, using OACA’s published white papers on AI adoption as the source material. The concepts, recommendations, and themes are drawn from those referenced source documents and adapted for educational and illustrative purposes. The document is offered as a companion to the underlying papers, not as a replacement for them.
This document is intended for educational and informational purposes. It does not constitute legal, regulatory, privacy, security, compliance, risk, or professional advice.
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