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Neither hope nor denial are strategies for managing AI risk.
AI adoption is accelerating faster than any previous technological shift. The opportunities for creating competitive advantage are huge – but so are the risks of new, faster routes to reputational damage.
GuardrAIls bridges the gap between innovation and reputation management by providing actionable, non-negotiable guardrails for ethical AI together with a framework for managing the Seven Pillars of AI Reputational Risk. With incisive case studies from companies such as Air Canada, Coca-Cola and Google Photos, together with concrete decision frameworks, crisis playbooks and a pragmatic 90-day action plan, it enables leaders to adopt AI aggressively but responsibly, and turn potential crises into competitive advantage.
Discover how to put in place effective AI governance, not as a technical or legal exercise but as a critical marketing and brand-protection discipline, so that you can actively maintain brand authenticity and stakeholder trust as you chart the path into the future.
Craig McDonogh is an accomplished marketing executive and AI ethicist with more than 30 years of experience in global B2B software. He has led marketing teams and strategy at companies including ServiceNow, BMC and Perspectium, and more recently at AI-driven organizations such as Forma.ai and Imgix. He is an advisor on AI Ethics to the University of San Francisco Digital Marketing Program, and publishes a daily newsletter on responsible AI at ethicore.substack.com
Craig combines a technical understanding of how AI systems work with deep experience in the ethics of AI, advising on issues such as fairness, transparency, accountability, and sustainability. Recognized as both a SaaS marketing leader and trusted voice on AI responsibility, he helps organizations adopt AI in ways that build trust, minimize risk, and drive long-term value.
Introduction
The four non-negotiable guardrails of ethical AI
Part I: Understanding AI Reputation Risk
Chapter 1: Why AI Reputation Risk is Different
Chapter 2: Mapping Your AI Risk Landscape
Chapter 3: The Hidden Costs: IP Infringement and Carbon Footprint
Chapter 4: Protecting Vulnerable Populations
Part II: Operational Risk Management
Chapter 5: Establishing Governance That Works
Chapter 6: Content, Creativity, and Copyright
Chapter 7: Customer Interactions: Personalization to Service
Chapter 8: Marketing Operations and Advertising
Chapter 9: Bias, Fairness, and Testing
Part III: Crisis and Recovery
Chapter 10: Prevention and Early Warning
Chapter 11: Crisis Response Playbook
Chapter 12: Recovery and Rebuilding Trust
Part IV: AI Wagons Ho!
Chapter 13: When AI Isn’t the Answer
Chapter 14: The Future of AI Reputation
Chapter 15: Your 90-Day Action Plan
Appendices
Appendix A: AI Reputational Risk Self-Assessment
Appendix B: Essential Vendor Questions
Appendix C: Stakeholder Communication Templates
Appendix D: Key Resources
Appendix E: Industry-Specific Quick Reference