The Digital Marketing Podcast · Daniel Rowles and Ciaran Rogers

How to Drive AI Adoption - A Step-by-Step Case Study

·27 min·1 clip

Emma says the task force had four objectives and all four were achieved.

1. The Digital Marketing Podcast episode 'How to Drive AI Adoption - A Step-by-Step Case Study' follows Emma Tronson's AI adoption work at Aston University. 2. Daniel Rowles hosts the conversation, and Emma Tronson appears as Deputy Director of Marketing at Aston University, which matters because she led the task force described here. 3. The episode asks how Aston moved beyond 'pilot purgatory' and embedded AI into everyday work through a structured, step-by-step process. 4. Emma says a setback at work pushed her to focus on 'AI Jan,' attending webinars, experimenting, and learning AI tools for herself. 5. She says she pitched 'Mission AI Impossible' to the director of marketing in March 2025 and tied it to the Aston 2030 strategy. 6. Emma says the ask was under five grand plus time and commitment from a small group to join the AI task force. 7. She says the biggest problem was a 'Wild West' environment with no clear policy, guidance, or upskilling around AI. 8. Emma defines four task force objectives: build AI expertise, pilot real use cases, establish governance, and support digital transformation. 9. She says the team started small with a 'hub and spoke approach' and selected staff who could be supported properly. 10. She says recruitment emphasized personal benefit, used statistics about marketing being heavily affected by AI, and even opened with an avatar rather than another email. 11. Emma says she wanted a range of people from marketing, communications, and admissions, including colleagues who could challenge assumptions and check for bias. 12. She says the task force was split into six categories: data and analytics, general work support, copywriting, visual and creative, SEO and web, and social and community. 13. Emma says each member got guidance, example use cases, and tools to explore, including Jasper AI, Claude, and custom GPTs. 14. She says she asked members to book 'lab time' so experimentation would not disappear into normal workload. 15. Emma says the lab time could be webinars, experimentation, reading, meetings, or catch-ups with other task force members. 16. She says a working group every other week used round robins to share what had worked, what had not, and what people had learned. 17. Emma says the wider department launch happened in October after meetings in September to make sure the cohort felt confident. 18. She says current progress is limited by system integrations and uncertainty about which AI platform the university will partner with. 19. Listeners who manage marketing teams, AI rollout, or university change work will find practical structures here. 20. People wanting abstract AI predictions without operational detail may skip this one.

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