How to Drive AI Adoption - A Step-by-Step Case Study
Release Date: 02/18/2026
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info_outlineIn this episode of The Digital Marketing Podcast, Daniel Rowles is joined by Emma Tronson, Deputy Director of Marketing at Aston University, for a practical, honest and refreshingly structured look at how to move beyond AI experimentation and into real organisational adoption.
Many teams are stuck in what Daniel calls “pilot purgatory”. Everyone is testing tools. Everyone is experimenting. But very few organisations have truly embedded AI into day-to-day operations. Workloads have not reduced. If anything, they have increased.
This episode explores what it actually takes to embed AI into a complex organisation with multiple stakeholders, legacy systems, risk concerns and competing priorities
Emma shares her step-by-step journey of launching an AI task force, securing leadership buy-in, aligning with institutional strategy, and creating a structured framework for adoption that delivered tangible outcomes within a year.In This Episode:
From career setback to AI champion
Emma explains how missing out on a promotion led her to proactively position herself as indispensable by embracing AI learning
Mission AI Impossible
How she pitched a structured AI task force aligned to Aston University’s 2030 strategy and secured budget, time and executive support.
Why time matters more than money
Resource allocation and protected “lab time” proved more critical than financial investment.
The six focus areas model
Data and analytics, general work support, copywriting, visual and creative, SEO and web, and social and community. Each task force member owned one domain.
Start small and build confidence
Select staff were upskilled first before launching more widely across the department.
Align AI to real use cases
Experimentation was always tied to live marketing and admissions challenges rather than abstract testing.
Governance before scale
Clear internal guidance helped build confidence in responsible AI usage.
The system integration challenge
Legacy systems and risk aversion slowed deeper embedding, a common challenge across many organisations.
Cohort Two and scaling adoption
Expansion into wider teams with three new priority workstreams: personalisation, data, and custom builds.
Why AI will not replace marketing teams
Instead, it will reward those who actively upskill and adapt.
Key Takeaways:
AI adoption requires structure.
Align initiatives to business strategy from the outset.
Start with a focused pilot group, then scale.
Protected experimentation time is essential.
Bring sceptics into the process rather than excluding them.
System integration and governance are often the biggest blockers.
Innovation must be baked into everyday work, not treated as a side project.
📥 Access the show notes, tools, and links at: https://targetinternet.com/resources/how-to-drive-ai-adoption