The Digital Marketing Podcast

Episode Title: How to Drive AI Adoption – A Step-by-Step Case Study
Hosts: Daniel Rowles and Ciaran Rogers
Guest: Emma Tronson, Deputy Director of Marketing, Aston University
Date: February 18, 2026

EPISODE OVERVIEW

This episode dives into a detailed, practical roadmap for embedding AI into a complex organization, moving beyond the “pilot purgatory” stage to achieve real transformation. Daniel speaks with Emma Tronson, who offers a step-by-step account of leading AI adoption at Aston University—focusing on strategy alignment, stakeholder management, skill-building, and lessons learned along the way.

MAIN THEMES AND PURPOSE

How to move AI from experimentation to everyday embedded practice
Strategies for building and supporting an internal AI task force
Lessons in change management, governance, and sustainable digital transformation
Practical insights for marketing (and broader) teams to approach AI adoption

KEY DISCUSSION POINTS

1. Emma’s Motivation and Early Steps ([01:35])

Personal Drive: After a career setback, Emma decided to upskill, coining the term “AI Jan” for her month of deep AI immersion.

“Instead of doing Dry Jan, I’ll do AI Jan. I really just threw myself into everything I could do with learning AI...” – Emma Tronson (01:45)

2. Pitching the AI Task Force ([02:24])

Strategic Alignment: Emma pitched “Mission AI Impossible,” ensuring the project aligned with broader university strategy (Aston 2030).
Resource Ask: Rather than a large budget, Emma emphasized the need for committed staff time.

“The resource and time is key, particularly in this area.” – Emma Tronson (03:29)
Clear Objectives: She mapped out concrete deliverables, getting easy buy-in from leadership.

3. Objectives of the AI Task Force ([05:14])

Four clear goals:
1. Build AI expertise among select staff (via a hub-and-spoke model)
2. Pilot real use cases in specific domains (marketing, communications, student support)
3. Establish governance and internal guidance for AI use
4. Support the university’s wider digital transformation
“My ethos is always try and relate it to the work you’re doing, otherwise you’ll end up doing double the amount of work.” – Emma (06:16)

4. Recruiting and Structuring the Team ([07:17] – [10:34])

Selling the Benefits: Emma focused on personalized benefits for staff, using creative communication (including an AI-generated avatar) to spark interest.

“Don’t talk about how AI is going to help the company… Most people are working for themselves… they want to know how AI can support themselves.” – Emma (07:29)
Diversity and Reach: She sought a mix of skills and departments, including AI skeptics to challenge bias and reach hidden communities.

“I didn’t want a whole task force of yes people. I wanted people that were going to challenge our thoughts, that were going to check for bias…” – Emma (09:13)

5. Task Force Model: Six Areas of Focus ([10:34])

Aligned members to:
- Data & Analytics
- General Work Support
- Copywriting
- Visual & Creative
- SEO & Web
- Social & Community
Benefits: Provided direction, focus, and easier triage of support queries.

6. Guidance and Upskilling ([11:49])

Human Expertise First: Matched areas of focus to existing staff skillsets to minimize learning curve and boost confidence.

“If you have humans who can understand immediately what good looks like… you’ve solved half the battle there.” – Emma (12:19)
Toolkits and Support: Provided written guidance and a menu of suggested AI tools per area.

“I provided clear guidance… then I also gave them a list of AI tools to explore.” – Emma (12:58)

7. Motivation & “Lab Time” ([14:06])

Lab Time: Members scheduled regular, protected slots for AI learning and experimentation.
Working Groups: Biweekly meetings facilitated knowledge sharing and collective motivation.

“Sometimes you’re doing AI without realizing you’re doing AI, and when you’re forced to think of, oh, what was the latest thing that I have worked on, that helps you realize how far you’ve come.” – Emma (15:12)

8. Broader Roll-Out and Embedding ([16:02])

Staged Approach: After ~6 months of internal work, Emma launched a department-wide Q&A and introduced the task force to the organization.
Support Model: Task force members fielded queries and provided tailored help, with Emma facilitating connections and collaborations.

9. Results, Challenges, and Lessons Learned ([18:30])

Wins:
- Task force developed significant expertise
- Catalysed learning culture (e.g., “brunch and learns,” online sharing)
- Created inter-university collaboration
Setbacks:
- System Integration: Progress slowed by uncertainty over platform choices and lack of trust in digital services.
"System integrations has been a real challenge. I think there’s still such a mistrust and hesitation." – Emma (19:24)
- Much work focused on “safe” projects until IT gave the green light.
- Balancing limited capacity and the need to engage the wider department.

10. Next Steps for 2026 ([20:56])

Expansion: Launch of second task force cohort, doubling up on focus areas.
New Workstreams:
1. Personalization at scale
2. Advanced data applications (with improved systems integration)
3. Custom builds and automations (leveraging in-house tech talent)
“We’ve got a real whiz on our team this year… Kian, who is just incredible… He’s like a bit of a secret weapon at the moment.” – Emma (21:41)

11. Reflections on the Human Side of AI ([23:10])

AI is unlikely to totally replace jobs but will fundamentally change roles.
Real value lies in teams that combine AI with technical and human expertise.
Encourages listeners to become change-makers themselves.

“Take the bull by the horns and you be that change maker… it’s there for the taking.” – Emma (24:33)

QUOTES & MEMORABLE MOMENTS

On Personal Upskilling Motivation:
“Instead of doing Dry Jan, I’ll do AI Jan. And I really just threw myself into everything I could do with learning AI...” – Emma Tronson (01:45)
On Getting Buy-In:
“Make sure that you’re showing that you’re in tune with what your institution, what your company is looking to do over the course of the next however many years.” – Emma (03:13)
On Team Selection:
“I didn’t want a whole task force of yes people. I wanted people that were going to challenge our thoughts, that were going to check for bias, that… at times were anti-AI.” – Emma (09:13)
On “Lab Time”:
“If you don’t have that time in your diary, like you say, it’s so easy to just go back to the business as usual and not continue.” – Emma (14:09)
On System Integration Bottlenecks:
“System integrations has been a real challenge. I think there’s still such a mistrust and hesitation… It does feel like we’re kind of scraping the possible. But we’re just at the tip.” – Emma (19:24)
On Practical AI Adoption:
“I’m not in the camp of AI is going to take all our jobs. I do think people need to embrace it and learn how they can make themselves better at their own job with the use of AI. That’s the way we need to go.” – Emma (23:10)
On Becoming a Change-Maker:
“Take the bull by the horns and you be that change maker, you become that leader in the AI space… it’s there for the taking.” – Emma (24:33)

TIMESTAMPS FOR KEY SEGMENTS

Emma’s Personal Journey and Motivation – 01:35
Pitching and Structuring Task Force – 02:24
Task Force Objectives – 05:14
Recruitment Approach – 07:29
Team Structure (“Areas of Focus”) – 10:34
Member Support & Toolkits – 11:49
Lab Time & Ongoing Motivation – 14:06
Wider Launch and Rollout – 16:02
Embedding, Results, and Pitfalls – 18:30
Plans for 2026 and New Workstreams – 20:56
On the Human Side of AI, Change-Making – 23:10, 24:33

TAKEAWAYS & TONE

The episode offers a practical, empathetic guide—emphasizing that AI adoption is as much about people, learning, and organizational culture as technology.
Emma’s approach is refreshing, honest about setbacks, and clear in translating lessons for listeners.
The tone is empowering and collaborative, urging marketers (and all professionals) to take initiative and lead AI change from within.

For more episodes and related resources, visit TargetInternet.com/podcast
For collaboration or questions, connect with Emma Tronson on LinkedIn.

The Digital Marketing Podcast

EPISODE OVERVIEW

MAIN THEMES AND PURPOSE

How to move AI from experimentation to everyday embedded practice
Strategies for building and supporting an internal AI task force
Lessons in change management, governance, and sustainable digital transformation
Practical insights for marketing (and broader) teams to approach AI adoption

KEY DISCUSSION POINTS

1. Emma’s Motivation and Early Steps ([01:35])

Personal Drive: After a career setback, Emma decided to upskill, coining the term “AI Jan” for her month of deep AI immersion.

“Instead of doing Dry Jan, I’ll do AI Jan. I really just threw myself into everything I could do with learning AI...” – Emma Tronson (01:45)

2. Pitching the AI Task Force ([02:24])

Strategic Alignment: Emma pitched “Mission AI Impossible,” ensuring the project aligned with broader university strategy (Aston 2030).
Resource Ask: Rather than a large budget, Emma emphasized the need for committed staff time.

“The resource and time is key, particularly in this area.” – Emma Tronson (03:29)
Clear Objectives: She mapped out concrete deliverables, getting easy buy-in from leadership.

3. Objectives of the AI Task Force ([05:14])

Four clear goals:
1. Build AI expertise among select staff (via a hub-and-spoke model)
2. Pilot real use cases in specific domains (marketing, communications, student support)
3. Establish governance and internal guidance for AI use
4. Support the university’s wider digital transformation
“My ethos is always try and relate it to the work you’re doing, otherwise you’ll end up doing double the amount of work.” – Emma (06:16)

4. Recruiting and Structuring the Team ([07:17] – [10:34])

Selling the Benefits: Emma focused on personalized benefits for staff, using creative communication (including an AI-generated avatar) to spark interest.

“Don’t talk about how AI is going to help the company… Most people are working for themselves… they want to know how AI can support themselves.” – Emma (07:29)
Diversity and Reach: She sought a mix of skills and departments, including AI skeptics to challenge bias and reach hidden communities.

“I didn’t want a whole task force of yes people. I wanted people that were going to challenge our thoughts, that were going to check for bias…” – Emma (09:13)

5. Task Force Model: Six Areas of Focus ([10:34])

Aligned members to:
- Data & Analytics
- General Work Support
- Copywriting
- Visual & Creative
- SEO & Web
- Social & Community
Benefits: Provided direction, focus, and easier triage of support queries.

6. Guidance and Upskilling ([11:49])

Human Expertise First: Matched areas of focus to existing staff skillsets to minimize learning curve and boost confidence.

“If you have humans who can understand immediately what good looks like… you’ve solved half the battle there.” – Emma (12:19)
Toolkits and Support: Provided written guidance and a menu of suggested AI tools per area.

“I provided clear guidance… then I also gave them a list of AI tools to explore.” – Emma (12:58)

7. Motivation & “Lab Time” ([14:06])

Lab Time: Members scheduled regular, protected slots for AI learning and experimentation.
Working Groups: Biweekly meetings facilitated knowledge sharing and collective motivation.

“Sometimes you’re doing AI without realizing you’re doing AI, and when you’re forced to think of, oh, what was the latest thing that I have worked on, that helps you realize how far you’ve come.” – Emma (15:12)

8. Broader Roll-Out and Embedding ([16:02])

Staged Approach: After ~6 months of internal work, Emma launched a department-wide Q&A and introduced the task force to the organization.
Support Model: Task force members fielded queries and provided tailored help, with Emma facilitating connections and collaborations.

9. Results, Challenges, and Lessons Learned ([18:30])

Wins:
- Task force developed significant expertise
- Catalysed learning culture (e.g., “brunch and learns,” online sharing)
- Created inter-university collaboration
Setbacks:
- System Integration: Progress slowed by uncertainty over platform choices and lack of trust in digital services.
"System integrations has been a real challenge. I think there’s still such a mistrust and hesitation." – Emma (19:24)
- Much work focused on “safe” projects until IT gave the green light.
- Balancing limited capacity and the need to engage the wider department.

10. Next Steps for 2026 ([20:56])

Expansion: Launch of second task force cohort, doubling up on focus areas.
New Workstreams:
1. Personalization at scale
2. Advanced data applications (with improved systems integration)
3. Custom builds and automations (leveraging in-house tech talent)
“We’ve got a real whiz on our team this year… Kian, who is just incredible… He’s like a bit of a secret weapon at the moment.” – Emma (21:41)

11. Reflections on the Human Side of AI ([23:10])

AI is unlikely to totally replace jobs but will fundamentally change roles.
Real value lies in teams that combine AI with technical and human expertise.
Encourages listeners to become change-makers themselves.

“Take the bull by the horns and you be that change maker… it’s there for the taking.” – Emma (24:33)

QUOTES & MEMORABLE MOMENTS

On Personal Upskilling Motivation:
“Instead of doing Dry Jan, I’ll do AI Jan. And I really just threw myself into everything I could do with learning AI...” – Emma Tronson (01:45)
On Getting Buy-In:
“Make sure that you’re showing that you’re in tune with what your institution, what your company is looking to do over the course of the next however many years.” – Emma (03:13)
On Team Selection:
“I didn’t want a whole task force of yes people. I wanted people that were going to challenge our thoughts, that were going to check for bias, that… at times were anti-AI.” – Emma (09:13)
On “Lab Time”:
“If you don’t have that time in your diary, like you say, it’s so easy to just go back to the business as usual and not continue.” – Emma (14:09)
On System Integration Bottlenecks:
“System integrations has been a real challenge. I think there’s still such a mistrust and hesitation… It does feel like we’re kind of scraping the possible. But we’re just at the tip.” – Emma (19:24)
On Practical AI Adoption:
“I’m not in the camp of AI is going to take all our jobs. I do think people need to embrace it and learn how they can make themselves better at their own job with the use of AI. That’s the way we need to go.” – Emma (23:10)
On Becoming a Change-Maker:
“Take the bull by the horns and you be that change maker, you become that leader in the AI space… it’s there for the taking.” – Emma (24:33)

TIMESTAMPS FOR KEY SEGMENTS

Emma’s Personal Journey and Motivation – 01:35
Pitching and Structuring Task Force – 02:24
Task Force Objectives – 05:14
Recruitment Approach – 07:29
Team Structure (“Areas of Focus”) – 10:34
Member Support & Toolkits – 11:49
Lab Time & Ongoing Motivation – 14:06
Wider Launch and Rollout – 16:02
Embedding, Results, and Pitfalls – 18:30
Plans for 2026 and New Workstreams – 20:56
On the Human Side of AI, Change-Making – 23:10, 24:33

TAKEAWAYS & TONE

The episode offers a practical, empathetic guide—emphasizing that AI adoption is as much about people, learning, and organizational culture as technology.
Emma’s approach is refreshing, honest about setbacks, and clear in translating lessons for listeners.
The tone is empowering and collaborative, urging marketers (and all professionals) to take initiative and lead AI change from within.

For more episodes and related resources, visit TargetInternet.com/podcast
For collaboration or questions, connect with Emma Tronson on LinkedIn.

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

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Summary

The Digital Marketing Podcast

EPISODE OVERVIEW

MAIN THEMES AND PURPOSE

KEY DISCUSSION POINTS

1. Emma’s Motivation and Early Steps ([01:35])

2. Pitching the AI Task Force ([02:24])

3. Objectives of the AI Task Force ([05:14])

4. Recruiting and Structuring the Team ([07:17] – [10:34])

5. Task Force Model: Six Areas of Focus ([10:34])

6. Guidance and Upskilling ([11:49])

7. Motivation & “Lab Time” ([14:06])

8. Broader Roll-Out and Embedding ([16:02])

9. Results, Challenges, and Lessons Learned ([18:30])

10. Next Steps for 2026 ([20:56])

11. Reflections on the Human Side of AI ([23:10])

QUOTES & MEMORABLE MOMENTS

TIMESTAMPS FOR KEY SEGMENTS

TAKEAWAYS & TONE

Summary

The Digital Marketing Podcast

EPISODE OVERVIEW

MAIN THEMES AND PURPOSE

KEY DISCUSSION POINTS

1. Emma’s Motivation and Early Steps ([01:35])

2. Pitching the AI Task Force ([02:24])

3. Objectives of the AI Task Force ([05:14])

4. Recruiting and Structuring the Team ([07:17] – [10:34])

5. Task Force Model: Six Areas of Focus ([10:34])

6. Guidance and Upskilling ([11:49])

7. Motivation & “Lab Time” ([14:06])

8. Broader Roll-Out and Embedding ([16:02])

9. Results, Challenges, and Lessons Learned ([18:30])

10. Next Steps for 2026 ([20:56])

11. Reflections on the Human Side of AI ([23:10])

QUOTES & MEMORABLE MOMENTS

TIMESTAMPS FOR KEY SEGMENTS

TAKEAWAYS & TONE