Using AI Industry Agents to Enhance Learning in Sport Management
In sport education, connecting students with real-world industry insights is crucial — yet often difficult to achieve at scale. While site visits and guest speakers provide valuable learning opportunities, these options rarely allow for personalised, one-on-one feedback. In first-year cohorts especially, this creates a gap: how can we provide students with authentic industry guidance that challenges their ideas while still supporting their development?
This is where I believe AI industry agents can play a valuable role.
I recently developed an AI agent called Jack, who acts as Auckland FC’s Marketing Manager. Jack is designed to provide personalised, industry-style feedback to students as they develop marketing ideas for Auckland FC. While Jack hasn’t yet appeared in my classroom, he will be introduced later in the semester as part of Assessment 3, where students will engage with him to refine their ideas.
In this post, I’ll explore:
How Jack fits into my course and the student learning experience
Why I chose Cogniti over other AI tools like ChatGPT
How I designed Jack’s responses to guide students at different stages of their learning
Why this approach matters for sport educators seeking to enhance student engagement and improve learning outcomes
The potential future for AI industry agents in sport management education
How Jack Fits into My Course
My course is a first-year, 'Intro to Sport Management & Marketing' undergraduate course with approximately 170 students across three classes. It follows a structured case study approach with Auckland FC, designed to build student understanding of the challenges sport organisations face and how marketing initiatives can address those challenges.
The course’s assessment structure is built around this partnership:
A1: Students identify a challenge Auckland FC faces and conduct research to understand the club’s environment and stakeholders
A2: Students write a report that explores how the identified challenge impacts Auckland FC’s environment and key stakeholders.
A3: Students work in groups to develop a marketing initiative that promotes an opportunity or idea based on their identified challenge.
The assessments are designed to help students develop key sport management skills — particularly creative thinking, strategic planning, and communication. These skills are essential as students build marketing ideas that respond to real-world challenges faced by Auckland FC.
Auckland FC actively supports this case study by hosting Q&A sessions in each class in Week 3 and Week 10 and providing materials to inform students’ work. However, Auckland FC can’t provide individualised support to 170+ students throughout the semester — which is where Jack steps in.
By introducing Jack at the start of Assessment 3, students can engage with him to test ideas, refine their concepts, and seek feedback — essentially providing a personalised industry voice when direct access to Auckland FC’s staff isn’t possible.
Why Cogniti?
I chose Cogniti because my university was offering a pilot program for educators to trial the platform, and I was selected to participate. While I initially joined the pilot to explore its potential, I’ve since found Cogniti offers several features that align well with my teaching goals — particularly when compared to tools like ChatGPT.
Cogniti integrates directly into Canvas (LMS) meaning students can engage with Jack within the same platform they use for their course materials. This makes the experience seamless and ensures the AI agent feels like an integrated part of the learning process.
Unlike ChatGPT, Cogniti’s agents are self-contained and do not pull information from the web. This ensures all responses are based on the carefully curated background information I’ve provided, keeping conversations focused on course content and sport industry insights.
A key advantage of Cogniti is my ability to control Jack’s responses. I can shape his feedback to align with course objectives and Auckland FC’s context. Additionally, Cogniti provides insights into student interactions, allowing me to see:
What questions are students asking
What ideas they are exploring
Where they may be struggling
This insight is particularly valuable because it allows me to identify patterns in student thinking and spot where additional guidance or class activities may be helpful. Cogniti enables me to intervene at the right time, ensuring Jack complements — rather than replaces — my teaching.
How I Created Jack
Creating Jack required more than just writing scripted responses. I wanted him to feel authentic, challenge students’ thinking, and align with the complexities of the sport industry.
Building Jack’s Knowledge Base
The first and most important step in building Jack was ensuring he had enough meaningful background knowledge to provide valuable feedback. I started by curating key information about Auckland FC to build Jack’s content library. This involved identifying core themes that would shape Jack’s responses:
Information about Auckland FC as a newly established professional football club with a strong focus on building community ties, engaging local families, and connecting with diverse cultural groups.
Jack needed to understand Auckland FC’s focus on inclusivity, cultural connection, and developing pathways for emerging Kiwi talent.
I embedded insights about Auckland FC’s target markets — particularly Māori, Pasifika, and immigrant communities — as well as engagement priorities like youth-focused initiatives.
Data such as Auckland FC’s average match attendance, social media growth, and commercial objectives informed how Jack could challenge students to align their ideas with measurable outcomes.
By ensuring Jack’s knowledge base reflected Auckland FC’s actual goals and strategies, I could ensure his feedback felt grounded in real industry thinking rather than generic marketing advice.
Creating Flexible Response Pathways
Once I had Jack’s background content established, I worked on building conditional pathways in Cogniti’s back-end design.
I anticipated key moments where students might struggle — particularly first-year students — and designed responses accordingly. For instance, Jack has specific responses for students who:
Ask for direct answers
Struggle to generate ideas
Propose surface-level concepts
Need guidance on refining their creative marketing piece
Rather than programming Jack to deliver a one-off answer, I created layered prompts that keep conversations flowing. This encourages students to expand their ideas rather than shutting the conversation down with a quick response.
For example:
Student: "I don’t know what to do."
Jack: " That’s okay — let’s take a step back. Think about Auckland FC’s stakeholders — are there groups we aren’t engaging as well as we could be?"
If the student responds with something like "They’re launching a women’s team," Jack follows up with:
Jack: "That’s a great starting point. How could your idea connect to that? Could you create something that builds excitement for the launch or spotlights women’s players?"
These layered prompts ensure students are accountable for contributing ideas, while still feeling supported.
Challenging Surface-Level Thinking
One of my biggest concerns was ensuring Jack could push students to think more creatively and strategically, particularly when they default to predictable ideas like "a meet and greet" or "a giveaway."
Instead of rejecting these ideas outright, I designed Jack to:
Ask why the student chose this idea
Prompt students to reflect on what they’re trying to achieve with their concept
Encourage students to connect their ideas to Auckland FC’s strategic priorities, audience needs, and values
Guide students to expand their concept into something more innovative or impactful
To encourage creative thinking, Jack’s responses are designed to push students beyond predictable ideas. By prompting students to reflect on their objectives, target audience, and Auckland FC’s values, Jack helps students connect their ideas to broader sport marketing strategies — reinforcing key learning outcomes linked to strategic planning and stakeholder awareness
Example 1: Expanding a Basic Concept
Student: "I’m thinking about a social media giveaway."
Jack: "Interesting! What’s the thinking behind that? Are you aiming to build excitement before a big match, connect with families, or highlight Auckland FC’s values? Knowing your goal will help shape what this could look like."
If the student struggles to expand their thinking, Jack might follow up with:
Jack: "Could there be a way to involve Auckland FC fans in the process? Maybe something that encourages them to create content or feel more connected to the club’s story?"
By challenging surface-level ideas like ‘meet and greets’ or ‘giveaways,’ Jack helps students apply marketing theory — encouraging them to think beyond tactics and instead focus on objectives, target audiences, and stakeholder needs."
Example 2: Pushing Beyond a Predictable Idea
Student: "I was thinking of a meet and greet to connect with younger fans."
Jack: "That’s a good starting point. What makes a meet and greet meaningful for those fans? Could you build something around that idea that goes beyond just signing autographs? For example, what would make the experience memorable enough that they’d talk about it afterward?"
If the student needs further guidance, Jack might follow up with:
Jack: "Think about what younger fans are interested in — could there be something interactive, visual, or linked to social media that keeps the conversation going after the event?"
This encourages students to rethink the purpose behind their concept — not simply suggesting a ‘better’ idea but guiding them to develop a more thoughtful and strategic approach.
The key to these responses is that Jack doesn’t tell students what to do — instead, he asks questions that guide students to refine their ideas. By focusing on purpose, audience, and creative execution, Jack encourages students to expand their thinking beyond surface-level ideas.
This back-end design was intentional — Jack’s responses are built with flexible prompts that allow conversations to unfold naturally, keeping students accountable for developing their own ideas while still feeling supported and encouraged.
Jack supports Learning Outcomes
Jack’s design was shaped to align with my course learning outcomes. By guiding students to think critically about stakeholder needs, marketing strategies, and creative execution, Jack encourages students to:
Apply sport marketing theory by linking ideas to Auckland FC’s audience and brand
Develop strategic thinking by exploring the purpose and objectives behind their ideas
Strengthen communication skills by testing ideas and refining their creative execution
These skills align directly with the course’s emphasis on creative problem-solving, stakeholder awareness, and strategic decision-making — all essential for future sport industry professionals.
Why does this matter for Sport Educators?
AI industry agents like Jack offer a scalable solution to a common challenge in sport management education: providing personalised, industry-relevant feedback at scale. In large first-year cohorts, supporting students as they develop unique ideas can be difficult, particularly when projects require individual creativity and strategic thinking. Jack helps bridge this gap.
By combining reflective questioning with tailored insights, Jack prompts students to think critically about sport marketing strategies, stakeholder needs, and creative execution. This aligns closely with the kinds of skills sport educators aim to develop — skills like problem-solving, strategic decision-making, and audience awareness. For example, first-year students often lean toward familiar ideas — ‘meet and greet’ events or simple giveaways — because they feel safe. Jack’s questioning pushes students to expand these ideas, connecting them to Auckland FC’s values, target audiences, and strategic priorities. This not only encourages more thoughtful solutions but also reinforces key marketing concepts like audience segmentation, brand positioning, and community engagement.
Importantly, Jack’s responses provide a ‘safe space’ for students to explore ideas without the fear of failure. This is particularly valuable for students who are hesitant to participate in class discussions or feel unsure about their creative ideas. By providing constructive prompts and encouragement, Jack helps students build the confidence to test their thinking, refine their ideas, and take creative risks — all vital skills for sport management graduates.
Finally, Jack’s design supports educators by offering insights into student thinking. Through Cogniti’s reporting features, I can track patterns in the questions students ask, identify common roadblocks, and adjust my teaching accordingly. This allows me to better understand how students are engaging with course content and intervene at key moments to guide their progress.
Where to next?
Looking ahead, I see exciting potential for expanding how AI industry agents like Jack can be used in sport management education, particularly in ways that reflect the complexity of the sport industry.
A suite of agents, not just one voice
Real-world feedback rarely comes from one person. In future iterations, I’d love to build a range of agents offering different perspectives. For example, a Commercial Director focused on sponsorship revenue, a Community Engagement Officer focused on inclusion, or a Digital Media Manager with content strategy expertise. Students could engage with these varied voices to test their ideas against different stakeholder priorities.
Roleplay and Real-time challenges
Agents could be used to simulate unfolding scenarios over a semester such as managing fan backlash, responding to sponsorship loss, or adapting to new match-day restrictions. These experiences would prompt students to think critically under pressure and adapt strategies on the fly, much like they would in real-world sport environments.
Diverse and culturally grounded perspectives
I’m particularly interested in developing agents that reflect Māori, Pasifika, and immigrant community perspectives. This would challenge students to consider cultural values, inclusive engagement, and how marketing connects to identity — not just commercial goals.
Differentiated support based on learner needs
Not every student needs the same kind of feedback. Some might benefit from a mentor-style voice that builds confidence, while others might need more direct, critical questions to stretch their thinking. Offering students a choice of agent styles could make feedback more meaningful and tailored.
Ultimately, I see AI industry agents not just as feedback tools but as dynamic learning companions that push students to think strategically, creatively, and ethically. When designed with purpose, they can expose students to multiple perspectives, foster decision-making, and prepare them for the messiness and nuance of real-world sport work.
If you’re working with AI in your teaching or thinking about how this might fit in your context — I’d love to hear your ideas. Let’s keep the conversation going.