About the Episode
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About The Episode:
Episode prompt:
https://www.linkedin.com/posts/mikekaput_you-can-use-ai-to-level-up-your-speaking-activity-7288952513226031104--ST5
https://aistudio.google.com/
You are an expert public speaking coach specializing in delivery techniques. Your role is to provide detailed feedback on the delivery of a presentation, focusing on aspects such as intonation, tone, talking speed, cadence, clarity, body language (if visible), and audience engagement. You provide constructive criticism and actionable advice while highlighting strengths.
I will provide you with a video or audio recording of my presentation. Your task is to analyze my delivery and provide expert feedback. Focus on the following elements:
Intonation and expressiveness: Does my tone engage the audience?
Cadence and talking speed: Is my pacing too fast, too slow, or just right?
Clarity and articulation: Are my words easy to understand?
Audience engagement: Does my delivery hold attention effectively?
Professionalism: Do I come across as confident and credible?
Your Response Should Include:
Strengths: Highlight specific moments where my delivery shines and explain why they work well.
Areas for Improvement: Point out specific moments or patterns that could use improvement. Provide actionable techniques or exercises to address these areas (e.g., breathing techniques, pacing drills).
Overall Grade: Give a grade on a scale of 1–10 for my delivery, along with a brief explanation for the score.
General Tips: Summarize a few tips or exercises to enhance my overall delivery.
Example Format:
Strengths: "Your intonation is excellent; it varied naturally and kept the audience engaged. For example, at 1:45, your tone became more dynamic as you introduced an important point, which emphasized its significance."
Areas for Improvement: "Your speaking speed is slightly too fast between 2:00–3:00, which made it harder to follow. Try practicing deliberate pauses at the end of each sentence to improve pacing."
Grade: 8/10.
Tips: "Record yourself practicing with intentional pauses. Work on controlling your tone by practicing modulation exercises like reading aloud dramatically."
Key Notes:
Take your time and provide detailed, step-by-step feedback for each element of my delivery.
If anything is unclear in the video or audio, let me know, and I'll clarify or provide more context.
When you deliver the feedback, ensure it is constructive, specific, and actionable.
Host Brian chats with Tracy Playle, founder of Pickle Jar and the Content Ed community, about the role of AI in content strategy for higher education. Tracy shares how her team at Pickle Jar is using AI to enhance audience research, content co-creation, and administrative workflows. She also explores the biggest challenges institutions face when integrating AI and offers actionable advice on how schools can start experimenting with these tools. Whether you're a skeptic or an enthusiast, this episode provides a practical and thought-provoking look at AI’s impact on content and marketing in higher ed.
Key Takeaways
- AI enhances content strategy – AI can help process audience research, identify trends, and develop content architectures.
- Co-creation, not replacement – AI is best used as a collaborator, accelerating brainstorming and ideation rather than replacing human creativity.
- Overcoming barriers to AI adoption – The biggest challenges in higher ed include lack of time, slow policy development, and messy data.
- Change management is key – AI adoption requires leadership buy-in and a shift in mindset toward workflow transformation.
- Start small and iterate – Institutions new to AI should begin with low-risk tasks like reformatting documents or summarizing meeting notes before scaling up.
- Structured content is essential – AI-driven personalization requires highly structured content and robust taxonomy frameworks.
- AI literacy is a must – Institutions should invest in training and hiring for AI proficiency to fully leverage its potential.
How Pickle Jar Uses AI to Enhance Higher Ed Content Strategy
AI in Audience Research and Content Strategy
Tracy’s team at Pickle Jar heavily relies on AI for audience research—one of the most critical components of content strategy. AI tools help process vast amounts of data, from survey responses to interview transcripts, identifying key themes and trends more efficiently than manual analysis.
One of the biggest advantages AI provides is the ability to generate audience personas and "motivational tribes." By analyzing patterns in student and stakeholder behaviors, AI helps marketers design content architectures that better align with user needs. This ensures that institutions are delivering the right messages to the right people at the right time.
For higher ed marketers, AI offers an opportunity to shift from intuition-based decisions to data-driven strategies. Institutions that integrate AI into their research processes will be better equipped to create content that resonates with prospective students and stakeholders.
The Power of AI in Content Co-Creation
Tracy describes her use of AI as a “second shower” for creativity—meaning it accelerates the ideation process much like those moments of inspiration that happen in the shower. Instead of waiting for the perfect idea to strike, AI tools can quickly generate options that Tracy and her team can refine.
Rather than relying on AI to write content from scratch, she uses it as a collaborator. For example, when working on brand messaging for a client, Tracy briefed ChatGPT to generate multiple versions of the same message with different tones—bold, moderate, and subtle. This kind of AI-assisted content iteration speeds up the creative process and provides fresh perspectives.
AI can also enhance storytelling. Tracy frequently uses it to find compelling anecdotes and case studies to strengthen her presentations and talks. This allows her to focus on crafting a narrative rather than spending hours searching for the perfect example.
Overcoming AI Adoption Challenges in Higher Ed
Despite AI’s potential, higher education institutions often struggle with adoption. Tracy identifies three major barriers:
- Time and Space to Experiment – Staff are overwhelmed with growing workloads and shrinking resources, making it difficult to carve out time to explore AI tools. Ironically, AI could be the solution to these productivity challenges, but institutions need to invest time upfront to see the long-term benefits.
- Slow Policy Development – Universities tend to wait for formal policies before implementing AI. Tracy argues that this cautious approach stifles innovation. Instead, institutions should encourage hands-on experimentation to inform policy development, rather than delaying progress.
- Data Quality Issues – Higher ed has a wealth of data, but much of it is unstructured or outdated. AI works best with clean, well-organized data. Institutions must improve their data governance practices to fully capitalize on AI’s capabilities.
Tracy also emphasizes the importance of educating senior leadership on AI’s potential and limitations. Many university leaders have unrealistic expectations about what AI can do, assuming that it can instantly create highly personalized content experiences. However, without structured content, robust taxonomies, and audience insights, AI-driven personalization simply isn’t possible.
How Institutions Can Get Started with AI
For universities looking to integrate AI into their workflows, Tracy recommends starting small and focusing on six key task areas:
- Repetitive Tasks – Automate administrative work like formatting documents or summarizing meeting notes.
- Boring Tasks – Use AI for routine work that human employees find tedious, freeing them up for more strategic efforts.
- 24/7 Availability – Implement AI chatbots to provide instant responses to FAQs for students and prospective applicants.
- Easily Trainable Tasks – Identify tasks that AI can be trained to handle quickly and efficiently.
- Low-Risk Activities – Begin with AI applications where errors won’t have significant negative consequences.
- Complex Data Analysis – Leverage AI to analyze large datasets and uncover insights that human analysts might miss.
By identifying opportunities within these areas, institutions can ease into AI adoption without feeling overwhelmed.
The Future of AI in Higher Education
Looking ahead, Tracy predicts that AI in higher education will evolve in three major ways:
- More Advanced Multimedia Capabilities – AI-driven video editing and voice synthesis will enhance content creation and accessibility, including seamless language translation for international students.
- Specialized AI Applications – Instead of generic AI models, institutions will see more AI tools tailored for specific higher ed functions like SEO optimization, student engagement, and course design.
- Agentic AI Growth – AI will shift from being a passive tool to an active assistant, capable of performing complex tasks and making decisions within defined parameters.
While AI continues to improve, Tracy believes that its real impact will come from how institutions use it, not just how powerful the technology becomes. The key will be rethinking workflows, fostering AI literacy, and integrating AI into strategic priorities rather than treating it as a quick-fix tool.
Connect With Our Host:
Brian Piper
https://www.linkedin.com/in/brianwpiper/
About The Enrollify Podcast Network:
AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!
Some of our favorites include Generation AI and Mastering the Next.
Enrollify is produced by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.
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