Putting AI To Work For Specific Tasks
episode
Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast
48 min
2 speakers
8 chapters
transcribed 1 month ago
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the main focus of the episode and who is the guest?
The Voices of Search Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast? I Hear Everything delivers podcast production, growth, and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit IHear Everything.com. Welcome to the Voices of Search Podcast, a member of the I Hear Everything Podcast Network. Ready to expedite your company's organic growth efforts? Sit back, relax, and get ready for your daily dose of search engine optimization wisdom. Here's today's host of the Voices of Search Podcast, Tyson Stockton.
Hey, what's going on? My name is Tyson from previsible.io, and joining me today is Brittany Mueller, who is the data scientist advocate at Britney Mueller Inc., which specializes in providing innovative digital marketing solutions achieved through a combination of cutting-edge technology and creative strategies. Today, Brittany and I are gonna be discussing putting AI to work for specific tasks. So with that, here's my conversation with Britney, data science advocate at Brittany Mueller Inc. Brittany, welcome to the podcast.
Woohoo, thanks for having me. This is awesome.
Uh I was I was looking forward to having you on here. I think as we were talking before the show, have a shared interest in the education space. Um so I think it's really cool what you've been working on from kind of AI education and trailing and yeah, kind of that entire front. So thanks for joining us.
Yeah, thanks for having me.
And I mean we're we're doing kind of today's conversation, tomorrow's as well, but today we wanted to jump into more of like different applications of AI. And I think most people A lot of the the narrative tends to drift towards content, generative AI. I have a suspicion that you're kind of thinking in uh maybe a wider lens. Like how would you set the stage for the listeners of like what should our perspective be? Like what's the breadth of options that we can really be working towards instead of just content?
Yeah, I love this question because I think so often, like especially right now with just all of kind of the AI hype and things exploding around AI, we are inundated with AI messaging that it's going to make our work faster. more efficient and productive. All of these vague productivity terminology is typically used to describe AI today. And what's interesting is it's a lot like programming in terms of application, you have to get really, really task specific to have it add value to your day-to-day life. And so oftentimes, you know, people kind of overlook the task that might take them 20 minutes a day. But if you figure out a way to streamline and automate that using something like AI if applicable, you know, over the course of a year, you're saving over 86 hours of work, right?
Over two full weeks of your time. So I think it's important to kind of create a fun playground to experiment with really, really task specific applications, right? And and to take a step back and identify what are the common tasks that you do each and every day? What does that look like? Right, what are you and your team working on? What sort of insights would be super, super valuable for you know, maybe your project or this quarter's goal? How could you start to kind of uncover different insights that AI can support you with? So, in my opinion, AI applications are everything from helping to clean up and organize your inbox. To categorizing massive amounts of customer insights and reviews and conversations on platforms like Reddit, the ability to surface real-time kind of temperature checks on how people are perceiving your tool, your services, your brand, etc., are more
attainable and valuable right now because it's more accessible than ever. You're able to use that and wield it in ways that we've never really had access to before. And then it's all the way to the research support side. There's um My friend had helped found this company, Monkey Learn, where they did sentiment analysis at scale.
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Chapters
8 chapters
1
What is the main focus of the episode and who is the guest?
0:00–7:03
2
How can AI be applied to specific, everyday tasks rather than just generic content creation?
7:03–12:49
3
What are the key limitations of large language models that listeners should be aware of?
12:49–18:37
4
Which practical AI use‑cases (e.g., sentiment analysis, inbox cleaning, data categorization) are highlighted?
18:37–24:33
5
How does prompt engineering (few‑shot vs zero‑shot) improve AI output for task‑specific work?
24:33–30:29
6
Why is human creativity still essential when using AI tools?
30:29–36:33
7
What future trends (digital PR, brand mentions, backlinks) are shaping AI‑enhanced SEO?
36:33–43:00
8
What final advice does the guest give for balancing AI automation with authentic human effort?
43:00–48:11