[Heather Bayer]
Today's episode is a podcast within a podcast, and if you want to find out what that means, you're just going to have to listen in.

This is the Vacation Rental Success podcast, keeping you up to date with news, views, information and resources on this rapidly changing short term rental business. I'm your host Heather Bayer, and with 25 years of experience in this industry, I'm making sure you know what's hot, what's not, what's new and what will help make your business a success.

Well hello and welcome to another episode of the Vacation Rental Success podcast. This is your host Heather Bayer, and as ever, I am super delighted to be back with you once again.

So what do I mean a podcast within a podcast? Well, you're going to have to wait a bit to find out for that because I just want to share a bit about what I've been doing recently, as if I haven't been sharing all that over the last few weeks. You know that I'm going down the rabbit hole of AI and learning a huge amount and being very mindful that there are humans on the other side of AI. And that's something that the more I get into it, the more I realize that I've got to keep that the back of my mind or maybe the forefront of my mind. In fact, I go down these rabbit holes and get lost in creating assistance and agents and looking at different apps and websites all about AI. And it's very easy to fall into that trap that AI is going to resolve everything for humanity. But in fact, it is not. It is more a helping hand to the humans. That's the way I'm seeing it now.

But anyway, did you know there's a website called There's an AI for that and it lists all of the apps that are currently out there. There are 36,734 apps on there at the time I am recording this. I just checked it this morning, which is a problem for me. I love my bright, shiny new things. Always been an early adopter of just about everything that comes out. I love to get in, get my hands dirty, just trying things out. And it can be a huge time waster.

And even more so these days, it was a time waster 15 years ago when I was getting into new stuff that was only coming along every few months. And now there are new things coming along every single day. And I know if I let my BST, my bright, shiny things syndrome get the best of me, I would not be doing anything else, but just exploring bright, shiny new things.

So I have to be very intentional, very focused. So I am basically I've come down to around about five platforms that I use on a consistent basis. One is ChatGPT. I think that is probably the one I use 80 percent of my time. Then there is Claude from Anthropic. That's the one I tend to use if I'm if I'm creating content. And a little aside on that, when I create content, it is 80 percent me. I come up with the ideas. I come up with the stories. I don't allow AI to create my stories. They are all mine. But what I do with it then is take the outline and write it as I would a blog post. And you know, I've written over fifteen hundred blog posts in the last however many years since I started blogging and I have a voice. It's for me, it's quite distinct. It's unique.

I've uploaded a ton of my blog posts to a GPT to give it my brand, my tone, the way I write. And so when I have my outline now of something I'm going to post, I'll put it into ChatGPT and ask it to apply my voice to it. And it will create the blog. I take out any stuff that it makes up. I adjust it. I read it thoroughly afterwards. I edit it. I proofread it. And to all intents and purposes, I feel that it is still my own work. I've allowed the AI to tidy it up a bit and make it look a bit better.

So anyway, that aside. So I'm using ChatGPT. I'm using Claude. I use Perplexity. Perplexity is sort of my Google now. I far prefer using Perplexity than I do Google. Occasionally I use Gemini when I'm in Gmail. Gemini is a Google product.

And the fifth one that I wanted to mention, because I'm going to talk a bit more about this one today is Notebook LM, which is also a Google product. And I use, I don't, I'm not going to say I use Notebook LM a lot because I don't do massive amount of research. But when I do, it is definitely the platform I go to when I want the large language model to research just sources. I don't want it to make anything up. I don't want it to go out and do its own thing. I want to give it a certain set of sources and say, tell me what this all says when you put it all together. Give me summaries, give me briefing docs, give me a mind map. Give me a podcast. So that's what I'm talking about right now.

Think of Notebook LM as a smart interactive notebook, which is powered by AI. And the best thing is what I just mentioned, that it reads, it learns, and it's response is based only on the content you give it. And that's to me is a big deal because unlike most AI tools that pull from the entire internet, and as I said, they sometimes hallucinate, make things up, Notebook LM doesn't do this. It sticks strictly to your sources, which you've chosen. So when it gives you an answer, it's not guessing, it's actually referencing what you, gave it. And that makes it a real trust booster for many business owners who, like us, need reliable insights and facts.

So how you use it is to upload any content you want. And it could be content from your Google drive, PDFs, industry reports, guest reviews, market research, your own listing copy, even competitor blogs, the things that you've gone out and found. Notebook LM then reads it and then it creates a dynamic, source-linked summary, a commentary if you like, and then you can ask it questions. You can generate ideas and you can even request full content drafts. And it's all rooted in your own material, which means it's not giving you generic answers, it's in effect, tailoring its responses to your exact business context.

So let me highlight a few of the features that I think makes it way more than a fancy chatbot. So first thing is briefing documents. Once you've got all your sources in there, it automatically creates short executive-style summaries of all the content you upload. So it's like AI prepping you for a meeting with a one page cheat sheet, a new feature is the mind mapping tool. And I've always loved mind mapping. I used to do it just freehand with a lot of colored pens. I just enjoyed mind mapping. And then about 15 years ago, I think, they came out with some of the first mind mapping tools and I just really enjoy enjoyed using them, because it helps you connect ideas or plan a project. I mean, certainly if you're planning a website or something, then mind mapping is just awesome. But Notebook LM takes all your content that you've got from all these sources and then then visualizes it in a mind map format. And that just helps you see structure ideas. It helps you see relationships between things and best of all, it sparks creativity. Then let's go back to the source themselves. It creates automatic source citations. So every response you get from it gives it fully linked to the exact document and section it came from. And then you can click right into that source and see very clearly that it is the genuine document. That means no guessing. It's just clarity.

And then you've got the Smart Q&A, have a conversation with it. An example might be, what are the top concerns my guests have mentioned in past reviews? Let's say you've uploaded 20 or 30 past reviews, or maybe more, maybe you've uploaded hundreds of reviews that have come to you that you have in one PDF document. You can ask it, what are the top concerns my guests have? Upload competitors reviews. And then you could ask things like how are, how are my competitors describing their pet friendly policies? And you get the answers really fast.

I have not used it for content creation, but you could certainly do that. You could write a blog post on the top local attractions and let's literally say draft this for me based on these sources. So you've got a whole bunch of sources on things that are going on in the local area, and it will do that draft for you.

So let's look at some real use cases, some scenarios where the tool is pretty much a game changer. First one is competitor and market research, and you can upload screenshots or texts from competing listings, add in some market reports, and then ask Notebook LM to identify pricing trends, any feature gaps or any standout guest perks. That's going to help you find your edge.

Listing optimization. You can upload your Airbnb or Vrbo listings and then put them alongside some other competitor listings and ask for some feedback, like how can I improve my title or property description to attract families, or digital nomads, or whoever your avatar is going to be. Use it as a guest messaging strategy, feed it your last 50 guest reviews or inquiries even, then ask what your guests are most concerned about, what they love, and how your communication style can be improved.

It's sort of like a mirror for your brand. And then mention content creation, think about creating a neighborhood guide, an FAQ section, or even a blog post to boost your SEO. So upload your research or your notes and ask Notebook LM to write a first draft. It's like having a copywriter. Having said that, I'm not sure I would use it that much for content creation. That's when I would go to Claude, but you could pull in content from competitors and ask it to pull out what is the most attractive style, or what appears to be drawing in your particular avatar, your target market that you want to attract.

So lots and lots of use cases. The best part of this, you don't have to have any skills. And that's actually pretty much the same for all of these platforms. It's what AI has made so much easier for us. These tools are designed to be intuitive. You know, if you can upload a file and you can type a question, you're already 90% of the way there. So bottom line, whether you're managing one unit or 20, it lets you act like a team of analysts and researchers and marketers all in one.

But let's get to the podcast within a podcast, because this is one of the best features I think that Notebook LM offers. You've got all your sources. You've got your 10 sources. I think you can have up to 50 sources. So you've collected all the sources and then you can go and ask it to create a podcast from those sources. Now, I could talk to you about that, but I'm not going to. I'm actually going to share what I did yesterday and the podcast I created from it.

So at the moment here at the Vacation Rental Formula Business School, we're currently building out a new training program that we're calling the AI Ambassador Program. And you're going to hear more about this over the next few weeks, but it's a course, it's a program, that will help people within organizations to really get to grips with how they can adapt and integrate AI across their company. And before we roll that out, we're really looking at how companies are currently adapting and integrating and pulling in all this material and making it consistent across their organizations.

So I went into Notebook LM and I asked it to bring in some sources of information about how small businesses are doing this, how small businesses are integrating AI within their companies right now. And that brought up 10 sources. So I then, having looked at the briefing document and having looked at the mind map, I then went over to the audio section, the podcast section, and I asked it to create a podcast segment summarizing the key takeaways and practical applications for entrepreneurs and operators in the short-term rental space.

So what you're about to hear is what Notebook LM produced. There's no edits, there's no rewrites, just the raw output from this incredible tool. And I think you're going to be really impressed. Listen through it, because the material that it has produced from these sources, I think you're going to find really useful. And I'll get back to you when that section is finished.

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Okay, let's unpack this. We've got quite a stack of sources here, haven't we?

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We really do. A real treasure trove, you could say.

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Reports from Software One, Harvard Business School Online, an invoice factoring company, Microsoft, LinkedIn.

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Access partnership is in there too, Ray Contour, Marketplace, the IELTS blog.

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And Manchester Metropolitan University. And well, they're all pointing towards something pretty massive.

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Yeah, huge ways of change, specifically for small and medium sized businesses.

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Driven by AI and generative AI in particular.

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Exactly.

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You know, AI isn't just this like futuristic thing anymore, is it? Or something only the big tech giants can afford.

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Not at all. It's actually becoming incredibly accessible now.

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A powerful tool that can really transform even the smallest businesses, affecting your day to day, your long term strategy, everything. So our mission for this deep dive is, well, to cut through all the noise, all the hype.

[Speaker 4]
Yeah, there's a lot of it out there.

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We want to understand what this technology really means for you if you run or work for an SMB right now.

[Speaker 4]
What are the actual opportunities? The tangible benefits.

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And the pitfalls too, right? Let's be real about those.

[Speaker 4]
Absolutely. There are definitely challenges to navigate.

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And crucially, how do you figure all this out without feeling totally overwhelmed?

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Think of this as maybe a shortcut, a way to get up to speed on something that's becoming pretty essential.

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A shortcut to being genuinely well-informed. I like that.

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So what's fascinating, pulling from sources like Software One and the IEL blog, is this idea of AI as an equalizer.

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An equalizer. How so?

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Well, generative AI specifically is giving SMBs opportunities they just didn't have before. Opportunities to compete, really compete with much larger companies.

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So it levels the playing field?

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It really can. That Software One report even suggests that, you know, because SMBs can be nimbler, quicker to adapt, they might actually be able to use this innovation to tip the scales in their favor. They can move faster than the big guys sometimes.

[Avatar 1]
Wow. Okay. That idea of leveling the playing field, that's powerful.

So let's jump in. How is this actually showing up? What are the real benefits businesses are seeing right now?

Time savings seems like a huge one.

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Oh, absolutely. And the numbers, especially from that invoice factoring source, are quite striking. Go on.

A typical small business owner they found is saving around 13 hours per week, just on their own tasks using AI.

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13 hours? That's almost two full work days.

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And wait, there's more. On top of that, they're shaving another 13 hours off employee hours across the team.

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Okay. Hold on. That's 26 hours a week combined.

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Exactly.

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That's like getting an extra half an employee's worth of time back, but without hiring anyone new.

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Pretty much.

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So what are businesses actually doing with all that extra time? Is it just less work?

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Well, that's where it gets interesting. According to the invoice factoring and LinkedIn reports, it's not just about doing the same stuff faster.

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Right.

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It's freeing up bandwidth for higher value work. The stuff that usually gets pushed aside by the daily grind, you know? Things like R&D, business development, spending more quality time engaging with customers, and importantly, upskilling their employees.

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Investing back into the team.

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Precisely. That LinkedIn report, they surveyed businesses using Gen AI and get this, three quarters of them, 76% reported significant time savings.

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76%. That's huge.

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It really is.

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So this incredible efficiency boost, it leads to more capacity for strategic thinking, for growth. Does it also translate into actual dollars and cents saved?

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It absolutely does. That same invoice factoring survey, they found a median annual savings of $7,500 for businesses using AI.

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Seven and a half grand. That's not trivial for an SMB.

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Not at all. And a quarter of those businesses reported saving over $20,000 a year.

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Wow. Okay. How is that saving happening?

Is it just, you know, cutting jobs?

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Not primarily. No, it's mostly coming from automating those repetitive tasks and just improving overall efficiency. The I'll blog and invoice factoring sources really highlight this.

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So things like data entry, scheduling, basic communications, drafting.

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When AI handles that stuff, your operational costs go down and your team is free for, well, more valuable activities.

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And AI helps with making decisions too, right? Handling all that data.

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Oh, massively. It's ability to process huge amounts of data super quickly and pull out actionable insights.

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Yeah.

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That's invaluable, especially if you don't have a big analytics team.

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Which most SMBs don't.

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Sources like invoice factoring, IL blog, GoDaddy. They all point this out. It helps you make smarter predictions.

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Like forecasting demand or cashflow.

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Yeah. Analyzing customer behavior patterns. That invoice factoring report even suggests AI can cut supply chain errors by like 20 to 50%.

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50%. Okay. That directly ties into productivity and efficiency, which seems to be a theme across GoDaddy Software One, IL blog.

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It's foundational really. And the potential scale here is just enormous.

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How enormous.

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LinkedIn estimated that if generative AI was used across all work tasks in just five major economies, US, UK, France, Germany, India, it could unlock up to $6.6 trillion in productive capacity.

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Trillion with a T.

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Trillion with a T. And half of the executives in that invoice factoring survey said AI boosted their productivity.

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Okay. So better efficiency, better decisions, more productivity. Does this circle back to actually growing the business?

More revenue.

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It seems to be a direct line for many. LinkedIn found half the companies they surveyed saw a revenue boost of 10% or more after adopting Gen AI.

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10% or more just when adopting AI.

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And invoice factoring noted that 80% of businesses using AI specifically for marketing and sales see a revenue increase.

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80%.

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Makes sense. Save time, cut costs, make smarter moves, get more done. Revenue tends to follow.

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Okay, this is where it gets really interesting for me. It's not just this like general idea of AI is good for efficiency.

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Right.

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These sources, Software One, IELTS blog, GoDaddy, Marketplace, Ray Contour, they lay out really practical, specific ways you can use AI in different parts of your business. Like actual examples.

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Exactly. Let's take sales and marketing, which we just touched on. Software One talks about AI building detailed customer profiles, grabbing competitive intelligence, stuff like SWOT analyses.

Strengths, weaknesses, opportunities, threats, industry lingo, financial summaries for sales prep, already in minutes.

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Stuff that used to take hours, maybe days of research.

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Done, just like that.

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Wow. And GoDaddy, IELTS blog, invoice factoring, they mentioned using AI for really personalized marketing.

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Hyper-personalized, yeah. Targeted ads, lead scoring, figuring out who your best prospects are, generating personalized emails and content automatically.

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At scale.

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At scale. And remember, what makes generative AI different? It's right there in the name, isn't it?

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It generates, it creates.

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Exactly. It doesn't just analyze data, it creates new things, text, images, ideas.

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So that's why sources like GoDaddy, IELTS blog, Ray Contour mentioned using it for creative content, websites, blogs.

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Videos, newsletters, you name it. That Ray Contour piece highlighted a company, Phoenix Fire Design.

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Oh yeah. What were they doing?

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Using tools like ChatGPT and Bard, just for drafting content. And they saw a real efficiency bump, as they put it.

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This is from drafting content. GoDaddy also mentioned social media help.

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Oh yeah.

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Brainstorming captions, creating content calendars, writing ad copy, even keeping your posting schedule consistent.

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Which is always a struggle for small teams.

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And SEO optimization, too. Keyword research. Generating SEO-friendly texts, meta tags, blog post ideas, go-to-edit lists, all those as things AI can help with.

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Okay, let's shift gears. What about HR? That's often a one-person show, or even less, in an SMB.

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Right. Software One suggests AI assistance for that. Imagine an assistant that can answer employee questions about the handbook, benefits, policies.

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Anytime.

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Two hundred and four seven self-service. Especially useful for onboarding new hires. And the IL blog mentions automating recruitment tasks, screening resumes, scheduling interviews.

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Taking some of that admin burden off, what about finance? That can be a huge time thing.

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Software One talks about doing sophisticated data analysis right inside Excel, using AI and Python integration.

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So you don't need a dedicated data analyst?

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Exactly. Smaller teams can dig into cash flow, forecasting, budgeting, really powerful stuff. The IL blog adds automating basic bookkeeping, categorizing expenses, tracking income.

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Simple stuff, but it adds up.

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It really does. And that invoice factoring source even suggested using invoice factoring itself to free up cash specifically to invest in these AI tools.

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Interesting angle. Okay. Operations and admin.

Lots of repetitive tasks there.

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Huge potential. IL blog and invoice factoring mentioned automating scheduling, payment processes, supply chain management.

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Software One pointed to making meetings more efficient.

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Yeah. AI generated summaries, action item tracking, even helping prep beforehand. Inventory management is another big one.

Software One and Rachntor mentioned that.

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Predicting demand, maybe.

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Exactly. Analyzing patterns. Rachntor highlighted FC Beauty using predictive analytics, though they used external partners for it.

Software One also mentioned drafting responses to RFPs or RFQs.

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Those big proposal documents?

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Yeah. AI can help get a first draft going. And Rachntor featured Get Transfer, a company that developed its own AI for things like process automation and even automated software testing.

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Wow. Building their own. Okay.

Customer service seems like a really natural fit too.

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Definitely. Enhanced customer experience is a key benefit mentioned by the IL blog.

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Chatbots, right. Like Antoinette Vanasek used in her insurance agency in that marketplace piece.

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Exactly. Handling common questions instantly. GoDaddy and the IO blog also talk about AI helping craft personalized responses to inquiries or complaints.

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And GoDaddy noted AI can handle multiple customer interactions at the same time.

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Yes. Which is a massive capacity boost for a small team.

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And that marketplace piece also mentioned Vanessa Jup's company, Leyva.

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Right. Using AI to personalize content and support for new mothers shows how it can enable really deep, specific connection.

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What about internal stuff like company knowledge?

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Software One highlights that too. Building these unified knowledge hubs.

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So employees can just ask questions and get answers based on company info.

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Pretty much. And the knowledge stays there, even if team members leave or the team grows. It's like building a searchable, intelligent company brain.

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That's cool. Now, this surprised me a bit. The LinkedIn report found more businesses use Gen AI for innovation and creativity than for automation.

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Yeah. 70% for innovation versus 60% for automation.

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So things like brainstorming, idea generation.

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Content creation beyond just text, design help, product development. The report suggests AI isn't just taking over tasks. It's freeing up people's time so they can be more creative.

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That's a really interesting flip. We also saw some other cool company examples in Ray Contour Marketplace.

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Git Transfer using AI for driver bidding, right?

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Yeah. And Allcasting using it for virtual auditions and talent discovery. They even said it helped promote diversity by removing geographic limits.

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It's clear the applications are incredibly broad, really impactful. And as Rekentur emphasized, a lot of this can be surprisingly accessible, even if you're on a tight budget.

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Okay, so if the potential is so huge and accessible, why isn't every single SMB jumping on this right now? Ah, the million dollar question.

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The sources definitely point out that adoption rates are lower for SMBs compared to the big guys. Challenges of AI implementation, Rekentur, LinkedIn, they all say this.

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Yeah, that challenges piece noted 31% of UK small businesses are still reluctant. There are real hurdles.

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So what are they? If you're running a small business, what are the things holding you back?

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Several sources map these out pretty clearly. Cost is definitely one that comes up a lot.

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Right. The initial investment in software, maybe hardware.

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Yeah.

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Ongoing costs.

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Maintenance, updates.

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Yeah.

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Yeah. And the perception that the really sophisticated stuff is just too expensive. That's from the challenges of AI and invoice factoring sources.

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But hang on. Didn't that invoice factoring report say the typical spend was only like $1,800 a year? That sounds pretty affordable.

How does that square with cost being a major hurdle?

[Avatar 1]
That's a really important nuance. You're right. The invoice factoring source did find that $1,800 median spend.

[Avatar 2]
So it suggests that while custom AI builds or really high-end complex systems can be expensive, the challenges source mentioned ranges from $5 up to $50 plus. OK. The entry point, especially with cloud-based generative AI platforms that have flexible subscriptions, can actually be quite low.

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So the perception of high cost is maybe a bigger barrier than the actual cost for many starter tools.

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Exactly. It might just be a lack of awareness about those more affordable entry points. The sticker shock of the high-end stuff scares people off before they see the cheaper options.

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Got it. OK. Next big one seems to be lack of technical expertise.

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Huge one. Challenges of AI, Ray Contour, LinkedIn. I'll mention this.

SMBs often just don't have people in-house with the skills to use AI efficiently.

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Or they can't afford to hire dedicated data scientists or AI specialists.

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LinkedIn found over half of businesses see lack of technical skills, 57%, and AI literacy skills, 60%, as major barriers.

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And competing for that top-tier AI talent, the pool is tiny, right? Less than 1% globally.

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According to LinkedIn, yeah. So it's much harder, much more expensive for an SMB to attract those people compared to a Google or a Microsoft.

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OK. What about issues with the AI itself, like reliability, errors, bias?

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Yeah. The challenges of AI source brings that up. AI systems aren't perfect.

They can make mistakes, especially if the data they were trained on was limited or flawed somehow.

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And bias is a big concern, too, isn't it? Harvard Business School Online talks about algorithmic bias.

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It is. It happens when the training data unintentionally reflects existing societal biases. This can lead to unfair or discriminatory outcomes in things like hiring or who gets access to certain resources.

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So how do you even deal with that?

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Well, the HBS source suggests things like making sure diverse groups of people are involved when you're collecting data or making decisions using AI, having open conversations about potential issues, regularly checking the systems for unintended consequences.

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OK. Then there are data issues more broadly.

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Right. Limitations in the training data you have access to or just the challenge of managing large amounts of data if you're generating it.

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And Harvard Business School added that weird point about keeping data you don't need actually being a security risk.

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Yeah, it sounds counterintuitive. But the more data you hold on to, the bigger the target you are and the more there is to potentially lose in a breach. So minimizing data storage to just what's essential is actually a good security practice.

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Speaking of security, cybersecurity risks are massive, right?

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Huge. These AI systems often handle your most sensitive information, customer data, financials, employee details.

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Making them prime targets.

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Exactly. HBS highlights threats like phishing, malware, ransomware. And they cited a really worrying stat.

Eighty five percent of security leaders say recent attacks are now using AI themselves.

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Wow. AI fighting AI. So security can't be an afterthought.

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Absolutely foundational. HBS stresses clear data practices, communicating policies, strong security measures like multifactor authentication and training your team to spot threats.

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And privacy concerns go hand in hand with security naturally.

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Collecting, storing, using data responsibly, preventing unauthorized access or misuse. HBS emphasizes transparency and strong data governance again, being clear about what you collect, why and how you protect it.

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Then there's just a general lack of understanding, skepticism. Ray Contour and Marketplace mentioned that.

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Yeah, sometimes people are just unfamiliar or wary of new tech. Marketplace noted that getting past that often takes education and showing clear practical benefits.

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And finally, compliance in IP, keeping up with data protection laws.

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Which are always changing as challenges of AI and HBS point out.

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And figuring out who owns AI-generated content preventing IP theft. That's tricky.

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Definitely complex legal ground there. And we shouldn't forget the digital divide issue either.

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Right. HBS mentioned some industries like manufacturing or traditional retail might find it harder to leverage AI easily, risking falling behind.

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And LinkedIn pointed out the uneven impact on different workers and populations too.

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Which brings us right to the human element. This AI shift is profoundly changing the labor market, isn't it? LinkedIn really stressed that.

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It is. But it's crucial to understand it's not just about jobs disappearing.

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It's about jobs transforming.

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Exactly. And new ones being created. HBS used that ATM analogy.

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Oh yeah, ATMs displacing some tellers, but creating new jobs in manufacturing, maintenance, software, and shifting the teller role itself.

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Right. It's a historical parallel. While HBS cited a figure, 85 million jobs could be displaced globally by 2025.

[Avatar 1]
Which sounds scary.

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It also noted 97 million new jobs requiring different skills are emerging alongside that.

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So a net gain, but requiring adaptation.

[Avatar 2]
And the demand for talent in these new AI related areas is immense. LinkedIn found 63% of businesses using Gen AI actually plan to increase their headcount.

[Avatar 1]
Increase? Why?

[Avatar 2]
To drive the AI transition, meet new demand created by these tools, support new ways of working.

[Avatar 1]
Okay, so what skills are actually needed in this new landscape? The sources broke it down, right? First, the obvious one, AI technical skills.

[Avatar 2]
Yeah, the deep expertise to build and deploy AI. But like we said, that talent pool is less than 1% globally, according to LinkedIn.

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Hiring quadrupled in eight years for those roles.

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Crew 30% faster than the supply. AI engineer was the fastest growing job in the US and UK last year.

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Making it super tough and expensive for SMDs to compete for them.

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Very tough.

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Okay, so building AI is one thing. What about just using it? That's AI literacy skills.

Exactly.

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The ability for everyday professionals, non-technical people, to use AI tools effectively in their day-to-day work.

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And demand for that is rising fast.

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Hugely. LinkedIn saw jobs listing AI literacy increase six times in the past year.

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Six times. And leaders are noticing.

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Two-thirds, 66% of leaders in that LinkedIn survey said they wouldn't hire someone without AI literacy skills today.

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Wow. Are people picking up on this? Are they learning?

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They are. LinkedIn members are adding AI skills to their profiles like crazy, 177% increase. Especially things like ChatGPT and prompt engineering.

[Avatar 1]
Prompt engineering telling the AI what you want it to do effectively.

[Avatar 2]
Right. But here's the catch. There's a gap.

Only about half of businesses plan to actively upskill their current employees in AI literacy. Leaders say they struggle to find the time or resources for that training. 58% cited that in the LinkedIn report.

That's a critical bottleneck for SMBs.

[Avatar 1]
Definitely. Okay, third skill category, people skills. Communication, leadership, critical thinking.

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These are becoming more valuable, not less. Because they complement what AI can do. AI can't do these things.

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Right.

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These skills are growing in importance, even in tech roles. LinkedIn mentioned companies using AI coding tools like GitHub Co-Pilot. They're actually hiring engineers with more non-programming skills now.

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Like project management, communication. Yeah.

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Because the AI handles some routine coding, freeing up the humans for more complex collaboration and problem solving. HBS pointed out, Gen AI can't replicate leading people, intuition, charisma, building real relationships.

[Avatar 1]
There's uniquely human things. Now, the sources also warn the impact won't be equal, right? Some jobs are more exposed.

[Avatar 2]
Yes. Jobs where the core tasks are highly replicable by generative AI. LinkedIn gave examples like admin assistant, legal associate, librarian.

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And certain industries too. Tech, media, finance.

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Professional services, yeah. Those are tasks often involve processing information or generating standard documents.

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And certain demographics were mentioned as more exposed. Women, younger workers, those with undergrad degrees.

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According to LinkedIn, yes. But it's really important to understand the why there.

[Avatar 1]
Okay.

[Avatar 2]
It's not saying these groups will lose jobs. It's about the types of skills currently concentrated in roles often held by these groups. Women, for instance, might be in roles with GAI replicable tasks.

But LinkedIn also notes many possess strong people skills AI can't replicate, which are in high demand.

[Avatar 1]
So it's complex.

[Avatar 2]
Very. Young workers might be in entry level roles with more automatable tasks and haven't had as much time to build those deep people skills yet. Undergrad degree holders might be in broader roles AI can assist with compared to highly specialized graduate degree holders.

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But the key point, as LinkedIn stressed, is that exposure doesn't automatically mean displacement.

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It means the way you work is likely to change. Success hinges on having the skills and support to adapt.

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Okay. So pulling it all together, what does this mean for you if you're listening and running a business? How can you actually overcome these hurdles and grab these opportunities?

[Avatar 2]
The sources offer some really practical strategies and point to support initiatives.

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Let's start with managing costs and just getting started with the idea that invoice factoring source had tips, right?

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Yes. Number one, absolutely crucial. Start small, scale gradually.

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Don't try to boil the ocean.

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Exactly. Pick one specific pain point or one clear opportunity. Don't try to implement everything at once.

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And leverage free or low-cost tools first.

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Definitely. Free tiers of things like Canva, ChatGPT. Affordable plans for software you might already use like QuickBooks or HubSpot.

Those Gen AI platforms often have flexible subscriptions. Making the entry point manageable.

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Use cloud solutions to avoid big hardware costs like Google Workspace with its AI features.

[Avatar 2]
Good example, yeah. Avoid needing servers and heavy IT maintenance. Use pay-as-you-go models if you can, especially when testing things out.

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Focus on ROI first. Where will AI give you the biggest bang for your buck quickly?

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Often marketing and sales, as invoice factoring noted. Also, tap into free training from vendors. They mentioned the HubSpot library as an example.

Lots of free learning material out there.

[Avatar 1]
Monitor your usage, adjust plans. Don't just set it and forget it.

[Avatar 2]
Right. And combine AI with tools you already have rather than ripping everything out. Look for AI add-ons for your CRM or accounting software.

[Avatar 1]
And if even those subscription costs feel like a stretch up front, that invoice factoring idea again.

[Avatar 2]
Yeah. Unlock cash flow from your unpaid invoices to fund that initial AI investment. It's one financial tool to consider.

[Avatar 1]
Oh, okay. Practical steps for the tech and the budget. What about skilling up your team, preparing your workforce?

[Avatar 2]
Investing in employee training. Absolutely critical. IL blog, LinkedIn, HBS.

They all hammer this point.

[Avatar 1]
Upscaling and reskilling your current team. Often cheaper and easier than hiring new experts.

[Avatar 2]
And software one suggested creating an environment where people feel safe to experiment, to play with these tools, to keep learning. Don't punish mistakes early on.

[Avatar 1]
How about dealing with those risks like bias?

[Avatar 2]
HBS had practical advice. Involve diverse team members in data collection and decision making. Talk openly about how the AI is performing.

Regularly review it.

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And for privacy and security.

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Clear, transparent data practices. Communicate policies. Strong security measures.

Minimize the data you store. Train your people. Foster that diverse, inclusive environment when rolling out tech.

And invest in training for roles that might be impacted most.

[Avatar 1]
Leadership has a big role too, doesn't it? Huge.

[Avatar 2]
Leaders need to communicate the why. Address concerns. Provide resources.

And think through the implications.

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And governments. Policymakers. LinkedIn said they have a role too.

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A significant one. Targeted financial help grants. Subsidies for SMB adoption.

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Funding training programs. Improving digital infrastructure.

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Supporting nonprofits. Reaching underserved communities. Investing in education all the way from schools to universities.

Promoting skills based hiring. Which broadens the talent pool.

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Leveraging free online content. Supporting human skills development.

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Tracking the impact of AI on jobs and making that data public. Launching public awareness campaigns.

[Avatar 1]
And those public-private partnerships sounded promising too. Like the Mississippi AI Collaborative.

[Avatar 2]
Yeah, or the UK's AI Opportunities Plan. Germany's Hubs for Tomorrow. Giving free support to SMBs.

The France Travay LinkedIn Partnership. India's AI for All. These show support structures are actually being built.

[Avatar 1]
Okay, so let's try to wrap this up. To recap this deep dive. We've seen the immense, really tangible potential of AI for small and medium businesses.

[Avatar 2]
Incredible time and cost savings, yeah. Leading to better decisions. Boosted productivity and actual revenue growth.

[Avatar 1]
And a huge range of practical uses. Sales, marketing, HR, customer service. Almost every part of the business.

[Avatar 2]
But we've also looked squarely at the challenges. Real ones. Cost perception versus reality.

The skills gap.

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Data issues, bias, cyber security risks, skepticism, compliance, and the impact on people.

[Avatar 2]
That's a lot to navigate.

[Avatar 1]
But it really seems from sources like the IL blog that strategically using AI, it's becoming a necessity, right? Not just a nice to have anymore.

[Avatar 2]
That seems to be the direction, yeah.

[Avatar 1]
Yeah.

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Staying competitive increasingly means figuring this out.

[Avatar 1]
So the key takeaway isn't just go buy some AI.

[Avatar 2]
Definitely not. It's strategic adoption. Start small, manage the cost smartly.

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And absolutely, crucially, invest in your people. Human skills, training, alongside the tech.

[Avatar 2]
It's about integrating AI into how your team works, how they learn, how they create value, that partnership.

[Avatar 1]
So for you listening right now, maybe think about this. What's the single most time consuming repetitive task you or your team does? How could AI potentially transform that?

[Avatar 2]
Or flip it around. Where could AI unlock totally new creative potential in your business?

[Avatar 1]
Yeah.

[Avatar 2]
Something you just don't have the bandwidth for today.

[Avatar 1]
Because the AI era, it feels like it's not just about the technology itself.

[Avatar 2]
No, it's about how we, as people, learn, adapt, and work with these intelligent tools, how we partner with them to create something new.

[Avatar 1]
A better workflow, a more creative idea, a stronger customer connection.

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That partnership between human intelligence and artificial intelligence.

[Avatar 1]
Yeah.

[Avatar 2]
That really seems to be where the greatest promise lies.

[Heather Bayer]
So what did you think? I use this a lot. If I'm using Notebook LM, I've got a lot of sources in there.

I can just go across and ask it to create this podcast, or I ask it a question, create me a podcast segment on a specific part of what I'm looking for that I know will be in those sources. And then I can just download that and take it out and listen to it while I'm walking the dog. It's just like listening to another podcast.

So you can access Notebook LM right now. It's notebooklm.google.com or just Google Notebook LM. It's completely free. I believe there is a paid version. I use it a lot and I have never had to pay for it. It's just fun. It's free. It's fast. It's fun to use. So go try it today. So upload some reviews. Upload some of your listing descriptions or strategy notes or whatever you've got and then start asking it questions and see what this AI powered assistant can actually do for you.

So again, that's notebooklm.google.com. You'll find the link in the show notes. And I'd like to hear what you come up with your audios. So do share those with me. You know you can get in touch with me at Heather@vacationrentalformula.com. I always love to get your emails and always respond to them. And of course you can find me on LinkedIn. My LinkedIn profile is in the Show Notes as well. Just put my name in the search bar in LinkedIn and you'll find me. Follow me. I will follow you back.

So I hope you enjoyed that. I felt it was a little bit different. A little bit off the wall. I'm going to continue on this AI train. I know that. And I know that the podcast seems to be shifting over more towards AI. And in fact, as you listen to this, if you listen to this on the day of publication, I will be leaving the following morning to go to Orlando for a three-day immersive AI conference. So you're going to hear all about that next week as I tell you all the things I've learnt from that summit. And I know there's going to be a lot. So stay tuned, keep in touch, and I'll look forward to being with you again next time.

It's been a pleasure as ever being with you. If there's anything you'd like to comment on, then join the conversation on the show notes for the episode at vacationrentalformula.com. We'd love to hear from you. And I look forward to being with you again next week. Bye-bye.

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