Ep 262: AI Sales Secrets Revealed – Work less. Sell more.

Integrating AI into the Sales Process

Artificial Intelligence (AI) has infiltrated most aspects of our lives, and the sales industry is no exception. However, it is largely used for surface-level tasks such as writing emails or summarizing meetings. The true potential of AI goes far beyond these simple tasks, indicating a need for transformation at multiple levels: AI assimilation, AI integration, and AI innovation.

Taking the integration further, AI can be employed to delegate micro-tasks, freeing up valuable time. This allows the sales team to focus on more significant aspects of their job and improves overall productivity.

Harnessing AI for Detailed Insights

One of the most innovative applications of AI involves using large language models to analyze sales call transcripts. By dissecting the patterns, objections, and language used by clients and prospects, businesses can gain invaluable insights. This new information can be integrated into marketing messaging and product design. Considering the immense possibilities, the ability to summarize a company's annual report within minutes using AI demonstrates the time-saving potential.

Offering plenty of AI tools for various tasks, ranging from research to content creation, there are resources available to every sales team. Despite the potential challenges in implementing generative AI, the benefits can far outweigh any hurdles as long as leaders focus on understanding and nurturing it.

Potential Shift towards AI-Powered Sales Agents

The discussion goes on to indicate the potential shift towards AI-powered sales agents, simultaneously highlighting the impact on the human connection in sales. It remains crucial not to forget the importance of the human touch in making sales, with AI simply being a tool to aid the process.

3-Step Plan to Better AI Integration

To make the most of AI, start by replacing traditional tools, such as Google, with AI tools for 15 minutes a day. Maintain a log of AI usage and brainstorm new applications. Over time, AI becomes a more integral part of the workflow and very likely a game-changer in sales.

Time-Saving Potential in Sales

AI has the potential to streamline sales by automating non-selling activities, freeing more time for actual selling. Instead of devoting a massive 72% of their time on non-selling tasks like research and preparation, salespeople get more time, potentially doubling their selling time.

Tapping into the Full Potential of AI across Sales Verticals

Leveraging AI technology across departments and verticals in sales can bring immense potential productivity. While it’s prudent to be aware of the repercussions of using bad AI-generated content, precautions and careful adoption can lead to promising results.

By embracing the power of AI and integrating it effectively across facets of the sales process, businesses can realize substantial benefits. A well-implemented AI strategy can enhance productivity, offer deeper insights, and most importantly, transform the dynamics of selling in a digital world.

Topics Covered in This Episode

1. Power and Potential of AI in Sales
2. AI Tools Used and Recommended
3. AI Skills Transformation


Podcast Transcript

Jordan Wilson [00:00:17]:
In the end, so many of us are essentially in sales. Right? Even if you don't have the word sales in your title or even if you're not technically selling a product or service every single day. Ultimately, you're selling something. Right? And and and you're going through a lot of these activities that a traditional salesperson might be going through. So I thought it was important for us to revisit how AI can really benefit sales, and I'm I'm very excited today to talk about some AI sales secrets revealed and how you can work less and sell more. Alright. So, if that sounds like something you need to know, then today's show is for you. Alright.

Jordan Wilson [00:00:55]:
So before we get into that, let me first welcome you to Everyday AI. My name is Jordan. I'm the host of Everyday AI, and this is for you. This is your daily livestream podcast and free daily newsletter that serves as your guide to learning and leveraging generative AI. So, thank you for joining us. Whether you're listening on the podcast, please make sure to check your show notes as always for additional, information related, shows, all of that. My my email, my LinkedIn is in there. Please feel to reach out with other questions.

Jordan Wilson [00:01:23]:
If you're joining us on the livestream, as always, thank you. So, Fred, who's who's tuning in, saying, hope hope I'm feeling better. I'm feeling a little better. Juan joining us from Chicago and and Rolando from South Florida. Woozi from Kansas City. Thank you all for joining. As always, we do this live unedited, unscripted, so you can come in and and interact with our audience. So if you do have questions on how AI could be used or maybe should be used in sales, make sure to get them in now.

Jordan Wilson [00:01:49]:
Alright. Before we get started, let's go over what's going on in the world of AI news. So first, is the new Rabbit r one device simply an Android app? So the new AI hardware device startup rabbit is under a bit of fire after recently shipping out its first round of rabbit r one. So the r one was marketed as this standalone device that didn't need a smartphone and function as a large action model using AI and the Internet to perform actions on the user's behalf. Initial reviews, though, have accused the software running the r one to be nothing more than a slightly modified Android app and not this bespoke large action model or unique software that the company suggested. So the Rabbit team clarified that the Rabbit r one is not solely or just an Android app. They explained that the Rabbit r one operates using Rabbit OS and the large, the large action, in the cloud. So, initial reviews though of the AI powered product have been pretty negative similar to the humane pin.

Jordan Wilson [00:02:51]:
Alright. So, yeah, I'm I'm curious. I know a couple of our audience members have, have said on on the live stream here that they're getting the the Rabbit r one. I'd love to hear what you all think. Next piece of AI news. Amazon's AI assistant queue has now been released to the public after an initial limited release. So Amazon Web Services or AWS has released Amazon Queue, a generative AI assistant for developers and businesses with a new capability for employees to build their own AI applications using natural language. So the company also offers now free courses to learn how to use Amazon queue.

Jordan Wilson [00:03:26]:
So, AWS's queue is now generally available for all developers and businesses. And like we said, the AI powered assistant can help with simple tasks, such as coding, debugging, and also decision making using their large language model. So a new capability though is Amazon Q Apps, which allows employees to build their own AI applications without coding experience, just by talking. Right? Alright. And last but not least, hey. If you tuned in to our show yesterday, here's some very timely news. But the mysterious GPT 2 chatbot model is now gone. It is offline.

Jordan Wilson [00:04:03]:
Alright. So the large, the large model systems organizations just announced a couple hours ago that the mysterious GPT 2 chatbot model will be taken offline. So this is the group that runs the LMSYS website, which hosts the chatbot arena where the GPT 2 chatbot model was hosted. So LMSYS said that the preview of the model was only available as an unreleased model for testing and is now no longer available. Apparently, the demand was too high. I don't know. Maybe we talked about it yesterday and everyone went out and tried it and crashed their servers. But if you missed yesterday's show, the GPT 2 chatbot was a mysterious large language model that didn't have a lot of public information tied to it.

Jordan Wilson [00:04:45]:
In informal testing, though, it was consistently performing at a level similar to Claude 3 Opus, Google Gemini, and GPT 4. And many people speculated that GPT 2 chatbot, could or or GPT 2 chatbot could be the next version of OpenAI's model, such as GPT 4.5 or even GPT 5. So make sure you go read, yesterday's newsletter. We kinda gave you our prediction. But, in a Twitter announcement, the group said, and I quote, due to unexpectedly high traffic and capacity limit, we will have to temporarily take GPT 2 chatbot offline. Please stay tuned for its broader releases. Interesting there. Alright.

Jordan Wilson [00:05:25]:
So broader release may be coming soon. Alright. So we're gonna have that in a lot more in our newsletter. So if you haven't already, please make sure to go to your everydayai.com. Sign up for that free daily newsletter for more on that. But you didn't come here to read and talk about the AI news. Well, maybe you did, but you probably wanna know a little bit, about how you can better use AI for sales to to win back some of your time and and to get more sales activities done in less time. So, you don't have to listen to me, you you know, blab on about this.

Jordan Wilson [00:05:54]:
We have our guest for today. So, please help me welcome to the show. There we have him. We have Ryan Staley, the CEO and founder of Whale Boss. Ryan, thank you so much for joining Everyday AI Show.

Ryan Staley [00:06:05]:
What's happening, Jordan? Happy to be here, man. Love the news breakdown. You know, I kinda thought that same thing happened with Rabbit. Like, I was a little skeptical of that. Super excited about q at chatgpt or I should say not chatgpt. GPT 2. If

Jordan Wilson [00:06:19]:
you Yeah. Yeah. It's yeah. Like, who knows what that actually is, right, in the long run? But, hey, that's that's another show for another day. But Ryan, tell everyone, hey, from another one Chicago guy to another, right, tell tell everyone a little bit about what you do at Whale Boss.

Ryan Staley [00:06:33]:
Yeah. Well, it's really interesting, man, because I've gone through an evolution. And, effectively, what's happened was, I don't know. This is about a year and a half ago. Actually, it's almost like a year and 8 months. I got early access to ChatJPT, and when it was in its beta. And then at that time, when people had releases for it, they started to test it on things that they knew to be true. And, effectively, I did that, and the thing that scared and excited me, like, to my core, was that within 2 or 3 questions, I could get 90% of the way there of something that took me 10 years to learn.

Ryan Staley [00:07:08]:
Okay? And so, that alone was something that made me stand up and take notice, and so effectively, that made me reshape everything I was doing from a focus as well as a, go to market deliverable for my clients. And from then on out, I went from basically the formula took me from growing a company to 7 or I should say 0 to 30,000,000 in 5 and a half years with only 4 salespeople to really integrating AI into every kind of sales component possible, and then sharing that with people so that they could, for the first time in history, actually scale people.

Jordan Wilson [00:07:43]:
And, you know, Ryan, I'm sure that for our audience listening, there's people from all different spectrums. Right? Like right now of of how they're using or how they're implementing AI. I'm sure there's those similar to yourself that have found ways to integrate it, you know, kind of top to bottom. And then there's those people who are, you know, just dipping their foot into this new, AI powered sales world. Can you give us kind of a state of AI in sales? Where are we at? Are most people using it on a day to day basis? Is it still this kind of niche market? Like, you know, kind of give us the the overview of how sales teams in general are are viewing and using or maybe not using AI right now.

Ryan Staley [00:08:19]:
Yeah. That's a great question, man. I mean, I'm deploying this, helping this to or deploy this to to sales teams at scale. And so that's one of the offerings I'd use. I'll do basically custom training and integration, prop library setup, and workflows for teams. And it's really interesting because what you would think is the AI components are getting integrated in every product. However, when you look at the core use cases for LLMs or large language models like ChatChipt or Gemini or Copilot, most people are only using it for the surface level things, like writing emails or summarizing meetings. And there's 10 times more power that's available to people, whether they're in sales, marketing, a small business owner, an executive.

Ryan Staley [00:09:03]:
It doesn't matter, And they're not they're just really scratching the surface. I look at this as three levels. There's AI assimilation, which is kind of what I'm talking about, like high level use cases, AI integration, which is more infusing into everything that you do, and then AI innovation. And that those are the three levels of skill transformation. The innovation level is reverse engineering, outcomes and by prompts, prompt engineering, as well as creating GPTs. And then, you know, there's a lot more to it because those are gonna be the foundational elements for agents, which are gonna be released later this year. So those are some of my viewpoints on it, if if that helps.

Jordan Wilson [00:09:38]:
Yeah. No. I love that. And and and maybe let's start at the top then. Right? So when we talk about AI assimilation and and use cases, what are you know, maybe not some of the standard use cases because you said a lot of people are just scratching the surface, but when it comes to, you know, where you think most, you know, sales departments or sales organizations should start with generative AI. Where is it? Where are some of those most common use cases that are, hey. This is more than scratching the surface, but this is where you should really be looking at or this is where your your sales team should be starting when it comes to generative AI.

Ryan Staley [00:10:11]:
Yeah. That's a great question. I think there's patterns like, everything doesn't need to be bespoke. There are certain patterns of problems that people have. Because if you look at what a salesperson is doing or most time even sales leaders are doing is I equate it to when the model t was being created, prior to the industrial revolution. Right? You would have one craftsman who had created an entire car by themselves, and it would take you know 13 to 14 hours to create that car. Well, what happened is once they transitioned to the conveyor belt with specialization, they were able to create that same car in like close to 65 minutes and they amped up the production from 100,000 a year to 2,000,000 10,000,000 a year. Right? And so and by the way, all cost came down on everything.

Ryan Staley [00:10:55]:
So if you look at it, that's the same thing that's happening with white collar work because what what's happened is we have all these tools available to us that have kinda sprung up over the years. And specifically in sales, there's all these micro tasks like building a car that they have to do to get the sale, which is the car. Right? And by going through that process, what happens is their focus gets diverted, they get frustrated, they're good at 4 out of the 25 things that they have, right, have to do, and they probably only like maybe 3 out of the 4 things that they have to do, right, of the 25. But what I'm what I'm saying where what's possible is by integrating that and basically delegating or doing the 4 to maybe 6 things that you have to do, and then delegate the rest to AI. And, oh, by the way, in some of those situations, AI is gonna do way better than you. So that's kinda how I look at it philosophically, if that makes sense. We can get more granular if you want as well.

Jordan Wilson [00:11:49]:
Yeah. Yeah. I mean, absolutely. You you know, one thing that I want to know is is how even your personal implementation or use cases, have changed, you know, over the years for for your own sales efforts. Can you give us even a high level overview of maybe, you know, maybe what was that one big first shift? You you know, because I think early on, a lot of people, you you know, like you said, started using different generative AI, different large language models for those very high level scratching the surfaces. Right? Like, maybe doing some research or maybe helping with emails, but maybe what was one implementation that even for you personally that really helped change your sales outlook?

Ryan Staley [00:12:28]:
Yeah. That's a great question. So I think, like, there's the basics where there's, like, the micro productivity task where you repeatedly do them throughout the course of a week, and then there's more deep work. Right? So I'll give you an example, and this is crosses over into sales and marketing. I just did this the other day, so it's fresh on my mind. So because the context windows of the large language models, which is basically how many tokens or kinda words and letters you could put into the large language models has massively expanded, there's a lot more opportunities. So what I did effectively is I took the transcripts from all the sales calls I've had over the last couple months, and then basically identified patterns of questions, objections, as well as verbiage that my clients and prospects are using. So then I could integrate that into marketing messaging.

Ryan Staley [00:13:16]:
I could proactively cover those objections before they come up and customize the material. And so that's one way where I think it touches a lot of parts of the business, and then that'll also feed into product design. So you got sales, marketing, and product all just by dissecting at scale conversations and direct feedback from clients. So that's one that I think is really exciting. Other things with when it comes to transforming sales, if you will, is, like, I'm a business owner myself. Right? But I'm also doing a lot of sales work. And so if I could do things in minutes that that take a half hour, an hour, that's gold. Right? And so, like, one of the things that we talked about and we mentioned I mentioned this to you on the preshow is literally I could do a process that takes 45 minutes in terms of looking at a company's annual report.

Ryan Staley [00:14:05]:
The challenges that they cite in their 10 k earnings report, as well as the top priorities from letter from the CEO, and have those all summarized within a couple minutes, and then integrated into a pre call script, basically questioning that I have exactly for the person I'm meeting with. Right? And that's all we're talking all that in a few minutes. It would take me 45 minutes to do that level of prep. And when I met with the this was a while back, but met with a, the senior director of sourcing at at Lowe's Home Improvement. Basically, one of the things he said that my team did really good with, and this was this was a while back, was that we understood at a deep level who he was, how he was evaluated, and what was going on in their company. And he said 90% of salespeople don't do that. And that was a a gentleman who had a $60,000,000 budget. So you could imagine how many people he saw, and this is fortune 50.

Ryan Staley [00:14:57]:
So they're not doing it at the fortune 50 level where the stakes are the highest. Imagine how much they're not doing at the lower levels as well.

Jordan Wilson [00:15:03]:
You know, I think, Ryan, what you bring up there is, at least even for me, it's it's one of my favorite use cases, for generative AI because, you know, whether you are in a sales role or marketing or admin or operations processes, it doesn't matter, right? Like something that, you know, so many skilled knowledge workers do is they have to read, they have to research, they have to analyze, and then they have to personalize that information for their own use cases, which is something that large language models do very, very well. You you know, I'm I'm curious and, you know, not asking you to pull, you know, data out of hat, but how much time, you know, would you say on average whether for yourself or for your clients, right, turning those, you know, 45 minute processes into a couple of minutes. How much first of all, how much time, right, because one of the the whole aspects of this show is is is how you can, you know, spend less time selling and get more sales. So how much time overall do you think that this is saving just going through one of those simple high level processes?

Ryan Staley [00:16:05]:
Yeah. So what I I think is, like, if you look at all of the the micro or the time piranhas or energy vampires, they they basically disintegrate by using it. I think if you're in sales, you could you could take out easily 10 hours a week. Right? If you do 10 hours a week, that's effectively 3 months a year that you can give back. And the beautiful thing is it's not just the time, it's the focus and energy that you that you also get as well. Right? And so, I think the same applies for revenue leaders, executives. For myself, where you're doing a lot of different things, you know, basically being a founder and a CEO, I have a small team of of people, but I think it basically 2 x or 3 x what's possible for me too. Not just from a more quantity of work, but quality of work that I didn't have the skill set to do, like graphics, like, basically deep writing, like creating videos.

Ryan Staley [00:17:00]:
Like, those are things that I could do instantly now that I didn't even have the skill set to do that would have taken me days to learn how to do them and then do a crappy job, Adam.

Jordan Wilson [00:17:09]:
You know, and and I'm curious, you know, for salespeople, right, historically, how much of their time is actually spent selling versus doing these things now that large language models can do very well. Right? Things like researching, analyzing information, personalizing it, you know, because I'm curious. It seems like the role of sales is a lot of preparation and in reading and analyzing and not a ton of sales. So can you give us any any kind of facts or estimates on this and then talk a little bit about how AI can maybe flip the script.

Ryan Staley [00:17:43]:
Yeah. So roughly right now and and Juan's asking a great question in there that I could try and integrate in there of where it's going. So, basically, you know, where it's at right now is roughly about 72% of selling time or 72% of a salesperson's time is spent on non selling activities. Right? So that could be research, prep, a lot of different list building, a lot of different areas. Right? And so and only I don't know. It's about 18, 20% is actually spent on selling when you you figure it out, and that includes prospecting. I think by shrinking the non selling times, you could effectively double the amount of time that each person has to sell. And then at the same time, you could double the quality and of the selling experience, basically improving significantly the conversion, which can lead to a 2 x output.

Ryan Staley [00:18:30]:
Right? And so if you look at how this transfers down screen, the answer one one's asking, like, you know, where AI would replace cold calling, emailing, STRs, and then, you know, would it go to an AE? What I think is gonna happen is where processes will be automated, they will be. Right? So, however, like, I I think we're a little while off from that, not super far, but, I also think you're more secure when it comes to higher dollar value, basically solutions that you're selling because of the fact that there's more complexities, more people in, so it's not a linear process. And so what's gonna happen though is it's gonna get to point where we move from AI assisted selling to basically we're just directing the AI and it's doing the bulk of the work for us with human oversight. So that's where the transition is gonna go. Gartner even identifies that as well as a trend that's happening. And one of the things that I mentioned about agents is there's agents out now, and, basically, agents are autonomous workflows where you identify the outcome. Kinda like Tony Stark in Iron Man, where he talks to Jarvis, and Jarvis construction does multiple things and just delivers an outcome. Right? We are going to get to that point.

Ryan Staley [00:19:42]:
But what my belief is, if you don't understand the core elements or the prompting level, then what's gonna happen is it's like the equivalent of sending a really bad email sequence out to a 1000000 people. Right? Like, yeah, you could reach everybody, but it's gonna be just spam at scale. Right? And that's what we wanna avoid.

Jordan Wilson [00:19:59]:
Yeah. And I think that's one of those, tempting sides of of generative AI is that, yes, it it gives you the, abilities and capabilities to do work really well at scale. But on the other side or the other edge of the sword, it allows you to put out very bad sales or very bad marketing at scale as well. So, hey, everyone. Just as a reminder, we have Ryan Staley, the CEO and founder of Whale Boss. So if you do have any questions, please get them in now. So this one from Woosy asking, Ryan, what's the most creative workflow you have seen set up in sales using AI, and what's the dumbest workflow you have seen set up in sales using AI? So let's maybe smart. We'll, start with the, you know, most creative or the best, type of workflows that you've seen, Ryan.

Ryan Staley [00:20:44]:
Yeah. I think, like, in terms of, like well, let me let me hit the worst one, and and I'll do that first. So I think, like and and Ethan Molick talks about this who just released a book. I had it right next to me, but I don't. An AI book that he just released. It's really good. He's a a Wharton professor. And, you know, one of the things he talks about is basically AI is like a jagged edge, right, in terms of what it could do.

Ryan Staley [00:21:09]:
It could do things exceptionally well, and then does things really terrible. So what I think is, the worst, like, examples that I see are when an email says, yeah, Co Intelligence. There you go. Little shout out to Ethan Mullick. It's a great book. I plowed through it. So, is when the message starts off with, like, I hope hope this finds you well. Right? It has that.

Ryan Staley [00:21:32]:
And then the other thing that it does too is it pulls up completely irrelevant data that isn't even applicable to what you do. Right? Where it's so obvious, it's like bad AI that it almost, like, offends you when you get it because people just, like, took a dump on your time. Right? You know, they're just gonna give you shitty emails. And so that would be an example of a terrible workflow. In terms of what I see is pretty amazing is when you do kind of like a chain of thought prompting, and there's a couple examples of this. One is it created a whole effective workflow in terms of building a sales department from scratch all the way from, you know, what what I wanted the outcome and the compensation to be. Right? So it built out a comp plan. It built out KPIs for evaluating.

Ryan Staley [00:22:17]:
It built out a management operating system. It built out a tech stack, and it built out a job description. And I did all this while I was had 20 minutes left on a plane, and I was about to land somewhere, and I wanted to do an experiment. Right? When we're talking more from, like, the individual contributor perspective, know, one of the things I think is amazing is when you have it do deep work on emotions, frustrations, fears, and desires for your ideal customer profile. And then at the same time, segment that down and integrate that in a customized messaging. So those are some of the things that I think it does really, really well. And there's plenty more that we could talk about whether it's, like, basically using Chris Voss from Never Split the Difference as a negotiation coach live in real time, or basically creating a book that goes from a general book that summarize, customized to you with an action plan that's delivered to you. So those are some really cool workflows I like, that I've seen that I use.

Jordan Wilson [00:23:17]:
You know, you know, speaking speaking of workflow, Ryan, I I think one thing that is constantly on people's minds, is how they can best leverage this technology across certain verticals or across certain departments. Right? Because everyone knows, oh, you can use, you know, chat g p t for this or you can use Gemini for that. But maybe, you know, I'm I'm curious. What are some of your kind of go to, you know, your go to tech stack or, you know, common, kind of AI sales enablement tools that if someone isn't maybe quite aware that they should be aware of? What are some of those, kind of leaders in the sales space for for AI tools?

Ryan Staley [00:23:56]:
So you could use Perplexity for free for research. It does an amazing job of real time research very fast. In terms of the core, like, stack that I use, I use, you know, the the basics. Mostly Chat, gbt, and Microsoft Copilot are the ones that I use the most. It's really interesting what's happening with the, the, basically, the giants or the juggernauts. You know, if you look at it, Microsoft has 365,000,000 Microsoft 365 paid users, and that's getting integrated in all the Office products. Google is doing the same thing with Gemini. Although, like, if you want a core use cases, like, I would say I found the best ones to be ChatGPT and Copilot because Copilot's powered by chat gpt, but also integrated into the work products.

Ryan Staley [00:24:45]:
Other ones that I like, if you're you know, I saw Ty was talking about being a solo person. Right? One of the things, tools that I like that's under the radar is a tool called Cast Magic, because I do a lot of speaking. I do a lot of, basically content creation on LinkedIn or YouTube. And so what it does is it it takes that that recording that you have, whether it's video or audio, transcribes it, and I can create multiple types of post, tweets, other things on that. And so it's very effective with that so it could customize content at scale. And then another tool that I like, last but not least, is for my prompt library. I leverage Text Blaze, which is a prompt expander. And I I recommend that for companies because you could track which are the prompts you use the most, as well as, you know, storing, basically collaboration and other areas for that.

Ryan Staley [00:25:36]:
So

Jordan Wilson [00:25:37]:
Yeah. I love that. What a what a great answer. And, you know, if if if you are a little new to the show, we did have the Cast Magic CEO on the show a couple months ago. You know, so we'll make sure to link that in the show notes as well. Another great question here, from Tanya. Tanya, thanks, thank you for this. So so, Ryan, she's asking, what is the error, between planning and implementation when it occurs? Because I'm sure that there's been many sales teams or departments that have been talking about, you know, integrating and then implementing generative AI now for months, and maybe they haven't fully done it.

Jordan Wilson [00:26:08]:
What would you say are are some of the common, pitfalls or some of the common reasons between this, you know, planning and implementation?

Ryan Staley [00:26:16]:
Yeah. I think and this isn't just with, sales teams. I think this is cross functional to any team. And so I think the number one area is, like, the leaders don't know how to use it, and they just try and delegate it to their team. And if you're not using it, you're not gonna understand the nuances. And so I would say that's one of the core challenges because this isn't regular software where it's a straight line process. It's gonna be like this, right, in terms of what it can do amazing. And so you have to use it to understand it.

Ryan Staley [00:26:45]:
So I think that's one of them. The other aspect is, besides the leader aspect, is not knowing what's possible. Right? And so, basically, just telling the team to go go ahead collaborate, figure it out, right, which is good. I think there there's some really immense value in that. However, if you don't give them kind of a jumping off point of some of the opportunities, it's hard to get their brain moving in terms of all the different use cases in areas of what's possible. And so I think to spark the innovation, the leader needs to know it, and they need to show them what's possible first, and that'll really fuel it. And here's what I would say. Most of the time, organizations are using it anyways.

Ryan Staley [00:27:25]:
And and basically also harvesting the top use cases from from the best performers as well.

Jordan Wilson [00:27:32]:
What's, you know, Ryan, I'm curious. What's next for you? What's next for for your business with your own, you know, company's AI implementation? Because I think people, you know, can always learn from not where people are currently finding success, but where they're looking at next. Because I feel, with anything generative AI, it's like you you blink in it. You, like, you miss a year of of development. Where are you and maybe where should others be looking at in the very near future when it comes to, you know, really leveraging and and utilizing AI for more sales?

Ryan Staley [00:28:05]:
It's a great question. And so what I would say is there's a the AI skill transformation, the progression pyramid of what I take, and the foundation is prompting, so understanding that. The next level are, you know, GPTs, if you will. And the GPTs are good. They're getting better. Right? And so what I'm looking at is beyond that, our agents, autonomous agents, as well as autonomous organizations of agents. So that's where the puck is going to to quote Wayne Gretzky in terms of what's happening. And so I think, like but here's what I would say.

Ryan Staley [00:28:37]:
If you understand how to use it, don't wait. Like, that's the worst possible thing you could do is be like, well, it's gonna change, so I'm gonna I'm not gonna I'm not gonna figure it out now. If you do that, you will get blown by everybody. So I would say invest as much as you can to use it, understand it. And, like, here's the thing, man. Like, if you use it literally for 15 minutes a day, you'll start to realize you're gonna get hours back a day, and then it becomes, like, it becomes so easy to become an expert at because you keep arbitraging your time. Right? And so that's what I would focus on. That's where I'm going.

Ryan Staley [00:29:08]:
And I think once again, the core foundational large language models is where I would start. Don't get caught in the wash of the 10,000 tools that are released every day. Just really understand the basics of the large foundation models, and then work from there.

Jordan Wilson [00:29:22]:
Such great advice. Right? Because, yeah, every every day there's dozens of new tools that seem like they're built specifically for you solving one specific problem, but those can come and go and, you know, get squashed with the next, you know, update from any one of the big, tech giants. So, you you know, one thing you mentioned there, Ryan, is is this, you know, maybe very near future, which which I believe. Right? I said this, you know, 6 months ago that 2024 is gonna be the year of kind of, you know, mainstream AI agents. But even on the other side, right, when we even talk about, you know, AI cold calling. Right? I I know there's, you know, some laws around that now, but are we going to see sales agents that are much less human, right, and and much more powered by AI, whether we're talking about, you know, text messages, emails, phone calls, videos, avatars. Is is that where sales might be heading, or is there still that, you know, something special about obviously being able to connect and talk with and buy from a human?

Ryan Staley [00:30:21]:
Yeah. I think it is going in that direction because there there's tools being created every day to do that. And so just like 24 is a year of agents we mentioned, it's a year of video too. It's gonna take the same leap in video, and it already is that the graphics took last year. Right? Imagine how bad, was at the beginning of the year with the graphics tools versus the end of the year. Same thing's gonna happen with video. And so, however, I'll tell you just from real world experience, and and it's funny before this whole AI storm happened, this was still something that most people forgot is, you know, I I think it was facilitated or augmented because of COVID. And so, what what I was seeing is people were getting just very, I wanna say cold, but just very processed tactical, not really in factoring the human element of what you talk about.

Ryan Staley [00:31:11]:
And so I think, like, some of the best things in the world you could do to differentiate yourself are non AI related because you're connecting with people at a true human level of not just what's important to them at work, but outside of work and what's driving that motivation for them at work. Right? And so if you could connect with them on that level and get on a text relationship with them just naturally, it's gonna transform, and it's gonna be so much easier than if you're sending out a 1,000,000,000 emails a day and you're masked you know, you're you're trying to do everything without talking people. We're still humans at at its core function, and we need to have that connection. And most people forget about that emotional connection.

Jordan Wilson [00:31:51]:
Yeah. I I I think that's that's a great reminder. Right? Because, I'm sure all of us get caught up and and swept into this, you know, nonstop and fast momentum of, you know, using AI everywhere for everything. So I think that's a a a great, call out there, Ryan, to to still remember that emotional human connection. So but we I mean, we've covered a lot in today's conversation, you know, how we can, you know, use AI to work, more efficiently and and how we can sell better and sell more by using AI at the right time in the right place. But, Ryan, maybe what's as as we wrap up here, what's what's the one, takeaway or maybe the one thing that sales leaders should be doing today so they can actually work less and sell more tomorrow?

Ryan Staley [00:32:33]:
Yeah. This is the simplest one, and I'm I'm gonna make the assumption that the sales leaders are not using it that much because that's what I'm seeing, and from conversations and trainings and all that. So the very basic simple advice was literally replace what you use Google for for 15 minutes a day and use chat gpt or use Copilot. And just that's step 1. Step 2 is be patient. And remember, this is like an alien life form. It's not like normal software. And you're talking to a human and treat it like you're talking to an intern.

Ryan Staley [00:33:06]:
And there's gonna be things that that person's good at, things they're not. And then step 2, and this is the part that most people miss. And I don't or they won't do, but it creates some of the best benefits. And it has it has nothing to do with AI. Well, it does, but it doesn't. Basically, have a log of what you used it for and write new ideas of how you could use it. If you just do that on a daily basis, and then you could, you know, basically do it on an Excel spreadsheet or or a sheet stock, What's gonna happen is you're gonna you're gonna have so many ideas, and it's gonna integrate into your body, into your soul, and your person so much of what's possible and how to do it, that it's gonna transform, you know, what you start to do with it. And it'll transform not only who you are, but it'll help you become superhuman in the process.

Jordan Wilson [00:33:53]:
Wow. Jeez. You can become superhuman and sell more in less time. I can't wait. That so much great information. Ryan, thank you so much for joining the Everyday AI Show. We really appreciate your time and your expertise.

Ryan Staley [00:34:07]:
Thanks, man. Appreciate being on. This is a lot of fun.

Jordan Wilson [00:34:09]:
Hey. And, hey, as a reminder, everyone, dropped a lot of knowledge there. Ryan just really gave us some of these, secrets to better use AI for sales. So if you haven't already, go to your everydayai.com. Every single day, we break down the conversation from the podcast, from the livestream, throw out a lot of other resources and next steps. So this is only half the battle. If you wanna win the war, it's done in our newsletter. So make sure to do that at your everydayai.com.

Jordan Wilson [00:34:37]:
Thank you for joining us today, and we hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.

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